importance of scope and limitations in research

How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

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How to Write the Scope of the Study

• By DiscoverPhDs
• August 26, 2020

What is the Scope of the Study?

The scope of the study refers to the boundaries within which your research project will be performed; this is sometimes also called the scope of research. To define the scope of the study is to define all aspects that will be considered in your research project. It is also just as important to make clear what aspects will not be covered; i.e. what is outside of the scope of the study.

Why is the Scope of the Study Important?

The scope of the study is always considered and agreed upon in the early stages of the project, before any data collection or experimental work has started. This is important because it focuses the work of the proposed study down to what is practically achievable within a given timeframe.

A well-defined research or study scope enables a researcher to give clarity to the study outcomes that are to be investigated. It makes clear why specific data points have been collected whilst others have been excluded.

Without this, it is difficult to define an end point for a research project since no limits have been defined on the work that could take place. Similarly, it can also make the approach to answering a research question too open ended.

How do you Write the Scope of the Study?

In order to write the scope of the study that you plan to perform, you must be clear on the research parameters that you will and won’t consider. These parameters usually consist of the sample size, the duration, inclusion and exclusion criteria, the methodology and any geographical or monetary constraints.

Each of these parameters will have limits placed on them so that the study can practically be performed, and the results interpreted relative to the limitations that have been defined. These parameters will also help to shape the direction of each research question you consider.

The term limitations’ is often used together with the scope of the study to describe the constraints of any parameters that are considered and also to clarify which parameters have not been considered at all. Make sure you get the balance right here between not making the scope too broad and unachievable, and it not being too restrictive, resulting in a lack of useful data.

The sample size is a commonly used parameter in the definition of the research scope. For example, a research project involving human participants may define at the start of the study that 100 participants will be recruited. This number will be determined based on an understanding of the difficulty in recruiting participants to studies and an agreement of an acceptable period of time in which to recruit this number.

Any results that are obtained by the research group can then be interpreted by others with the knowledge that the study was capped to 100 participants and an acceptance of this as a limitation of the study. In other words, it is acknowledged that recruiting 100 rather than 1,000 participants has limited the amount of data that could be collected, however this is an acceptable limitation due to the known difficulties in recruiting so many participants (e.g. the significant period of time it would take and the costs associated with this).

Example of a Scope of the Study

The follow is a (hypothetical) example of the definition of the scope of the study, with the research question investigating the impact of the COVID-19 pandemic on mental health.

Whilst the immediate negative health problems related to the COVID-19 pandemic have been well documented, the impact of the virus on the mental health (MH) of young adults (age 18-24 years) is poorly understood. The aim of this study is to report on MH changes in population group due to the pandemic.

The scope of the study is limited to recruiting 100 volunteers between the ages of 18 and 24 who will be contacted using their university email accounts. This recruitment period will last for a maximum of 2 months and will end when either 100 volunteers have been recruited or 2 months have passed. Each volunteer to the study will be asked to complete a short questionnaire in order to evaluate any changes in their MH.

From this example we can immediately see that the scope of the study has placed a constraint on the sample size to be used and/or the time frame for recruitment of volunteers. It has also introduced a limitation by only opening recruitment to people that have university emails; i.e. anyone that does not attend university will be excluded from this study.

This may be an important factor when interpreting the results of this study; the comparison of MH during the pandemic between those that do and do not attend university, is therefore outside the scope of the study here. We are also told that the methodology used to assess any changes in MH are via a questionnaire. This is a clear definition of how the outcome measure will be investigated and any other methods are not within the scope of research and their exclusion may be a limitation of the study.

The scope of the study is important to define as it enables a researcher to focus their research to within achievable parameters.

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The scope of the study is defined at the start of the study. It is used by researchers to set the boundaries and limitations within which the research study will be performed.

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How to present limitations in research

Last updated

30 January 2024

Reviewed by

Limitations don’t invalidate or diminish your results, but it’s best to acknowledge them. This will enable you to address any questions your study failed to answer because of them.

In this guide, learn how to recognize, present, and overcome limitations in research.

• What is a research limitation?

Research limitations are weaknesses in your research design or execution that may have impacted outcomes and conclusions. Uncovering limitations doesn’t necessarily indicate poor research design—it just means you encountered challenges you couldn’t have anticipated that limited your research efforts.

Does basic research have limitations?

Basic research aims to provide more information about your research topic. It requires the same standard research methodology and data collection efforts as any other research type, and it can also have limitations.

• Common research limitations

Researchers encounter common limitations when embarking on a study. Limitations can occur in relation to the methods you apply or the research process you design. They could also be connected to you as the researcher.

Methodology limitations

Not having access to data or reliable information can impact the methods used to facilitate your research. A lack of data or reliability may limit the parameters of your study area and the extent of your exploration.

Your sample size may also be affected because you won’t have any direction on how big or small it should be and who or what you should include. Having too few participants won’t adequately represent the population or groups of people needed to draw meaningful conclusions.

Research process limitations

The study’s design can impose constraints on the process. For example, as you’re conducting the research, issues may arise that don’t conform to the data collection methodology you developed. You may not realize until well into the process that you should have incorporated more specific questions or comprehensive experiments to generate the data you need to have confidence in your results.

Constraints on resources can also have an impact. Being limited on participants or participation incentives may limit your sample sizes. Insufficient tools, equipment, and materials to conduct a thorough study may also be a factor.

Common researcher limitations

Here are some of the common researcher limitations you may encounter:

Time: some research areas require multi-year longitudinal approaches, but you might not be able to dedicate that much time. Imagine you want to measure how much memory a person loses as they age. This may involve conducting multiple tests on a sample of participants over 20–30 years, which may be impossible.

Bias: researchers can consciously or unconsciously apply bias to their research. Biases can contribute to relying on research sources and methodologies that will only support your beliefs about the research you’re embarking on. You might also omit relevant issues or participants from the scope of your study because of your biases.

Limited access to data : you may need to pay to access specific databases or journals that would be helpful to your research process. You might also need to gain information from certain people or organizations but have limited access to them. These cases require readjusting your process and explaining why your findings are still reliable.

• Why is it important to identify limitations?

Identifying limitations adds credibility to research and provides a deeper understanding of how you arrived at your conclusions.

Constraints may have prevented you from collecting specific data or information you hoped would prove or disprove your hypothesis or provide a more comprehensive understanding of your research topic.

However, identifying the limitations contributing to your conclusions can inspire further research efforts that help gather more substantial information and data.

• Where to put limitations in a research paper

A research paper is broken up into different sections that appear in the following order:

Introduction

Methodology

The discussion portion of your paper explores your findings and puts them in the context of the overall research. Either place research limitations at the beginning of the discussion section before the analysis of your findings or at the end of the section to indicate that further research needs to be pursued.

What not to include in the limitations section

Evidence that doesn’t support your hypothesis is not a limitation, so you shouldn’t include it in the limitation section. Don’t just list limitations and their degree of severity without further explanation.

• How to present limitations

You’ll want to present the limitations of your study in a way that doesn’t diminish the validity of your research and leave the reader wondering if your results and conclusions have been compromised.

Include only the limitations that directly relate to and impact how you addressed your research questions. Following a specific format enables the reader to develop an understanding of the weaknesses within the context of your findings without doubting the quality and integrity of your research.

Identify the limitations specific to your study

You don’t have to identify every possible limitation that might have occurred during your research process. Only identify those that may have influenced the quality of your findings and your ability to answer your research question.

Explain study limitations in detail

This explanation should be the most significant portion of your limitation section.

Link each limitation with an interpretation and appraisal of their impact on the study. You’ll have to evaluate and explain whether the error, method, or validity issues influenced the study’s outcome and how.

Propose a direction for future studies and present alternatives

In this section, suggest how researchers can avoid the pitfalls you experienced during your research process.

If an issue with methodology was a limitation, propose alternate methods that may help with a smoother and more conclusive research project. Discuss the pros and cons of your alternate recommendation.

Describe steps taken to minimize each limitation

You probably took steps to try to address or mitigate limitations when you noticed them throughout the course of your research project. Describe these steps in the limitation section.

• Limitation example

“Approaches like stem cell transplantation and vaccination in AD [Alzheimer’s disease] work on a cellular or molecular level in the laboratory. However, translation into clinical settings will remain a challenge for the next decade.”

The authors are saying that even though these methods showed promise in helping people with memory loss when conducted in the lab (in other words, using animal studies), more studies are needed. These may be controlled clinical trials, for example. 

However, the short life span of stem cells outside the lab and the vaccination’s severe inflammatory side effects are limitations. Researchers won’t be able to conduct clinical trials until these issues are overcome.

• How to overcome limitations in research

You’ve already started on the road to overcoming limitations in research by acknowledging that they exist. However, you need to ensure readers don’t mistake weaknesses for errors within your research design.

To do this, you’ll need to justify and explain your rationale for the methods, research design, and analysis tools you chose and how you noticed they may have presented limitations.

Your readers need to know that even when limitations presented themselves, you followed best practices and the ethical standards of your field. You didn’t violate any rules and regulations during your research process.

You’ll also want to reinforce the validity of your conclusions and results with multiple sources, methods, and perspectives. This prevents readers from assuming your findings were derived from a single or biased source.

• Learning and improving starts with limitations in research

Dealing with limitations with transparency and integrity helps identify areas for future improvements and developments. It’s a learning process, providing valuable insights into how you can improve methodologies, expand sample sizes, or explore alternate approaches to further support the validity of your findings.

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Home » Delimitations in Research – Types, Examples and Writing Guide

Delimitations in Research – Types, Examples and Writing Guide

Table of Contents

Delimitations

Definition:

Delimitations refer to the specific boundaries or limitations that are set in a research study in order to narrow its scope and focus. Delimitations may be related to a variety of factors, including the population being studied, the geographical location, the time period, the research design , and the methods or tools being used to collect data .

The Importance of Delimitations in Research Studies

Here are some reasons why delimitations are important in research studies:

• Provide focus : Delimitations help researchers focus on a specific area of interest and avoid getting sidetracked by tangential topics. By setting clear boundaries, researchers can concentrate their efforts on the most relevant and significant aspects of the research question.
• Increase validity : Delimitations ensure that the research is more valid by defining the boundaries of the study. When researchers establish clear criteria for inclusion and exclusion, they can better control for extraneous variables that might otherwise confound the results.
• Improve generalizability : Delimitations help researchers determine the extent to which their findings can be generalized to other populations or contexts. By specifying the sample size, geographic region, time frame, or other relevant factors, researchers can provide more accurate estimates of the generalizability of their results.
• Enhance feasibility : Delimitations help researchers identify the resources and time required to complete the study. By setting realistic parameters, researchers can ensure that the study is feasible and can be completed within the available time and resources.
• Clarify scope: Delimitations help readers understand the scope of the research project. By explicitly stating what is included and excluded, researchers can avoid confusion and ensure that readers understand the boundaries of the study.

Types of Delimitations in Research

Here are some types of delimitations in research and their significance:

Time Delimitations

This type of delimitation refers to the time frame in which the research will be conducted. Time delimitations are important because they help to narrow down the scope of the study and ensure that the research is feasible within the given time constraints.

Geographical Delimitations

Geographical delimitations refer to the geographic boundaries within which the research will be conducted. These delimitations are significant because they help to ensure that the research is relevant to the intended population or location.

Population Delimitations

Population delimitations refer to the specific group of people that the research will focus on. These delimitations are important because they help to ensure that the research is targeted to a specific group, which can improve the accuracy of the results.

Data Delimitations

Data delimitations refer to the specific types of data that will be used in the research. These delimitations are important because they help to ensure that the data is relevant to the research question and that the research is conducted using reliable and valid data sources.

Scope Delimitations

Scope delimitations refer to the specific aspects or dimensions of the research that will be examined. These delimitations are important because they help to ensure that the research is focused and that the findings are relevant to the research question.

How to Write Delimitations

In order to write delimitations in research, you can follow these steps:

• Identify the scope of your study : Determine the extent of your research by defining its boundaries. This will help you to identify the areas that are within the scope of your research and those that are outside of it.
• Determine the time frame : Decide on the time period that your research will cover. This could be a specific period, such as a year, or it could be a general time frame, such as the last decade.
• I dentify the population : Determine the group of people or objects that your study will focus on. This could be a specific age group, gender, profession, or geographic location.
• Establish the sample size : Determine the number of participants that your study will involve. This will help you to establish the number of people you need to recruit for your study.
• Determine the variables: Identify the variables that will be measured in your study. This could include demographic information, attitudes, behaviors, or other factors.
• Explain the limitations : Clearly state the limitations of your study. This could include limitations related to time, resources, sample size, or other factors that may impact the validity of your research.
• Justify the limitations : Explain why these limitations are necessary for your research. This will help readers understand why certain factors were excluded from the study.

When to Write Delimitations in Research

Here are some situations when you may need to write delimitations in research:

• When defining the scope of the study: Delimitations help to define the boundaries of your research by specifying what is and what is not included in your study. For instance, you may delimit your study by focusing on a specific population, geographic region, time period, or research methodology.
• When addressing limitations: Delimitations can also be used to address the limitations of your research. For example, if your data is limited to a certain timeframe or geographic area, you can include this information in your delimitations to help readers understand the limitations of your findings.
• When justifying the relevance of the study : Delimitations can also help you to justify the relevance of your research. For instance, if you are conducting a study on a specific population or region, you can explain why this group or area is important and how your research will contribute to the understanding of this topic.
• When clarifying the research question or hypothesis : Delimitations can also be used to clarify your research question or hypothesis. By specifying the boundaries of your study, you can ensure that your research question or hypothesis is focused and specific.
• When establishing the context of the study : Finally, delimitations can help you to establish the context of your research. By providing information about the scope and limitations of your study, you can help readers to understand the context in which your research was conducted and the implications of your findings.

Examples of Delimitations in Research

Examples of Delimitations in Research are as follows:

Research Title : “Impact of Artificial Intelligence on Cybersecurity Threat Detection”

Delimitations :

• The study will focus solely on the use of artificial intelligence in detecting and mitigating cybersecurity threats.
• The study will only consider the impact of AI on threat detection and not on other aspects of cybersecurity such as prevention, response, or recovery.
• The research will be limited to a specific type of cybersecurity threats, such as malware or phishing attacks, rather than all types of cyber threats.
• The study will only consider the use of AI in a specific industry, such as finance or healthcare, rather than examining its impact across all industries.
• The research will only consider AI-based threat detection tools that are currently available and widely used, rather than including experimental or theoretical AI models.

Research Title: “The Effects of Social Media on Academic Performance: A Case Study of College Students”

Delimitations:

• The study will focus only on college students enrolled in a particular university.
• The study will only consider social media platforms such as Facebook, Twitter, and Instagram.
• The study will only analyze the academic performance of students based on their GPA and course grades.
• The study will not consider the impact of other factors such as student demographics, socioeconomic status, or other factors that may affect academic performance.
• The study will only use self-reported data from students, rather than objective measures of their social media usage or academic performance.

Purpose of Delimitations

Some Purposes of Delimitations are as follows:

• Focusing the research : By defining the scope of the study, delimitations help researchers to narrow down their research questions and focus on specific aspects of the topic. This allows for a more targeted and meaningful study.
• Clarifying the research scope : Delimitations help to clarify the boundaries of the research, which helps readers to understand what is and is not included in the study.
• Avoiding scope creep : Delimitations help researchers to stay focused on their research objectives and avoid being sidetracked by tangential issues or data.
• Enhancing the validity of the study : By setting clear boundaries, delimitations help to ensure that the study is valid and reliable.
• Improving the feasibility of the study : Delimitations help researchers to ensure that their study is feasible and can be conducted within the time and resources available.

Applications of Delimitations

Here are some common applications of delimitations:

• Geographic delimitations : Researchers may limit their study to a specific geographic area, such as a particular city, state, or country. This helps to narrow the focus of the study and makes it more manageable.
• Time delimitations : Researchers may limit their study to a specific time period, such as a decade, a year, or a specific date range. This can be useful for studying trends over time or for comparing data from different time periods.
• Population delimitations : Researchers may limit their study to a specific population, such as a particular age group, gender, or ethnic group. This can help to ensure that the study is relevant to the population being studied.
• Data delimitations : Researchers may limit their study to specific types of data, such as survey responses, interviews, or archival records. This can help to ensure that the study is based on reliable and relevant data.
• Conceptual delimitations : Researchers may limit their study to specific concepts or variables, such as only studying the effects of a particular treatment on a specific outcome. This can help to ensure that the study is focused and clear.

Advantages of Delimitations

Some Advantages of Delimitations are as follows:

• Helps to focus the study: Delimitations help to narrow down the scope of the research and identify specific areas that need to be investigated. This helps to focus the study and ensures that the research is not too broad or too narrow.
• Defines the study population: Delimitations can help to define the population that will be studied. This can include age range, gender, geographical location, or any other factors that are relevant to the research. This helps to ensure that the study is more specific and targeted.
• Provides clarity: Delimitations help to provide clarity about the research study. By identifying the boundaries and limitations of the research, it helps to avoid confusion and ensures that the research is more understandable.
• Improves validity: Delimitations can help to improve the validity of the research by ensuring that the study is more focused and specific. This can help to ensure that the research is more accurate and reliable.
• Reduces bias: Delimitations can help to reduce bias by limiting the scope of the research. This can help to ensure that the research is more objective and unbiased.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Exploring Scope and Delimitation in Academic Research

Academic research is a meticulous process that requires precise planning and clear boundaries. Two pivotal components in this process are the scope and delimitations of the study. The definitions and establishment of these parameters are instrumental in ensuring that the research is effective, manageable, and yields relevant results.

The "scope" of a research project refers to the areas that the study will cover. It is the breadth and depth of the investigation. It defines the subject matter, the geographical location, the time frame, and the issues that the study will explore. Essentially, the scope delineates what the researcher aims to cover in the study.

On the other hand, "delimitations" are the boundaries or limitations set by the researcher. They define what the study will not include. Delimitations could involve the choice of research methodology , the selection of respondents, the duration of the study, and more. They help in confining the study to a manageable size while excluding peripheral elements.

Understanding and correctly implementing scope and delimitations are vital to ensuring your research is well-defined and focused, facilitating higher accuracy and relevancy in your findings.

Importance of scope in research

"Scope" in research refers to the comprehensive extent of study—it outlines the parameters of what will be explored and addressed. It defines the topic of the research , the geographical region under study, the timeframe considered, and the issues that the study will address. The scope of a research project is vital because it determines the depth and breadth of your investigation.

Defining the scope of research is a fundamental step in the research process for several reasons. First, it provides a roadmap for the study, giving the researcher clear guidelines about what to include and exclude. Without a well-defined scope, research can become unmanageably vast or lose its focus.

Second, the scope ensures the research's relevance and applicability. It helps the researcher maintain a tight focus on the study's central question , ensuring that all aspects of the research contribute to answering this question. This focus aids in avoiding irrelevant diversions that could dilute the final conclusions.

Finally, a well-defined scope can help ensure the efficient use of resources. Research involves considerable time, effort, and often financial resources. By providing clear boundaries, the scope ensures these resources are utilized effectively without wasted effort on peripheral issues.

Suppose a research study is looking at the impacts of social media usage on mental health. If the scope is too broad—like examining all social media platforms' effects on all demographic groups worldwide—then the research can quickly become unwieldy and hard to manage. It would involve vast amounts of data, requiring considerable time, resources, and computational power to analyze effectively.

However, if the scope is narrowed down—such as investigating the impact of Instagram usage on the mental health of teenagers in a specific city over the past five years—the research becomes far more manageable. This specific focus allows for a more in-depth analysis and likely will provide more meaningful, actionable results. This example illustrates the importance of appropriately defining the scope of research for its successful execution.

Determining the scope of your research

Setting the scope of your research project is a critical and delicate task. Below are steps, tips, and common mistakes to avoid when determining the scope of your research:

Steps to define the scope

• Identify Your Topic: The first step involves identifying and understanding your research topic. This knowledge will serve as a basis for determining the breadth and depth of your study.
• Define Your Research Questions: The research questions are the heart of your study. They will help you determine the specific areas your research should cover.
• Establish Boundaries: Clearly establish the geographical, temporal, and topical boundaries of your research. These boundaries will guide the range of your study.
• Choose Your Methodology: Decide on the research methods you will use as these will directly impact the scope of your study.

Tips for a manageable scope

• Stay Focused: Stay concentrated on your research questions. Do not stray into areas that aren't directly relevant.
• Be Realistic: Consider the resources (time, money, manpower) available. Ensure your scope is feasible given these resources.
• Seek Guidance: Consult with your academic advisor or peers for feedback on your proposed scope.

Common mistakes to avoid

• Overly Broad Scope: Avoid setting an overly broad scope which could result in an unmanageable and unfocused study.
• Too Narrow Scope: Conversely, a scope that is too narrow may miss important aspects of the research topic.
• Ignoring Resources: Not taking into account available resources when setting the scope can lead to a project that is impossible to complete.

Defining the scope of your research is a delicate balance, requiring careful consideration of your research questions, resources, and the depth and breadth of investigation needed to answer these questions effectively.

Importance of delimitations in research

In the context of academic research, "delimitations" refers to the choices made by the researcher which define the boundaries of the study. These are the variables that lead the researcher to narrow the scope of the study from its potential vastness to a manageable size.

Delimitations might include the geographic area where the study is confined, the participants involved in the study, the methodology used, the time period considered, or the specific incidents or aspects the study will focus on. Essentially, delimitations are the self-imposed limitations on the scope of the study.

Defining the delimitations of a research project is crucial for several reasons. Firstly, they establish the context or setting in which the study occurs. This, in turn, allows for the work to be reproduced in a similar context for verification or refutation in future studies.

Secondly, delimitations provide a way to narrow the scope of the research to a manageable size, thus avoiding the pitfall of an overly ambitious project. They help researchers to stay focused on the main research questions and prevent diversion into irrelevant aspects.

Finally, clearly defined delimitations enhance the credibility of the research. They offer transparency about the research design and methodology, which adds to the validity of the results.

For instance, in a research study examining the impact of technology on student achievement in a certain district, examples of delimitations might include focusing only on public schools, considering only high school students, and confining the study to a particular school year. These choices help to focus the research and ensure its manageability. Therefore, delimitations play a pivotal role in structuring and guiding an effective and efficient research study.

Setting delimitations for your research

Establishing appropriate delimitations for your research project is an important part of research design. Here are some steps, guidelines, and common mistakes to consider when setting your research delimitations:

Steps to establish delimitations

• Identify the boundaries: Begin by deciding the geographical region, time period, and subject matter your research will cover.
• Determine Your Research Population: Identify the specific population your study will focus on. This could be based on age, profession, geographical location, etc.
• Choose Your Research Methods: Decide the specific methods you will use to collect and analyze data, as these decisions will also set limitations on your study.

Guidelines for choosing delimitations

• Align with Your Research Objectives: The delimitations should be in line with your research questions and objectives. They should help focus your study without detracting from its goals.
• Be Practical: Consider the resources available, including time, funds, and access to data. Your delimitations should be feasible given these constraints.
• Seek Input: Consult with your research advisor or peers. Their feedback can help ensure your delimitations are appropriate and well thought out.

Common errors to avoid:

• Unrealistic Delimitations: Be wary of setting delimitations that are too stringent or ambitious to be feasible given your resources and timeframe.
• Undefined Delimitations: Avoid leaving your delimitations vague or undefined. This can lead to scope creep, where your project expands beyond its initial plan, making it unmanageable.
• Ignoring Delimitations: Once set, stick to your delimitations. Deviating from them can lead to a loss of focus and can compromise the integrity of your results.

Setting delimitations is a crucial step in research planning. Properly defined delimitations can make your research project more manageable, maintain your focus, and ensure the effective use of your resources.

The interplay between scope and delimitations

The relationship between scope and delimitations in academic research is a dynamic and interdependent one. Each aspect serves to shape and refine the other, ultimately leading to a focused, feasible, and effective research design.

The scope of a research project describes the breadth and depth of the investigation—what it aims to cover and how far it intends to delve into the subject matter. The delimitations, on the other hand, identify the boundaries and constraints of the study—what it will not cover.

As such, the scope and delimitations of a research study are intimately connected. When the scope of a study is broad, the delimitations must be carefully considered to ensure the project remains manageable and focused. Conversely, when the scope is narrow, the delimitations might be less constraining, but they still play a critical role in defining the specificity of the research.

Balancing the scope and delimitations is crucial for an efficient research design. Too broad a scope without carefully defined delimitations can lead to a study that is unwieldy and lacks depth. On the other hand, a very narrow scope with overly rigid delimitations might result in a study that overlooks important aspects of the research topic.

Thus, researchers must strive to maintain a balance—establishing a scope that is wide enough to fully explore the research topic, but also setting appropriate delimitations to ensure the study remains feasible and focused. In doing so, the research will be well-structured and yield meaningful, relevant findings.

Role of scope and delimitations in research validity

Scope and delimitations are fundamental aspects of research design that directly influence the validity, reliability, and replicability of a study.

Research validity refers to the degree to which a study accurately reflects or measures the concept that the researcher intends to investigate. A well-defined scope is critical to research validity because it clearly delineates what the study will cover. This clear definition ensures that the research focuses on relevant aspects of the topic and that the findings accurately reflect the concept under investigation.

Similarly, carefully thought-out delimitations contribute to research validity by identifying what the study will not cover. This clarity helps to prevent the study from straying into irrelevant areas, ensuring that the research stays focused and relevant.

In addition to contributing to research validity, scope and delimitations also influence the reliability and replicability of a study. Reliability refers to the consistency of a study's results, while replicability refers to the ability of other researchers to repeat the study and obtain similar results.

A clearly defined scope makes a study more reliable by providing a detailed outline of the areas covered by the research. This clarity makes it more likely that the study will produce consistent results. Moreover, clearly defined delimitations enhance the replicability of a study by providing explicit boundaries for the research, which makes it easier for other researchers to repeat the study in a similar context.

In summary, a well-defined scope and carefully thought-out delimitations contribute significantly to the validity, reliability, and replicability of academic research. They ensure that the research is focused, that the findings are relevant and accurate, and that the study can be reliably repeated by other researchers.

Examples of scope and delimitation in well-known research

• The Milgram Experiment: Stanley Milgram's famous psychology experiment sought to understand obedience to authority figures. The scope of this study was clearly defined—it focused on how far individuals would go in obeying an instruction if it involved harming another person. However, delimitations were set to ensure manageability. Participants were delimited to male individuals, and the experiment was confined to a controlled laboratory setting. These delimitations allowed Milgram to manage the research effectively while maintaining the depth of his study on human behavior.
• The Framingham Heart Study: This ongoing cardiovascular study began in 1948 and is aimed at identifying common factors that contribute to cardiovascular disease. The scope of the research is broad, covering many aspects of lifestyle, medical history, and physical characteristics. However, the study set clear delimitations: it initially only involved adult residents of Framingham, Massachusetts. This geographical delimitation made this broad-scope study manageable and eventually yielded influential results that shaped our understanding of heart disease.
• The Marshmallow Test: This well-known study by Walter Mischel explored delayed gratification in children. The scope was clearly defined: the study aimed to understand the ability of children to delay gratification and how it related to future success. The delimitations of the study included the age of the participants (preschool children), the setting (a controlled experiment with a treat), and the measure of future success (academic achievement, ability to cope with stress, etc.). These delimitations helped keep the study focused and manageable.

In all these examples, the researchers set a clear scope to outline the focus of their studies and used delimitations to restrict the boundaries. This balance between scope and delimitation was key in conducting successful and influential research.

In academic research, defining the scope and delimitations is a pivotal step in designing a robust and effective study. The scope outlines the breadth and depth of the investigation, offering a clear direction for the research. Meanwhile, delimitations set the boundaries of the study, ensuring that the research remains focused and manageable. Together, they play a crucial role in enhancing the validity, reliability, and replicability of a study.

Understanding the interplay between scope and delimitations is key to conducting efficient research. A well-defined scope paired with thoughtfully set delimitations contribute to a study's feasibility and its potential to yield meaningful and applicable results. Mistakes in setting the scope and delimitations can lead to unwieldy, unfocused research or a study that overlooks important aspects of a research question.

Reviewing famous studies, like the Milgram Experiment, the Framingham Heart Study, and the Marshmallow Test, we observe how a balanced approach to setting scope and delimitations can result in influential and valuable findings. Therefore, researchers should give careful thought to defining the scope and delimitations of their studies, keeping in mind their research questions, available resources, and the need for balance between breadth and focus. By doing so, they pave the way for successful and impactful research outcomes.

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Writing Limitations of Research Study — 4 Reasons Why It Is Important!

It is not unusual for researchers to come across the term limitations of research during their academic paper writing. More often this is interpreted as something terrible. However, when it comes to research study, limitations can help structure the research study better. Therefore, do not underestimate significance of limitations of research study.

Allow us to take you through the context of how to evaluate the limits of your research and conclude an impactful relevance to your results.

Table of Contents

What Are the Limitations of a Research Study?

Every research has its limit and these limitations arise due to restrictions in methodology or research design.  This could impact your entire research or the research paper you wish to publish. Unfortunately, most researchers choose not to discuss their limitations of research fearing it will affect the value of their article in the eyes of readers.

However, it is very important to discuss your study limitations and show it to your target audience (other researchers, journal editors, peer reviewers etc.). It is very important that you provide an explanation of how your research limitations may affect the conclusions and opinions drawn from your research. Moreover, when as an author you state the limitations of research, it shows that you have investigated all the weaknesses of your study and have a deep understanding of the subject. Being honest could impress your readers and mark your study as a sincere effort in research.

Why and Where Should You Include the Research Limitations?

The main goal of your research is to address your research objectives. Conduct experiments, get results and explain those results, and finally justify your research question . It is best to mention the limitations of research in the discussion paragraph of your research article.

At the very beginning of this paragraph, immediately after highlighting the strengths of the research methodology, you should write down your limitations. You can discuss specific points from your research limitations as suggestions for further research in the conclusion of your thesis.

1. Common Limitations of the Researchers

Limitations that are related to the researcher must be mentioned. This will help you gain transparency with your readers. Furthermore, you could provide suggestions on decreasing these limitations in you and your future studies.

2. Limited Access to Information

Your work may involve some institutions and individuals in research, and sometimes you may have problems accessing these institutions. Therefore, you need to redesign and rewrite your work. You must explain your readers the reason for limited access.

3. Limited Time

All researchers are bound by their deadlines when it comes to completing their studies. Sometimes, time constraints can affect your research negatively. However, the best practice is to acknowledge it and mention a requirement for future study to solve the research problem in a better way.

4. Conflict over Biased Views and Personal Issues

Biased views can affect the research. In fact, researchers end up choosing only those results and data that support their main argument, keeping aside the other loose ends of the research.

Types of Limitations of Research

Before beginning your research study, know that there are certain limitations to what you are testing or possible research results. There are different types that researchers may encounter, and they all have unique characteristics, such as:

1. Research Design Limitations

Certain restrictions on your research or available procedures may affect your final results or research outputs. You may have formulated research goals and objectives too broadly. However, this can help you understand how you can narrow down the formulation of research goals and objectives, thereby increasing the focus of your study.

2. Impact Limitations

Even if your research has excellent statistics and a strong design, it can suffer from the influence of the following factors:

• Presence of increasing findings as researched
• Being population specific
• A strong regional focus.

3. Data or statistical limitations

In some cases, it is impossible to collect sufficient data for research or very difficult to get access to the data. This could lead to incomplete conclusion to your study. Moreover, this insufficiency in data could be the outcome of your study design. The unclear, shabby research outline could produce more problems in interpreting your findings.

How to Correctly Structure Your Research Limitations?

There are strict guidelines for narrowing down research questions, wherein you could justify and explain potential weaknesses of your academic paper. You could go through these basic steps to get a well-structured clarity of research limitations:

• Declare that you wish to identify your limitations of research and explain their importance,
• Provide the necessary depth, explain their nature, and justify your study choices.
• Write how you are suggesting that it is possible to overcome them in the future.

In this section, your readers will see that you are aware of the potential weaknesses in your business, understand them and offer effective solutions, and it will positively strengthen your article as you clarify all limitations of research to your target audience.

Know that you cannot be perfect and there is no individual without flaws. You could use the limitations of research as a great opportunity to take on a new challenge and improve the future of research. In a typical academic paper, research limitations may relate to:

1. Formulating your goals and objectives

If you formulate goals and objectives too broadly, your work will have some shortcomings. In this case, specify effective methods or ways to narrow down the formula of goals and aim to increase your level of study focus.

2. Application of your data collection methods in research

If you do not have experience in primary data collection, there is a risk that there will be flaws in the implementation of your methods. It is necessary to accept this, and learn and educate yourself to understand data collection methods.

3. Sample sizes

This depends on the nature of problem you choose. Sample size is of a greater importance in quantitative studies as opposed to qualitative ones. If your sample size is too small, statistical tests cannot identify significant relationships or connections within a given data set.

You could point out that other researchers should base the same study on a larger sample size to get more accurate results.

4. The absence of previous studies in the field you have chosen

Writing a literature review is an important step in any scientific study because it helps researchers determine the scope of current work in the chosen field. It is a major foundation for any researcher who must use them to achieve a set of specific goals or objectives.

However, if you are focused on the most current and evolving research problem or a very narrow research problem, there may be very little prior research on your topic. For example, if you chose to explore the role of Bitcoin as the currency of the future, you may not find tons of scientific papers addressing the research problem as Bitcoins are only a new phenomenon.

It is important that you learn to identify research limitations examples at each step. Whatever field you choose, feel free to add the shortcoming of your work. This is mainly because you do not have many years of experience writing scientific papers or completing complex work. Therefore, the depth and scope of your discussions may be compromised at different levels compared to academics with a lot of expertise. Include specific points from limitations of research. Use them as suggestions for the future.

Have you ever faced a challenge of writing the limitations of research study in your paper? How did you overcome it? What ways did you follow? Were they beneficial? Let us know in the comments below!

Frequently Asked Questions

Setting limitations in our study helps to clarify the outcomes drawn from our research and enhance understanding of the subject. Moreover, it shows that the author has investigated all the weaknesses in the study.

Scope is the range and limitations of a research project which are set to define the boundaries of a project. Limitations are the impacts on the overall study due to the constraints on the research design.

Limitation in research is an impact of a constraint on the research design in the overall study. They are the flaws or weaknesses in the study, which may influence the outcome of the research.

1. Limitations in research can be written as follows: Formulate your goals and objectives 2. Analyze the chosen data collection method and the sample sizes 3. Identify your limitations of research and explain their importance 4. Provide the necessary depth, explain their nature, and justify your study choices 5. Write how you are suggesting that it is possible to overcome them in the future

Excellent article ,,,it has helped me big

This is very helpful information. It has given me an insight on how to go about my study limitations.

Good comments and helpful

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Limitations Section

This guide will discuss the core concepts of study limitations and provide the foundations for how to formulate this section in an academic research paper.

Scientific research is an imperfect process. The core aspect of research, to investigate research questions, on topics both known and unknown, inherently includes an element of risk. These include human error, barriers to data gathering, limited resources, and bias. Researchers are encouraged to discuss the limitations of their work to enhance the process of research, as well as to allow readers to gain an understanding of the study’s framework and value.

The limitations of a study are defined as any characteristics, traits, actions, or influences that could impact the research process , and therefore its findings . Types of limitations can differ significantly, ranging from internal aspects, such as flaws in design and methodology, to external influences that a researcher was unable to control. A study may have several limitations that impact how its findings withstand validity tests, the generalizability of conclusions, or the appropriateness of the study design in a specific context.

Importance of Discussing Limitations

Many new researchers fear openly and clearly stating the limitations of their studies as they worry it will undermine the validity and relevance of their work for readers and other professionals in the field. That is not the case , as a statement of study limitations allows the reader to better understand the conditions of the study and challenges that the researcher has encountered . Not including this section, or leaving out vital aspects, which can address anything from sampling to the specific research methodology, can be detrimental to the general research field as it establishes an incomplete and potentially fallacious depiction of the research. Within academia, it is expected that all studies have limitations to some extent. Including this section demonstrates a comprehensive and holistic understanding of the research process and topic by the author.

A discussion of limitations should be a subjective learning process that assesses the magnitude, and critically evaluates the extenuating impact of the said limitations. This leads to the importance of stating limitations as it creates opportunities for both the original author and other researchers to improve the quality and validity of any future studies. Including limitations is based on the core principle of transparency in scientific research, with the purpose to maintain mutual integrity and promote further progress in similar studies.

Descriptions of Various Limitations

• Sample size or profile – sampling is one of the most common limitations mentioned by researchers. This is often due to the difficulty of finding a perfect sample that both fits the size parameters and necessary characteristics of the study to ensure generalizability of results. Various sampling techniques are also open to error and bias, which may potentially influence outcomes. Sometimes researchers are faced with limitations in selecting samples and resort to selective picking of participants or, the opposite, including irrelevant people in the general pool to reach the necessary total.
• Availability of information or previous research – generally, studies are based on previous knowledge or theoretical concepts on a specific topic. This provides a strong foundation for developing both the design and research problem for the investigation. However, there are instances where research is done on relatively specific topics, or is very progressive. Therefore, a lack of knowledge or other previous studies may limit the scope of the analysis, lead to inaccuracies in the author’s arguments, and present an increased margin for error in many aspects of the research and methodology.
• Methodology errors – the complexity of modern research leads to potential limitations in methodology. Most often, it is regarding data collection and analysis, as these aspects can strongly influence outcomes. Data collection techniques differ and, although fitting for the study design, present strong limitations in terms of privacy, distractions, or inappropriate levels of detail.
• Bias – a potential limitation that can affect all researchers. This is a limitation that researchers attempt to avoid by ensuring there are no conflicts of interest, lack of any emotional or prejudiced attitudes towards the topic, and establishing a level of oversight by referring to an ethics committee and peer-review procedures. As humans, it is inherent that bias will be present to some extent. However, it is the responsibility of the researcher to remain objective and attempt to control any potential bias or inaccuracies throughout every stage of the research process.

Structuring and Writing Limitations in Research Paper

The limitation section should be written in such a way that it demonstrates that the author understands the core concepts of bias, confounding, and analytical self-criticism . It is not necessary to highlight every single limitation, but rather the ones that have a direct impact on the study results or the research problem. The thought process of the researcher should be presented, explaining the pros and cons of any decisions made and the circumstances which have led to the limitation. Structuring the limitations should be done in a fourfold approach:

• Identify and describe the limitation. This should be done through the use of professional terminology and accompanying definitions when necessary. The explanation of the limitation should be brief and precise to ensure that readers have a clear grasp of the issue, as well as being able to follow the author’s pattern of thought.
• Outline the potential influence or impact that the limitation may have on the study. This consists of elements such as the likelihood of occurrence, the magnitude of impact, and the general direction that a specific limitation has driven the study findings. It is generally accepted that some limitations will have a more profound influence than others. Therefore, it is vital to highlight the impact of the limitation so that readers can decide which issues to consider when examining the topic as limitations with a null value bias are less dangerous.
• Discuss alternative approaches to the specific limitations , or the research question in general. A justification should be provided by the author to support the particular approach and methodology selected in the specific study and why it was warranted within the context of any limitations. If possible, persuasive evidence should be provided and alternative decisions discussed to some extent. This demonstrates transparency of thought and reassures readers that despite potential limitations, the selected approach was the best alternative for the current research on the topic within the field of study.
• Describe techniques to minimize any risks resulting from the limitations. This may include reference to previous research and suggestions on the improvement of design and analysis.

Limitations are an inherent part of any research study. Therefore, it is generally accepted in academia to acknowledge various limitations as part of the research process. Issues may vary, ranging from sampling and literature review, to methodology and bias. However, there is a structure for identifying these elements, discussing them, and offering insight or alternatives on how limitations can be mitigated. This not only enhances the process of the research but also helps readers gain a comprehensive understanding of a study’s conditions.

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Research Limitations & Delimitations

What they are and how they’re different (with examples)

By: Derek Jansen (MBA) | Expert Reviewed By: David Phair (PhD) | September 2022

If you’re new to the world of research, you’ve probably heard the terms “ research limitations ” and “ research delimitations ” being thrown around, often quite loosely. In this post, we’ll unpack what both of these mean, how they’re similar and how they’re different – so that you can write up these sections the right way.

Overview: Limitations vs Delimitations

• Are they the same?
• What are research limitations
• What are research delimitations
• Limitations vs delimitations

First things first…

Let’s start with the most important takeaway point of this post – research limitations and research delimitations are not the same – but they are related to each other (we’ll unpack that a little later). So, if you hear someone using these two words interchangeably, be sure to share this post with them!

Research Limitations

Research limitations are, at the simplest level, the weaknesses of the study, based on factors that are often outside of your control as the researcher. These factors could include things like time , access to funding, equipment , data or participants . For example, if you weren’t able to access a random sample of participants for your study and had to adopt a convenience sampling strategy instead, that would impact the generalizability of your findings and therefore reflect a limitation of your study.

Research limitations can also emerge from the research design itself . For example, if you were undertaking a correlational study, you wouldn’t be able to infer causality (since correlation doesn’t mean certain causation). Similarly, if you utilised online surveys to collect data from your participants, you naturally wouldn’t be able to get the same degree of rich data that you would from in-person interviews .

Simply put, research limitations reflect the shortcomings of a study , based on practical (or theoretical) constraints that the researcher faced. These shortcomings limit what you can conclude from a study, but at the same time, present a foundation for future research . Importantly, all research has limitations , so there’s no need to hide anything here – as long as you discuss how the limitations might affect your findings, it’s all good.

Research Delimitations

Alright, now that we’ve unpacked the limitations, let’s move on to the delimitations .

Research delimitations are similar to limitations in that they also “ limit ” the study, but their focus is entirely different. Specifically, the delimitations of a study refer to the scope of the research aims and research questions . In other words, delimitations reflect the choices you, as the researcher, intentionally make in terms of what you will and won’t try to achieve with your study. In other words, what your research aims and research questions will and won’t include.

As we’ve spoken about many times before, it’s important to have a tight, narrow focus for your research, so that you can dive deeply into your topic, apply your energy to one specific area and develop meaningful insights. If you have an overly broad scope or unfocused topic, your research will often pull in multiple, even opposing directions, and you’ll just land up with a muddy mess of findings .

So, the delimitations section is where you’ll clearly state what your research aims and research questions will focus on – and just as importantly, what they will exclude . For example, you might investigate a widespread phenomenon, but choose to focus your study on a specific age group, ethnicity or gender. Similarly, your study may focus exclusively on one country, city or even organization. As long as the scope is well justified (in other words, it represents a novel, valuable research topic), this is perfectly acceptable – in fact, it’s essential. Remember, focus is your friend.

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Conclusion: Limitations vs Delimitations

Ok, so let’s recap.

Research limitations and research delimitations are related in that they both refer to “limits” within a study. But, they are distinctly different. Limitations reflect the shortcomings of your study, based on practical or theoretical constraints that you faced.

Contrasted to that, delimitations reflect the choices that you made in terms of the focus and scope of your research aims and research questions. If you want to learn more about research aims and questions, you can check out this video post , where we unpack those concepts in detail.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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18 Comments

Good clarification of ideas on how a researcher ought to do during Process of choice

Thank you so much for this very simple but explicit explanation on limitation and delimitation. It has so helped me to develop my masters proposal. hope to recieve more from your site as time progresses

Thank you for this explanation – very clear.

Thanks for the explanation, really got it well.

This website is really helpful for my masters proposal

Thank you very much for helping to explain these two terms

I spent almost the whole day trying to figure out the differences

when I came across your notes everything became very clear

thanks for the clearly outlined explanation on the two terms, limitation and delimitation.

Very helpful Many thanks 🙏

Excellent it resolved my conflict .

I would like you to assist me please. If in my Research, I interviewed some participants and I submitted Questionnaires to other participants to answered to the questions, in the same organization, Is this a Qualitative methodology , a Quantitative Methodology or is it a Mixture Methodology I have used in my research? Please help me

How do I cite this article in APA format

Really so great ,finally have understood it’s difference now

Getting more clear regarding Limitations and Delimitation and concepts

I really appreciate your apt and precise explanation of the two concepts namely ; Limitations and Delimitations.

This is a good sources of research information for learners.

thank you for this, very helpful to researchers

Very good explained

Great and clear explanation, after a long confusion period on the two words, i can now explain to someone with ease.

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A different level of detail is required for different sections of a research paper or different chapters of a thesis. For example, the Materials and Methods section of a research paper or thesis would describe what was done and how it was done in substantial detail. However, in addition to providing detailed information where relevant, it is important to state the broader parameters and boundaries of the research . This forms the scope and delimitations of a study and helps to contextualise the research for the reader so they can better anticipate the extent of the details to come.

Scope explained

The main purpose of stating the scope of the study is to set the context early on so that readers can interpret the results and discussions with the given context in mind.

The scope of the study is given in broad terms and identifies any of the following elements:

Delimitations explained

You could think of delimitations as EITHER of the following:

• Stating what was not done  
• A more detailed and variant exposition of the scope, which is expressed in terms of exclusion rather than inclusion – i.e. a description of what is not included or considered or studied within the given piece of research

Some examples of delimitations are:

  Importance of stating scope and delimitations

• Clarifying the scope and delimitations of a study is helpful for interpreting the results because the results are influenced by the scope and materials (delimitations). For instance, agricultural field experiments conducted under irrigated conditions can give very different results from the experiments conducted without irrigation.
• Scope and delimitations also help to make the study more replicabl e by specifying what was excluded. For example, in the example mentioned earlier for delimitations, the results can be very different if samples with greater impurities are not discarded.
• In the field of medicine, the gender bias is becoming increasingly evident, which is why it is becoming important to state – even when a sample of subjects was selected at random – the proportion of men and women in the sample.

Writing the scope and delimitations in the paper

Considering that it is given in broader terms, the scope can form part of the Introduction , whereas delimitations, being more detailed, rightfully belong to the Methods section.

Delimitations vs. limitations

Finally, note that delimitations of a study are different from its limitations: the latter can be thought of as shortcomings , typically mentioned to address in anticipation any objections from the reviewers of a manuscript . (Learn more about limitations here: How to write the Limitations of your research )

The above explanation and examples should convince you of the need to include scope and delimitations while writing a research paper, a thesis or even a research proposal . Do not hesitate to include them because if you do not point them out, somebody else will !

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How To Write Scope and Delimitation of a Research Paper (With Examples)

An effective research paper or thesis has a well-written Scope and Delimitation.  This portion specifies your study’s coverage and boundaries.

Not yet sure about how to write your research’s Scope and Delimitation? Fret not, as we’ll guide you through the entire writing process through this article.

Related: How To Write Significance of the Study (With Examples)

Table of Contents

What is the scope and delimitation of a research paper.

The “Scope and Delimitation” section states the concepts and variables your study covered. It tells readers which things you have included and excluded in your analysis.

This portion tells two things: 1

• The study’s “Scope” – concepts and variables you have explored in your research and;
• The study’s “Delimitation” – the “boundaries” of your study’s scope. It sets apart the things included in your analysis from those excluded.

For example, your scope might be the effectiveness of plant leaves in lowering blood sugar levels. You can “delimit” your study only to the effect of gabi leaves on the blood glucose of Swiss mice.

Where Should I Put the Scope and Delimitation?

This portion is in Chapter 1, usually after the “Background of the Study.”

Why Should I Write the Scope and Delimitation of My Research Paper?

There’s a lot to discover in a research paper or thesis. However, your resources and time dedicated to it are scarce. Thus, given these constraints, you have to narrow down your study. You do this in the Scope and Delimitation.

Suppose you’re studying the correlation between the quantity of organic fertilizer and plant growth . Experimenting with several types of plants is impossible because of several limitations. So, you’ve decided to use one plant type only. 

Informing your readers about this decision is a must. So, you have to state it in your Scope and Delimitation. It also acts as a “disclaimer” that your results are inapplicable to the entire plant kingdom.

What Is the Difference Between Delimitation and Limitation?

People often use the terms “Delimitation” and “Limitation” interchangeably. However, these words differ 2 .

Delimitation refers to factors you set to limit your analysis. It delineates those that are included in your research and those that are excluded. Remember, delimitations are within your control. 

Meanwhile, limitations are factors beyond your control that may affect your research’s results.  You can think of limitations as the “weaknesses” of your study. 

Let’s go back to our previous example. Due to some constraints, you’ve only decided to examine one plant type: dandelions. This is an example of a delimitation since it limits your analysis to dandelions only and not other plant types. Note that the number of plant types used is within your control. 

Meanwhile, your study cannot state that a higher quantity of organic fertilizer is the sole reason for plant growth. That’s because your research’s focus is only on correlation. Since this is already beyond your control, then this is a limitation. 

How To Write Scope and Delimitation: Step-by-Step Guide

To write your research’s Scope and Delimitation section, follow these steps:

1. Review Your Study’s Objectives and Problem Statement

Your study’s coverage relies on its objectives. Thus, you can only write this section if you know what you’re researching. Furthermore, ensure that you understand the problems you ought to answer. 

Once you understand the abovementioned things, you may start writing your study’s Scope and Delimitation.

2. State the Key Information To Explain Your Study’s Coverage and Boundaries

a. The Main Objective of the Research

This refers to the concept that you’re focusing on in your research. Some examples are the following:

• level of awareness or satisfaction of a particular group of people
• correlation between two variables
• effectiveness of a new product
• comparison between two methods/approaches
• lived experiences of several individuals

It’s helpful to consult your study’s Objectives or Statement of the Problem section to determine your research’s primary goal.

b. Independent and Dependent Variables Included

Your study’s independent variable is the variable that you manipulate. Meanwhile, the dependent variable is the variable whose result depends upon the independent variable. Both of these variables must be clear and specific when indicated. 

Suppose you study the relationship between social media usage and students’ language skills. These are the possible variables for the study:

• Independent Variable: Number of hours per day spent on using Facebook
• Dependent Variable: Grade 10 students’ scores in Quarterly Examination in English. 

Note how specific the variables stated above are. For the independent variable, we narrow it down to Facebook only. Since there are many ways to assess “language skills,” we zero in on the students’ English exam scores as our dependent variable. 

c. Subject of the Study

This refers to your study’s respondents or participants. 

In our previous example, the research participants are Grade 10 students. However, there are a lot of Grade 10 students in the Philippines. Thus, we have to select from a specific school only—for instance, Grade 10 students from a national high school in Manila. 

d. Timeframe and Location of the Study

Specify the month(s), quarter(s), or year(s) as the duration of your study. Also, indicate where you will gather the data required for your research. 

e. Brief Description of the Study’s Research Design and Methodology

You may also include whether your research is quantitative or qualitative, the sampling method (cluster, stratified, purposive) applied, and how you conducted the experiment.

Using our previous example, the Grade 10 students can be selected using stratified sampling. Afterward, the researchers may obtain their English quarterly exam scores from their respective teachers. You can add these things to your study’s Scope and Delimitation. 

3. Indicate Which Variables or Factors Are Not Covered by Your Research

Although you’ve already set your study’s coverage and boundaries in Step 2, you may also explicitly mention things you’ve excluded from your research. 

Returning to our previous example, you can state that your assessment will not include the vocabulary and oral aspects of the English proficiency skill. 

Examples of Scope and Delimitation of a Research Paper

1. scope and delimitation examples for quantitative research.

a. Example 1

Research Title

    A Study on the Relationship of the Extent of Facebook Usage on the English Proficiency Level of Grade 10 Students of Matagumpay High School

Scope and Delimitation

(Main Objective)

This study assessed the correlation between the respondents’ duration of Facebook usage and their English proficiency level. 

(Variables used)

The researchers used the number of hours per day of using Facebook and the activities usually performed on the platform to assess the respondents’ extent of Facebook usage. Meanwhile, the respondents’ English proficiency level is limited to their quarterly English exam scores. 

(Subject of the study)

A sample of fifty (50) Grade 10 students of Matagumpay High School served as the study’s respondents. 

(Timeframe and location)

This study was conducted during the Second Semester of the School Year 2018 – 2019 on the premises of Matagumpay High School in Metro Manila. 

(Methodology)

The respondents are selected by performing stratified random sampling to ensure that there will be ten respondents from five Grade 10 classes of the school mentioned above. The researchers administered a 20-item questionnaire to assess the extent of Facebook usage of the selected respondents. Meanwhile, the data for the respondents’ quarterly exam scores were acquired from their English teachers. The collected data are handled with the utmost confidentiality. Spearman’s Rank Order Correlation was applied to quantitatively assess the correlation between the variables.

(Exclusions)

This study didn’t assess other aspects of the respondents’ English proficiency, such as English vocabulary and oral skills. 

Note: The words inside the parentheses in the example above are guides only. They are not included in the actual text.

b. Example 2

  Level of Satisfaction of Grade 11 Students on the Implementation of the Online Learning Setup of Matagumpay High School for SY 2020 – 2021

This study aims to identify students’ satisfaction levels with implementing online learning setups during the height of the COVID-19 pandemic.

Students’ satisfaction was assessed according to teachers’ pedagogy, school policies, and learning materials used in the online learning setup. The respondents included sixty (60) Grade 11 students of Matagumpay High School who were randomly picked. The researchers conducted the study from October 2020 to February 2021. 

Online platforms such as email and social media applications were used to reach the respondents. The researchers administered a 15-item online questionnaire to measure the respondents’ satisfaction levels. Each response was assessed using a Likert Scale to provide a descriptive interpretation of their answers. A weighted mean was applied to determine the respondents’ general satisfaction. 

This study did not cover other factors related to the online learning setup, such as the learning platform used, the schedule of synchronous learning, and channels for information dissemination.

2. Scope and Delimitation Examples for Qualitative Research

  Lived Experiences of Public Utility Vehicle (PUV) Drivers of Antipolo City Amidst the Continuous June 2022 Oil Price Hikes

This research focused on the presentation and discussion of the lived experiences of PUV drivers during the constant oil price hike in June 2022.

The respondents involved are five (5) jeepney drivers from Antipolo City who agreed to be interviewed. The researchers assessed their experiences in terms of the following: (1) daily net income; (2) duration and extent of working; (3) alternative employment opportunity considerations; and (4) mental and emotional status. The respondents were interviewed daily at their stations on June 6 – 10, 2022. 

In-depth one-on-one interviews were used for data collection.  Afterward, the respondents’ first-hand experiences were drafted and annotated with the researchers’ insights. 

The researchers excluded some factors in determining the respondents’ experiences, such as physical and health conditions and current family relationship status. 

 A Study on the Perception of the Residents of Mayamot, Antipolo City on the Political and Socioeconomic Conditions During the Post-EDSA Period (1986 – 1996)

This research aims to discuss the perception of Filipinos regarding the political and socioeconomic economic conditions during the post-EDSA period, specifically during the years 1986 – 1996. 

Ten (10) residents of Mayamot, Antipolo City, who belonged to Generation X (currently 40 – 62 years old), were purposively selected as the study’s respondents. The researchers asked them about their perception of the following aspects during the period mentioned above (1) performance of national and local government; (2) bureaucracy and government services; (3) personal economic and financial status; and (4) wage purchasing power. 

The researchers conducted face-to-face interviews in the respondents’ residences during the second semester of AY 2018 – 2019. The responses were written and corroborated with the literature on the post-EDSA period. 

The following factors were not included in the research analysis: political conflicts and turmoils, the status of the legislative and judicial departments, and other macroeconomic indicators. 

Tips and Warnings

1. use the “5ws and 1h” as your guide in understanding your study’s coverage.

• Why did you write your study?  
• What variables are included?
• Who are your study’s subject
• Where did you conduct the study?
• When did your study start and end?
• How did you conduct the study?

2. Use key phrases when writing your research’s scope

• This study aims to … 
• This study primarily focuses on …
• This study deals with … 
• This study will cover …
• This study will be confined…

3. Use key phrases when writing factors beyond your research’s delimitations

• The researcher(s) decided to exclude …
• This study did not cover….
• This study excluded … 
• These variables/factors were excluded from the study…

4. Don’t forget to ask for help

Your research adviser can assist you in selecting specific concepts and variables suitable to your study. Make sure to consult him/her regularly. 

5. Make it brief

No need to make this section wordy. You’re good to go if you meet the “5Ws and 1Hs”. 

Frequently Asked Questions

1. what are scope and delimitation in tagalog.

In a Filipino research ( pananaliksik ), Scope and Delimitation is called “ Saklaw at Delimitasyon”. 

Here’s an example of Scope and Delimitation in Filipino:

Pamagat ng Pananaliksik

Epekto Ng Paggamit Ng Mga Digital Learning Tools Sa Pag-Aaral Ng Mga Mag-Aaral Ng Mataas Na Paaralan Ng Matagumpay Sa General Mathematics

Sakop at Delimitasyon ng Pag-aaral

Nakatuon ang pananaliksik na ito sa epekto ng paggamit ng mga digital learning aids sa pag-aaral ng mga mag-aaral.

Ang mga digital learning tools na kinonsidera sa pag-aaral na ito ay Google Classroom, Edmodo, Kahoot, at mga piling bidyo mula YouTube. Samantala, ang epekto sa pag-aaral ng mga mag-aaral ng mga nabanggit na digital learning tools ay natukoy sa pamamagitan ng kanilang (1) mga pananaw hinggil sa benepisyo nito sa kanilang pag-aaral sa General Mathematics at (2) kanilang average grade sa asignaturang ito.

Dalawampu’t-limang (25) mag-aaral mula sa Senior High School ng Mataas na Paaralan ng Matagumpay ang pinili para sa pananaliksik na ito. Sila ay na-interbyu at binigyan ng questionnaire noong Enero 2022 sa nasabing paaralan. Sinuri ang resulta ng pananaliksik sa pamamagitan ng mga instrumentong estadistikal na weighted mean at Analysis of Variance (ANOVA). Hindi saklaw ng pananaliksik na ito ang ibang mga aspeto hinggil sa epekto ng online learning aids sa pag-aaral gaya ng lebel ng pag-unawa sa aralin at kakayahang iugnay ito sa araw-araw na buhay. 

2. The Scope and Delimitation should consist of how many paragraphs?

Three or more paragraphs will suffice for your study’s Scope and Delimitation. Here’s our suggestion on what you should write for each paragraph:

Paragraph 1: Introduction (state research objective) Paragraph 2: Coverage and boundaries of the research (you may divide this section into 2-3 paragraphs) Paragraph 3 : Factors excluded from the study

• University of St. La Salle. Unit 3: Lesson 3 Setting the Scope and Limitation of a Qualitative Research [Ebook] (p. 12). Retrieved from https://www.studocu.com/ph/document/university-of-st-la-salle/senior-high-school/final-sg-pr1-11-12-unit-3-lesson-3-setting-the-scope-and-limitation-of-a-qualitative-research/24341582
• Theofanidis, D., & Fountouki, A. (2018). Limitations and Delimitations in the Research Process. Perioperative Nursing (GORNA), 7(3), 155–162. doi: 10.5281/zenodo.2552022

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Last Updated May 6, 2023 09:59 AM

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

Browse all articles written by Jewel Kyle Fabula

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Principles, Scope, and Limitations of the Methodological Triangulation *

Principios, alcances y limitaciones de la triangulación metodológica, princípios, alcances e limitações da triangulação metodológica, maría mercedes arias valencia.

1 Nurse, Ph.D. Professor at Facultad de Enfermería, Universidad de Antioquia. Medellín (Colombia). Email: [email protected], Universidad de Antioquia, Facultad de Enfermería, Universidad de Antioquia, Medellín , Colombia, [email protected]

This article sought to collect basic and relevant information about methodological triangulation and make a first approach to the principles underlying its use, potentiality and scope, advances and limitations, and some alternative proposals to surpass them. In that sense, it is an attempt to operationalize concepts and present the procedures to conduct it rigorously. In the first place, conceptual aspects and types of triangulation are presented, and in the second place, the principles, uses and difficulties. But, beyond what must be done, an approach is made to how to do it. The assumption underlying through the article is the complementarity among methods. It is emphasized in the principle through which the nature of objects must guide the selection of the methods and of the most effective techniques to approach and account for phenomena that are socially pertinent of being studied.

El presente artículo pretende levantar información básica y relevante sobre la triangulación metodológica y hacer una primera aproximación a los principios que subyacen en su uso, su potencialidad y alcance, sus avances y limitaciones, y algunas propuestas alternativas para superarlas. En ese sentido, es un intento de operacionalizar los conceptos y presentar los procedimientos para llevarla a cabo en forma rigurosa. En primer lugar, se presentan los aspectos conceptuales y los tipos de triangulación, y en segundo lugar los principios, los usos y las dificultades. Pero, más allá del qué hacer, se hace una aproximación al cómo hacerlo. El supuesto que subyace a través del artículo es la complementariedad entre los métodos. Se enfatiza en el principio mediante el cual, la naturaleza de los objetos debe guiar la escogencia de los métodos y de las técnicas más eficaces para aproximarse y dar cuenta de los fenómenos que son pertinentes socialmente, de ser estudiados.

Este artigo tem como objetivo coletar informações básicas e relevantes sobre triangulação metodológica e fazer uma primeira aproximação aos princípios que fundamentam sua utilização, seu potencial e alcance, sua avanços e limitações, e algumas propostas alternativas para superá-los. Nesse sentido, é uma tentativa de operacionalizar os conceitos e apresentar os procedimentos para realizá-lo com rigor. Em primeiro lugar, são apresentados os aspectos conceituais e os tipos de triangulação e, em segundo lugar, os princípios, usos e dificuldades. Mas, além do que fazer, é feita uma abordagem de como fazer. A hipótese subjacente ao longo do artigo é a complementaridade entre os métodos. A ênfase é colocada no princípio pelo qual a natureza dos objetos deve orientar a escolha dos métodos e técnicas mais eficazes para abordar e dar conta dos fenômenos socialmente relevantes, se estudados.

Introduction

According to Boudon, 1 for authors, like Dilthey, Rickert, Jaspers, and Max Weber, research in social sciences follows the path of understanding and the natural sciences through explanation, although for some, especially for Weber, both procedures, although distinct, are not exclusive. The same author found false opposition between the methods of the sciences, given our condition of social beings and the specificities of the human, through the diversity of objects and limitations of the methods, to account for complex phenomena of the social reality. For this author, it is naive to evaluate the methods of the social sciences with the unified parameters of the natural sciences, given that it would not be imaginable, for example, that History could be similar to Physics.

Quantitative research is supported on a set of established logical principles and should not be imposed from the outside for the researcher. Qualitative research also obeys an implicit but less unifiable logic. 1 The nature of the object and effectiveness of the methods will guide the researcher’s reflection to approach and account for phenomena that are pertinent, socially, of being studied. It must be highlighted that the methods are not the truth, they only constitute tools, procedures, instruments and modes of putting together the theory to investigate a problem and that when used facilitate its understanding; in that sense, the methodological triangulation will be treated as research procedure.

The term triangulation comes from navigation, where, from various angles, an object is situated; in this case, a ship. Thus, triangulation constructs several appendages, namely theoretical or methodological perspectives, several views or several readings, diverse points of view to address the same research problem. As explained by Morse, the discussion among authors has dealt on the appropriations, advantages, and disadvantages of methodological triangulation. 2 The issue that has gained greater interest is the combination of qualitative and quantitative methods within the same project. Some authors have published examples of how this is carried out within a specific project, identifying the issues involved in said strategies; others have identified unsolved issues or highlight the guidelines they consider successful and the less developed in the use of methodological triangulation.

This article sought to collect basic and relevant information about methodological triangulation and make a first approach over the principles underlying its use, potentiality and scope, its progress and limitations, as well as solution alternatives.

From triangulation of indicators and variables to theoretical and methodological triangulation: conceptual aspects

What is methodological triangulation? Triangulation is a term originally used in navigation circles by taking multiple reference points to locate an unknown position. Campbell and Fiske are credited in the literature as the first to apply triangulation in research in 1959. 3 It is assumed conventionally that triangulation is the use of multiple methods to study the same object. This is the generic definition, but it is only one form of the strategy. It is convenient to conceive triangulation including varieties of data, researchers and theories, as well as methodologies. 4

Kimchi et al ., 5 assume the definition by Denzin in 1970 on triangulation in research: it is the combination of two or more theories, sources of data, research methods, in the study of a singular phenomenon. Close scrutiny reveals that the combination can be interpreted in several manners; for such, the authors start from the classification by Denzin and provide explanations about the most adequate way of performing it.

For Cowman, 3 triangulation is defined as the combination of multiple methods in studying the same object or event to better address the phenomenon researched. In turn, Morse 2 defines methodological triangulation as the use of at least two methods, usually qualitative and quantitative, to guide the same research problem. When a singular research method is inadequate, triangulation can be used for a more comprehensive approach to solve the research problem.

Multiple triangulation strategies

Denzin 4 describes four basic types of triangulation: 1) data triangulation with three subtypes of time, space and person; the person analysis, in turn, has three levels: aggregate, interactive and collective; 2) researcher triangulation that consists in using multiple observers, more than single observers of the same object; 3) theoretical triangulation that consists in using multiple perspectives, more than single perspectives in relation with the same set of objects, and 4) methodological triangulation that can imply triangulation within methods and triangulations among methods.

Data triangulation 4

Denzin 4 illustrates this type of triangulation. For the author, observers can triangulate with data sources and researchers make explicit the search for the different sources. For example, analysts can employ, in efficient manner, the same methods for a maximum theoretical advantage. Thus, for example, in studying the social meaning of death in a modern hospital it may be possible to use a standard method (like participant observation, which, in strict manner would be technical) and deliberately follow this method in as many different areas as possible.

Researchers can observe different groups within the hospital and take the family members of the dead people. Death rituals can also be examined with the same process. Other examples are deaths on the road, deaths at home, deaths at work and even deaths at play. Each represents a different area of significance with which the same generic event (death) occurs. Basically, this could be used in a comparison of dissimilar groups as a sampling strategy, but more properly reflects a triangulation strategy. Selecting different collocations systematically, researchers can discover that its concepts (like assignment of reality units) share common issues. Similarly, the constituent unit of those concepts can be discovered in its contextual situation.

Furthermore, all sociological observations report activities of people situated socially -although they are in groups or organizations or distributed in groups in a social area -. Focusing time and space as observation units recognizes their relationship with the observations of people. Observers can make a sampling of activities according to time of day, week, month or year. Likewise, they can do it with space and treat it as an analysis unit (for example, ecological analysis), or as a component of external validity. The most-common analysis unit, the social organization of people can be sampled over time and space. Those three units -time, space and person- are interrelated. Studying one demands studying the others.

Levels of person analysis. Three levels of person analysis can be treated: 4

• Aggregate analysis. It is the first level; selecting individuals for the study, not groups, or relationships, or organizations. This level of analysis is called aggregate because it does not establish social relationships among that observed. Random samples of house workers, school students, and laborers are examples of aggregate analysis of persons.
• Interactive analysis. It is the second level and is related directly with the symbolic interaction. Regarding the term interactive, a unit exists among people interacting in the laboratory or in the natural field. For example, small groups, families or aviators. Sociologists commonly associate it with participant observation; experiments in small groups and non-obstructive measurements represent this form of analysis. The unit is the interaction more than person or group; for example, face-to-face studies by Goffman, who investigated in insurers, nurses and hospital social structure, only how they interact in the generation of series of interactive episodes.
• Collective analysis. The third level, more commonly associated with the structural-functional analysis, is the collectivity. Here, the observational unit is an organization, group, community or, even, an entire society. People and their interactions are treated only according with how they reflect pressures and demands of the total collectivity.

The three levels of analysis may be illustrated by returning to the example of death in hos pital. Research guided in aggregate manner can sample simply the attitudes of the hospital staff during the process. An interactional study can examine how those attitudes are generated by the encounters of the personnel. Lastly, the researcher aimed towards the collectivity can examine how the hospital’s structural units (for example, its organizational charter, job positions) dictate certain attitudes and practices by its members.

In synthesis, any research can combine the three levels and types of data; in effect, those studies commonly recall as classical events these combinations: time, space and person are alternatively analyzed in the aggregate, interactive, and collective levels.

Researcher triangulation 4

Researcher triangulation means multiple observers are used, rather than a single one. More researchers, in effect, conduct multiple observations, although not all play equally prominent roles in the process. Delegation at work can be established by placing well-prepared individuals in crucial positions. When using multiple observers, the most skilled should be placed near to the data. Upon triangulating observers, potential bias coming from single person is removed and considerable reliability is ensured in the observations.

There are various field workers subjected to the same data. If a colleague reports the same class of observation as another, without prior consultation, trust is increased. If later, listening to the report of an observation, a colleague contributes the same, unquestionably duplicates it; that indicates that our observation techniques have some degree of reliability.

Multiple observers may not agree on what they are observing, given that each observer has unique interactional experiences with the phenomenon observed. 4 Researcher triangulation is considered present when two or more trained researchers with divergent antecedents explore the same phenomenon. It is considered to take place when; 1) each researcher has a prominent role in the study, 2) the experience of each researcher is different, and 3) the disciplinary bias of each researcher is evident in the study. This definition, as the previous classifications, was elaborated and extended by Denzin in 1989, who stated that researcher triangulation occurs when two or more skilled researchers examine the data. The concern that stands out from researcher triangulation is that different disciplinary biases are compared or neutralized through the study. Overall, this is not discernible in a research publication. Researcher triangulation is difficult to distinguish, unless the authors describe explicitly how they achieved it.

Theoretical triangulation 4

Denzin defined theoretical triangulation as an evaluation of the usefulness and being able to test rival theories or hypotheses. This definition includes tests through research, rival theories, rival hypotheses or alternative explanations of the same phenomenon. Denzin placed as example the studies by Campbell of women’s responses toward abuse, which provide an example of theoretical triangulation. Two competitive models were tested in the same sample of women. Both were used previously to explain the women’s responses. The goal was to pit them against each other in a singular study to determine which one provides the best explanatory model of the phenomenon of abuse. The data collection approached was used to measure specific concepts and variables from each model. The report published placed the objective a priori, to the test of two opposing rival theories; this component is necessary to operationalize the theoretical triangulation.

Theoretical triangulation is an element few researchers manage and end up reaching. Overall, a small group of hypotheses guides the study and the data obtained emerge not only in those dimensions, rather they may appear with value, in empirical approach materials with multiple perspectives and interpretations in mind. Data could refute the central hypothesis and various theoretical points of view can take place to determine its power and usefulness. Each strategy can allow the contribution of criticism and controversy from several theoretical perspectives. Confronting theories in the same body of data means the presence of efficient criticism, more in line with the scientific method. This last issue can be qualified by understanding, for example, that sociologists never have the same body of data; this means that a body of data of empirical materials is always socially constructed and subject to multiple interpretations.

Methodological triangulation

Triangulation of methods using two or more research methods can be made in the design or in the data collection. Two types exist, triangulation within methods and among methods. 4

Triangulation within methods is the combination of two or more data collections to approach the study of the same object; using two or more quantitative measurements of the same phenomenon in a study is an example. Including two or more qualitative approaches, like the observation and open interview to assess the same phenomenon, is also considered triangulation within methods. Observational data and interview data are coded and analyzed separately, and then compared, as a way of validating the findings.

This form is used more frequently when the observational units are seen as multidimensional. Researchers take a method (from safety) and employ multiple strategies to examine the data. A safe questionnaire can be constructed with different measurement scales for the same empirical unit. For example, in the famous case of the alienation scales, several recent investigations have used five different indices. The obvious difficulty is that only one method is employed. Observers are mistaken if they believe that five different variations on the same method generate five triangulation varieties.

Moreover, each class of data generated -interviews, questionnaires, observation and physical evidence- is potentially biased and its specificity may be threatened. Ideally, data should converge, i.e. , they should not contradict, although conserving their multiple variations.

Triangulation among methods is a more sophisticated way of combining triangulation of dissimilar methods to illuminate the same class of phenomena; it is called among methods or triangulation through methods. The rationale in this strategy is that the weaknesses of a method constitute the strengths of another; and with a combination of methods, observers reach the best of each, overcome its weakness. Triangulation among methods can take several forms, but its basic characteristic can be the combination of two or more research strategies in studying the same empirical unit or several.

With seven research methods on research design -that in a stricter sense, would be techniques, a variety of combinations can be constructed. 1 , 2 Completely triangulated research can combine them all. Besides, if the basic strategy was participant observation, researchers can employ safe interviews with field experiments, non-obtrusive methods, filming, and life stories. Most sociological research can be seen to emphasize a dominant method, with combinations of other additional dimensions.

Kimchi et al ., state in their article Denzin’s classification and add explanations about the most adequate way of conducting the triangulation. 5 In their opinion, the specificity and the step-by-step procedures to implement the triangulation should be addressed. The purpose of their work was to present operational definitions for the types of triangulation described by Denzin in an effort to clarify the triangulation and attract researchers. Based on the theoretical definitions by Denzin, these show a group of operational definitions of the types of triangulation. The definitions seek to clarify, specify, and provide indicators that research readers can use if they deem there has been triangulation. Operational definitions were made by Kimchi during a review of all the data on which 319 articles were based from six nursing research journals published during 1986 and 1987. The six journals were: Advances in Nursing Science, Image, Inter national Journal of Nursing Studies, Nursing research, Research in Nursing and Health, Wes tern Journal of Nursing Research. The following presents some operational definitions.

- Data triangulation. 5 Considered as the use of multiple data sources to obtain diverse visions about a topic for the purpose of validation. Temporal triangulation represents data collection of the same phenomenon during different points over time, as already exposed; in these studies, time is relevant. Longitudinal studies are not considered temporal triangulation because the aim of a longitudinal study is to document changes over time and the purpose of temporal triangulation is to validate the congruence of the same phenomenon through different points over time.

- Spatial triangulation. 5 It is data collection of the same phenomenon in different sites. Space must be the central variable. Studies in which data are collected in multiple sites, but do not cross, are not considered spatial triangulation. In spatial triangulation, data are collected in two or more scenarios and tests of consistency are analyzed by crossing the sites.

-Person triangulation. 5 It is data collection from, at least, two of the three levels of person: individuals, couples, families, groups or collectives (communities, organizations or societies). Researchers can collect data from individuals, couples and groups, or each of the three types. Data collection from a source is used to validate data from the other sources or a single one. Kimchi, Polivka and Stevenson set as example the work by Hutchinson who, in 1987, studied the process of dependency on recovery ward nurses on two levels. Data were collected weekly from meetings of groups of recovery nurses over one year (group level) and in selection interviews (individual level). The phenomenon of interest was the recovery process. Each data level was used to validate the findings of the other.

- Multiple triangulation. 5 This occurs when using more than one type of triangulation in analyzing the same event, contributing more comprehensive and satisfactory sense of the phenomenon 4 ; as mentioned, it is the combination of two or more types of triangulation in a study. Using triangulation within methods and researcher triangulation in a study or using triangulation within methods and among methods in a study are two examples of multiple triangulation. Kimchi et al ., give as an example the study by Wallson et al ., which combined researcher triangulation and triangulation within methods. The group represents a multidisciplinary mix of researchers and study goals reflected on distinct values from different disciplines. Triangulation within methods was evidenced by the use of three measures of stress, each used to validate the others, a psychological measure and two written tests.

Triangulation in the analysis, a more recent type of development, is the use of two or more approaches in the analysis of the same data group for validation purposes. It is conducted by comparing data analysis results, using different statistical tests or different techniques of qualitative analysis to evaluate similarly the results available. It serves to identify similar patterns and, thus, verify the findings. Use of divergent methods of data analysis for cross-validation purposes constitutes another triangulation potential. For Denzin, 4 “ the greatest goal of triangulation is to control the personal bias of researchers and cover the intrinsic deficiencies of a single researcher or a unique theory, or the same method of study and, thus, increase the validity of the results ”.

- Combination of results: Morse 2 agrees with Mitchell in that the problem of the weight of the results of each component is solved if the findings are interpreted within the context of present knowledge. Each component should fit as a piece in a puzzle. The essential is the process of informed thought, judgment, wisdom, creativity, and reflection, and includes the privilege of modifying the theory, this is the exciting part of each research project and when there is triangulation of different methods, this is particularly exciting. If contradictory results occur from the triangulation of qualitative and quantitative methods, then a group of findings is invali d or the total result of the study is inadequate, incomplete or imprecise or both. If the study was guided deductively, the theoretical map may be incorrect.

Implementing the methodological triangulation

The methodological triangulation can be classified as simultaneous or sequential. 2 The first, when using qualitative and quantitative methods at the same time. In that case, the interaction between both data groups during the collection is limited, but the findings complement each other at the end of the study. Sequential triangulation is used if the results of a method are essential to plan another method. The qualitative method is completed before implementing the quantitative method or vice versa.

Thus, according to Morse, 2 in the methodological triangulation, the key issue is if the theory, which guides the research, is developed inductively or is used deductively, as in the quantitative inquiry. From this differentiation, various types of methodological triangulation result. If the research is directed by an inductive process and the theory is developed qualitatively and is complemented through quantitative methods, the QUAL + quan notation is used to indicate simultaneous triangulation. If the project is deductive, directed by a conceptual map a priori, the quantitative methods take precedence and can be complemented with qualitative methods. In that case, the QUAN + qual notation is used . The sequential triangulation is indicated by QUAL -› quan with an inductive project, that is, when the theoretical direction is inductive and uses a qualitative foundation. Using the QUAN -› qual notation indicates a deductive approach; that is, when we follow the complete quantitative steps and the qualitative method is used to examine or explore unexpected encounters.

The purpose of the article by Morse 2 was to explore the principles underlying the use of methodological triangulation when combining qualitative and quantitative methods. Those principles are related with the consistency among the research purpose, research problem, method used, sample selection, and interpretation of the results. The author coincides with Mitchell who highlights five areas of concern: 1) difficulty to combine text and numerical data; 2) interpretation of divergent results obtained from using qualitative and quantitative methods; 3) success or not in delineating and mixing the concepts; 4) weight of the information from different data sources, and 5) difficulty of guessing the contribution of each method when the results are similar.

The first step in the quantitative-qualitative triangulation is to determine the nature of the research problem, if it is “natural” or “social”, which aims towards a primarily quantitative or qualitative approach. Characteristics of a qualitative research problem: 1) the concept under study is immature due to weak success and conspicuous theory and prior research; 2) a notion that the available theory may be inappropriate, incorrect or biased; 3) a need exists to explore and describe the phenomenon and develop theory, or 4) the nature of the phenomenon is not appropriate for quantitative measurements.

If a research problem is quantitative, the characteristics described are not applicable. Researchers can locate substantial and relevant literature about the topic, create a conceptual map, and identify hypothesis to test. In this case, the research design is comparative or correlational, experimental or quasi-experimental.

The qualitative and quantitative aspects of a research project cannot be weighed equally: besides, a project must be guided theoretically by qualitative methods incorporating a complementary quantitative component, or guided theoretically by a quantitative method incorporating a complementary qualitative component. The important point is that each method must be complete in itself, that is, all the methods used must appropriate rigor criteria. If qualitative interviews are conducted, this must be done as if this method were alone. The interviews must continue while saturation is reached, and the content analysis has to be carried out inductively, more than forcing the data within a category preconceived for the study.

Further, triangulation may be used with different objectives, among them, the following:

• Triangulation is linked by many authors with rigor and quality; in that sense, one of the expectations is to increase research rigor, 6 thus, Flick 7 highlights triangulation as “a way to promote quality in research”.
• Triangulation as verification: for Patton, 8 studies using multiple methods that analyze different types of data “provide cross validation”. A les common use of triangulation is to ensure the validity of the instruments. However, this approach should be cautious, testing an instrument before its implementation or establishing its validity during the pilot test.
• Triangulation as completeness: for Patton 8 “(…) qualitative and quantitative data can be combined fruitfully when these elucidate complementary aspects of the same phenomenon”.
• Interdisciplinarity: Flick 9 proposes the possibility of conducting a “systematic triangulation of perspectives”, which may imply “researcher triangulation as collaborative strategy”; this opens the possibility addressing at least the multi- or interdisciplinarity; as proposed by Janesick: 10 I would wish to add a fifth type: “interdisciplinary triangulation”.

In synthesis, following Molina, 11 triangulation can “(…) expand the research process to contribute to deeper and broader comprehension of the phenomenon, given that it adds “(…) rigor, amplitude, complexity, richness, and depth to any research”.

Mixed methods in research -perspective under development and emerging since the 1990s- emphasize on integrating different data sets, as highlighted by Creswell. 12 The author starts from the labels and notations exposed by Morse who was the precursor of said nomenclature and Creswell proposes it to differentiate design categories or typologies possible to apply in said methods. 12 Said combined methods “have extended rapidly through social and behavioral sciences”, as stated by Timans, Wouters, and Heilbron 13 and “have developed linked to the triangulation concept”. 12 Some authors denominate the singularly as mixed method.

The complementarity of methods

Defining qualitative research as development of theories and generation of hypothesis, and quantitative research as modification of theories and tests of hypothesis, Field and Morse have identified the complementarity of both approaches.

For Morse, 2 the biggest threat to validity is the use of inadequate or inappropriate samples. Perhaps due to reasons of convenience, researchers have sought to use the same subjects for both methods, qualitative and quantitative, although it is clearly inappropriate to exchange those samples. For example, quantitative research is based on large representative samples of the population randomly selected; adjustment of the sample is determined statistically, as well as its representativity of the whole population. In qualitative research, appropriation is in relation to how well the sample can represent the phenomenon of interest (for example, how much have the participants experienced the phenomenon and can articulate their experiences); the sample will be adequate when data saturation is enriched. Still, in light of the overall purpose of research, no reason exists (different from convenience) to use the same subjects for both samples.

Clearly, when incorporating quantitative methods within a qualitative study, the qualitative sample may be inadequate for quantitative purposes. Lack of representativity of the qualitative sample selected in purpose is inappropriate and threatens the validity. Selection of the sample through the qualitative and quantitative components of a sequential ( QUAL -› quan ) or simultaneous ( QUAL + quan ) triangulation must be independent. Because the quantitative sample is inadequate and inappropriate for quantitative purposes, researchers must design a quantitative sample for the population. However, when the quantitative method is used to add more information about the qualitative sample ( QUAL + quan ), exceptions can be made if the norms so permit, or if a comparison is available of a normal group, to interpret the results. For example, if dealing with the anxiety of the relatives in the waiting room, the anxiety scales can be interpreted with the norms available for anxiety scales.

A subsample may be used from a large quantitative sample for the qualitative component of the QUAN + qual or QUAL -› quan triangulation , but those subjects included or the incidental observations in the qualitative part must be selected according with the criterion of good participants than through random selection. Thereby, the subjects selected for the quantitative sample must have greater experience and articulation, and the observations selected must consider the best examples of the situation.

Methodological triangulation is not a term applied to ethnography when the research method includes the use of semi-structured interviews, some levels of participant observation, use of recordings, and administration of questionnaires. It is the combination of said techniques that constitutes the ethnography and what makes ethnography, ethnography. It is not the case of blending or integrating guides from both texts, qualitative and quantitative, rather, it is using appropriate strategies to maintain the validity of each method. The QUAN + qual triangulation is not only the addition of linguistic and narrative data in an experimental design; at least, the interview data must be collected and analyzed according with the assumptions and principles of the qualitative method. Similarly, incorporating one or two open questions within the quantitative survey does not make study qualitative.

Additionally, using quantitative data in a qualitative study (like frequency data to improve the description), does not constitute a quantitative study. Methodological triangulation is not a technique to use due to rapidity and convenience in the research. Well done, it will likely lengthen the duration of the project, but the gains reached in the long term are immensurable.

Methodological triangulation is not a concurrent validation technique. Although the same strategies may be used, these are implemented in a study for different motives. The purpose of the concurrent validation is to find if the results of measuring the same concept through both methods are equivalent. The purpose of simultaneous triangulation is to obtain different but complementary data on the same topic, more than replicating the results.

According to Knafl, methodological triangulation is not merely to maximize the strength and minimize the weakness of each method. If a careful approach is not made, the end result may be to broaden the weakness of each method and invalidate completely the research project. It is more a method to obtain complementary findings and contribute to the theory and development of knowledge.

Some of the controversies of methodological triangulation have emphasized on the issue of qualitative research against quantitative. This controversy advocates for the combination of methods inasmuch as it is consistent with theoretical research. Some researchers forget that research methodologies are only tools, instruments that when used facilitate understanding. Researchers should be versatile and have a repertoire of methods available. To broaden the foregoing, a summary is presented of the discussion by Cowman about the paradigms and the author’s proposal regarding triangulation. 3

Quantitative approach was the dominant paradigm from 1950 until 1990; the research approach - in turn - has been increasingly localized on the qualitative paradigm. Within the literature there is general support to separate both paradigms. However, accepting the inherent differences between the two, researchers are concerned that no isolated method can provide understanding of human beings and of their complex needs. Triangulation, as research strategy, represents the integration of two research approaches. The literature that explores its merits in research is incomplete, however, it is reported that triangulation, by reconciling the paradigmatic assumptions of quantitative and qualitative methods, provides richness and productive data. Triangulation offers a bipolar alternative and approaches the quantitative and qualitative. The qualitative-quantitative debate is still in development. It should be noted that each research perspective has several inherent differences. The quantitative approach has been associated exclusively with the dominant empirical-analytical paradigm and sees the causes of human behavior through observations that seek to be objective and collects quantifiable data. More often, research methods are associated with experimental research designs, which examine the causal relations among variables, controlled or removed from their natural scenario and observations are quantified and analyzed through statistically determined probabilities.

Quantitative research holds the methodological assumption that the social world looks at itself through objective forms of measurement. Conversely, Leininger 1985 suggests that people are not reducible to measurable objects and that they do not exist independently of their historical, social, and cultural context. The qualitative paradigm emerges from a tradition in sociology and anthropology, techniques to obtain qualitative data permit observing the world from the perspective of the subject, not the researcher. The qualitative paradigm is concerned for the value of the meaning and for the social world from which this meaning derives; through a variety of theoretical perspectives and research traditions that include phenomenology and ethnography, natural and family data are valued and serve to gain understanding of people. Differences between quantitative and qualitative approaches can be seen, even at the most basic level. The qualitative approach develops theory inductively from the data; in quantitative research, it is done deductively and its methods are encouraged primarily as a theory subjected to statistical tests, that is, falsifiable in Popperian terms.

Knowing the natural difficulties of research quantitative and qualitative methods and having identified the need to integrate the research approaches, the triangulation strategy is proposed. Cowman 3 accepts four principles underscored by Mitchell, 14 which, applied carefully, point to maximizing the validity of a particular research, incorporating the methodological triangulation: 1) the research question must be clearly focused, 2) the strengths and weaknesses of each method chosen must complement the other, 3) methods must be selected according with their relevance for the nature of the phenomenon under study, and 4) a continuous evaluation must be performed of the method selected during the course of the research to monitor if the three previous principles are being followed. These consistency elements also apply in mixed methods.

Cowman 3 also warns of possible difficulties of triangulation: in first instance, a researcher, accepting the advantages of triangulation, can lose sight of differences between the methods chosen. Danger exists in collecting large volumes of data, which - subsequently - it will not be possible to analyze or are dealt with superficially. Fielding and Fielding emphasized on the danger of taking multiple methods without using simultaneously the bias control procedure.

Moreover, triangulation provides strengths, like animation, creativity, flexibility, and depth in data collection and analysis; as indicated by Cohen and Manion, methodologists often push methods as pets because those are the only methods with which they are familiar or because they believe that their method is superior to all the rest. Reichardt and Cook suggest that it is time to stop constructing walls between methods and start building bridges.

Given that the methods need independence within a single project, the real issue in triangulation can go beyond incompatibility between different assumptions of two paradigms, as argued by several researchers. It also assumes the possible incompatibility of contrasting philosophical issues, of static and dynamic realities, of objective and subjective perspectives, of inductive and deductive approaches or of integral and particular visions. It is not the elusive mix of numerical and text data or of simultaneous considerations of antagonistic approaches of causality and non-causality. Integration of data does not occur in the analysis process, but in the union of the results of each study within a cohesive and coherent product where the confirmation or revision of the existing theory takes place. This can be achieved through adhesion to the rules and assumptions of each method in selecting the sample, purpose, method, and the contribution of the results within the research plan as a whole.

* How to cite this article: Arias Valencia MM. Principles, Scope, and Limitations of the Methodological Triangula-tion. Invest. Educ. Enferm. 2022; 40(2):e03.

CONCEPTUAL ANALYSIS article

Expanding the scope of “trans-humanism”: situating within the framework of life and death education – the importance of a “trans-mystical mindset”.

• 1 School of Education, University of New England, Armidale, NSW, Australia
• 2 Department of Education, National Taipei University of Education, Taipei, Taiwan

Life and death education , as noted from the literatures, has been studied and researched extensively in China, Malaysia, and Taiwan. Our own research undertakings over the past several years, situated in different sociocultural settings have delved into aspects of life and death that could help advance theoretical understanding of the subject matters (e.g., does the meaning of “effective life functioning” connote differing interpretations for different cultural groups?). Situating within the framework of life and death education, we expand the study of trans-humanism by introducing an extended prefix or nomenclature known as “trans-mystical”. Specifically, our philosophized concept of trans-mysticism considers a related concept, which we term as a “trans-mystical mindset”. A trans-mystical mindset, differing from an ordinary mindset, from our philosophical rationalization, is defined as “a person’s higher-order state of consciousness, espousing her perception, judgment, belief, and attempted interpretation of life and death phenomena that are mystifying and fall outside the ordinary boundaries of human psyche.” Our focus of inquiry, as reported in the present article, seeks to advance our proposition: that a trans-mystical mindset, unlike an ordinary mindset, may help a person to rationalize, appreciate, and understand metaphysical contexts, mystical experiences, and the like. This focus, interestingly, serves to highlight an important discourse - namely, that there is a dichotomy in theoretical lenses (i.e., objective reality vs. individual subjectivity) that a person may use to rationalize the significance or non-significance of universal contexts, events, phenomena, etc. (e.g., a person’s experience of “premonition”). As such, then, there is an important question that we seek to consider: whether philosophization, or the use of philosophical psychology, would yield perceived “scientific evidence” to support or to reject the study of metaphysicism, mysticism, and the like? For example, does our philosophization of an “equivalency” between a person’s trans-mystical mindset and her experience of self-transcendence help to normalize and/or to scientize the subject matters of metaphysicism, mysticism, etc.?

1 Introduction

The subject of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ) has significant daily relevance and applicability for us in society to consider. Personal understanding of life education , for example, may inform and educate a person about the diverse meanings and purposes of effective life functioning (e.g., the attainment of financial success in life vs. the attainment of good health). In relation to death education , likewise, a senior citizen’s spiritual knowledge of “transcendence” ( Conn, 1998 ; Long, 2000 ; Ge and Yang, 2023 ), or his perceived “spiritual connectedness” to God ( Laurin et al., 2014 ; Cohen-Zimerman et al., 2020 ), may assist him with his coping of grief. On a formal front, conceptual and/or empirical research development of life and death education may yield evidence to help elucidate and/or explain the underlying nature of the subject contents.

Our own teaching and research undertakings over the past decade have delved into different aspects of life and death education. For example, recently, we introduced a theoretical concept that we termed as a “holistic mindset”, or a person’s “multiple mindsets” ( Phan et al., 2024 ). In brief, we theorize that a person may possess multiple contextual mindsets at any moment in time for adaptation and accommodation of different life and death contexts. For example, a Catholic nun may possess and exhibit a strong “spiritual mindset” whereas, in contrast, a scholar of Buddhism ( Masel et al., 2012 ; Prude, 2019 ) may possess and exhibit a strong “philosophical mindset”. In a similar vein, a doctorate student preparing for an oral exam is more likely than most to possess and exhibit a “cognitive mindset”. Our theorization then, contends that a specific life context (e.g., the context of academic learning) would define and/or espouse a corresponding “contextual mindset”.

One particular life context that we are interested in is known as a “trans-mystical context” or a perceived mystical context. There are metaphysical or mystical life and death contexts in this world that are somewhat anomalistic and non-conventional. For example, some cultural groups may engage in the practice of “ancestor worshipping” ( Steadman et al., 1996 ), whereas other cultural groups may view this practice with a sense of intellectual curiosity. In a similar vein, there are some of us who have reported the personal experience of “premonition”. 1 We purport that ancestor worshipping, premonition, the belief in “reincarnation” ( Nagaraj et al., 2013 ; Burley, 2014 ), and the like are metaphysical contexts or “non-daily” contexts. Such contexts, we contend, may elicit perceived experiences that are somewhat subjective and whether they fall outside the realm of objectivity and/or the realm of ordinary human psyche. Importantly, however, we reason that the scientific premise of psychology may provide sound, logical accounts to help explain the “uniqueness” of metaphysical contexts. That perhaps, despite individual subjectivity in perception, interpretation, and reason, metaphysical contexts and/or mystical experiences are just on par with “ordinary” contexts, life experiences, etc.

Our focus of inquiry for consideration relates to the advancement of the study of “trans-mysticism”. In particular, we philosophize a psychological concept, termed as a “trans-mystical mindset”, that may help to show how metaphysicism can be subjectively rational. In brief, we define a person’s “trans-mystical mindset” as:

A “contemplative higher-order, mystical” state that details his/her perception, attitude, judgment towards some “unknown” and/or extraordinary life concept, life phenomenon, event, situation, etc. (e.g., a person’s trans-mystical mindset towards the notion of “post-death” experience).

A trans-mystical mindset, as defined, may help a person to reason and/or to make meaningful sense of a metaphysical context and/or a mystical encounter (e.g., a person’s experience of premonition). By the same token, encountering a metaphysical context or a mystical life/death experience may help necessitate, facilitate, sustain a person’s trans-mystical mindset and his willingness to accept that such an encounter is valid. From this then, situating within the scope of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ), we premise a significant principle for consideration:

That metaphysical or mystical contexts (e.g., a perception of “spiritual transportation” to another time-space realm) are pivotal to the “formation” of a trans-mystical mindset, or that a person’s trans-mystical mindset is intimately linked to her trans-mystical life/death experiences.

Our position or standing is that psychological grounding (e.g., the use of the discourse of philosophical psychology, which entails the proposition of a trans-mystical mindset) may offer robust explanations for metaphysical encounters. More importantly, however, we contend that our philosophical undertaking here may form the basis for future examination of something that is somewhat contentious: that psychological inquiries alone cannot encapsulate and/or explain the uniqueness of metaphysical contexts; rather, as a possibility and something that is beyond the scope of this conceptual analysis article, is the fact that metaphysical contexts and mystical experiences have alternative interpretations and meanings – for example, the context of premonition ( Cameron, 1958 ; Dossey, 2009 ), one’s belief in reincarnation ( Nagaraj et al., 2013 ; Burley, 2014 ), and the like cannot simply be validated or vindicated by scientific inquiries.

Overall, then, the present conceptual analysis article uses philosophical psychology ( Thagard, 2014 ; Thagard, 2018 ; Phan et al., 2024 ) to help “normalize” and/or to “scientize” the subject matters of trans-mysticism. That philosophizing the concept of trans-mysticism (e.g., a trans-mystical mindset) and “benchmarking” this against Maslow’s (1968 , 1969) theory of the “hierarchy of needs” may, in fact, validate and/or legitimize the importance of metaphysical contexts, mystical life and death experiences, etc. This line of inquiry, we contend, emphasizes an important standing: the premise of “objectivity” vs. the premise of “subjectivity”. Objectivity indicates consistency , transparency , realism , and non-biased judgment , whereas subjectivity, in contrast, considers openness , personal viewpoint and interpretation , and individualistic thinking . Regardless of one’s position, we firmly believe that our philosophized concept of trans-mysticism and thereafter may advance the study of life and death education. In the following section of the article, we discuss a number of elements – namely:

i. An introduction of a theoretical account of the subject of life and death education.

ii. An examination of the nature of a proposed life and death-related concept that we term as “trans-mysticism”.

iii. A proposition of a theoretical premise, which purports the process of transformation of a person’s ordinary mindset, resulting in a trans-mystical mindset.

iv. A proposition of an association, which purports a situational placement or contextualization, highlighting a potential equivalence between a trans-mystical mindset and a state of self-transcendence.

v. A discussion of a few notable inquiries for teaching and research development purposes.

2 The importance of life and death education: a brief introduction

Life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ) is an interesting subject for teaching and learning, given its potential relevance and significance for daily life purposes. The study of life and death education, in its entirety, seeks to understand and appreciate the intricacies or complexities of human existence from different historical-sociocultural perspectives (e.g., what does proactive life functioning mean for South Pacific Islanders?). Life education , in brief, relates to the teaching of specific tenets about life that may enable and/or assist a person to live a cherished and self-fulfilling life. A cherished and self-fulfilling life, say, may consist of a person’s feeling of self-gratification, arising from her successful attainment of financial wealth. In a similar vein, but somewhat different, a cherished and self-fulfilling life may reflect a person’s daily practice to impart his life wisdom onto others. Such teaching is meaningful and may serve to enlighten individuals, their families, and society in general. One distinction, in this case, refers to a person’s appreciation and acknowledgment that variations in historical-sociocultural context (e.g., a child who grows up in an Indonesian historical-sociocultural context) give rise to different life courses and life trajectories (e.g., a child who grows up in an Indonesian sociocultural context, and the shaping of her aspirations, desires, future intentions, etc.). In a similar vein, a person’s life wisdom or life knowledge ( Goldstein and Kornfield, 1987 , Sternberg and Glück, 2019 , Chattopadhyay, 2022 ) may be transformed into practice for daily life purposes.

Life education seeks to provide quality teaching, theoretical insights, and relevant information that may assist, explain, and facilitate proactive daily life functioning. Proactive life functioning on a daily basis is vibrant and healthy, helping a person to fulfill and attain a desirable life trajectory or trajectories. Different life contexts (e.g., the context of academic learning) on a daily basis, we contend, connote different types of proactive functioning – for example, the life context of awareness of the danger that COVID-19 poses ( Willyard, 2023 ) may compel a person, in this case, to seek appropriate pathways to ensure that she has a healthy life trajectory. In a similar vein, the life context of the importance of academic attainments may shape a student’s mindset to seek mastery and deep, meaningful learning experiences in his schooling. Regardless of diversity of life contexts, life education places emphasis on the recognition, promotion, and development of a cherished and self-fulfilling life.

Death education , or the study of thanatology ( Meagher and Balk, 2013 ; Chapple et al., 2017 ), in contrast, seeks to understand the intricate nature of death and other dying-related matters (e.g., the process of grief for a loved one). For example, angst, stress, sadness, and depression are life matters that closely associate with death. Unlike life education, which is positive, vibrant, and self-fulfilling, death education is morbid and undesirable for teaching and learning. For example, the teaching of death education seeks to educate individuals, family members, and society the following aspects:

i. The perception, viewpoint, and/or belief that one has towards the subject of death (e.g., how does one feel, at present, knowing that a loved one is facing a critical illness?).

ii. Personal care and preparation from others (e.g., social workers, volunteers) to assist with the impending encounter and/or facing of death.

iii. Stages and processes (e.g., counselling, spiritual advice, etc.) that are associated with grief and bereavement upon the death of a loved on.

iv. Consideration of programs, strategies, pathways, etc. that could help alleviate the negative emotions, feelings, perceptions, etc. that one may have when faced with a death-related matter.

Our study of life and death education for teaching and theoretical contribution purposes over the past decade has led us to undertake a few notable developments – namely, the testament of the following: Focus on instructional designs and pedagogical approaches (2.1), Research inquiries for consideration (2.2), and Advancement in theoretical contributions (2.3).

2.1 Focus on instructional designs and pedagogical approaches

Focus on appropriate instructional designs and pedagogical approaches that may instill appreciation and facilitate effective learning experiences for the subject life and death education (e.g., appreciating that death education has potential daily life relevance). We propose an interesting idea known as “theoretical infusion”, which involves the practice of “infusion” of a particular faith, epistemological belief, customary practice, discourse, etc. in the teaching of life and death. “Spiritual infusion”, for example, details the incorporation of spirituality, or one’s spiritual faith ( Schneiders, 1986 ; Wagani and Colucci, 2018 ; Villani et al., 2019 ), to complement the teaching of life and death, making it more stimulating and “life-related” for learning. Theoretical infusion (e.g., Buddhist spiritual infusion), we contend, may serve to associate subject contents of life and death with other meaningful and/or related contents. In other words, theoretical infusion is used to encourage students to appreciate subject contents of other topics and/or subjects (e.g., appreciating the importance of Christianity from a life perspective) within the context of life and death education. By the same token, we rationalize the benefits of embedding subject contents of life and death within other subject contexts (e.g., how does Christian faith view death?). Having said this, however, we also acknowledge an important mentioning from one of our reviewers in an earlier draft of this article – that we need to also consider the potential “negativity” of our idea of theoretical infusion. That engaging in theoretical infusion (e.g., infusing a particular religious or spiritual faith to support the teaching of death education) may, in fact, amount to and/or be perceived as a form of “indoctrination”. A student with no religious affiliation, in this instance, may feel pressured to accept the practice of “Buddhist spiritual infusion” as a “norm”.

Aside from theoretical infusion, we also propose and use another discourse that we term as “active transformation”. In brief, active transformation relates to one’s self-cognizance of daily practicality of knowledge pertaining to life and death. In other words, active transformation emphasizes the important nexus between theory and practice – for example, how can a teenager use her personal understanding of Confucianism ( Yao, 2000 ; Havens, 2013 ) to assist others in the neighborhood? As such, then, we rationalize that our idea or theoretical premise of active transformation may serve to impart benefits for individuals and society. For example, a mother may accompany her son and make weekly visits, offering spiritual advice and life wisdom on different life and death-related matters to those in this need. This voluntary periodic engagement reflects her willingness to help others in the community and, more importantly, showcases proactive practice of active transformation of life wisdom, or life knowledge. Again, having said this, we are cognizant of one of our reviewers’ earlier mentioning: that the idea or the theoretical premise of active transformation may, likewise, produce negative yields. A person’s inclination towards some form of negativity, in this case, may compel her to engage in negative or maladaptive functioning. That rather than offering sound spiritual advice, a mother may instead transform her life wisdom about spirituality for negative purposes (e.g., a purposively act to indoctrinate a senior citizen with a biased view of Buddhist spirituality).

2.2 Research inquiries for consideration

Concerted attempts to seek new research frontiers that may amplify the importance of the subject life and death. One aspect of our research development, at present, seeks to understand and appreciate the importance of life and death from two contrasting positions: objectivity and subjectivity . Certain life and death matters (e.g., the proposed notion of “post-death” experience) ( Phan et al., 2024 ), we contend, compel and/or require us to seek alternative research discourses for understanding. For example, over the past few years, our use of philosophical reasoning ( Thagard, 2014 ; Thagard, 2018 ; Phan et al., 2024 ) has assisted us to understand about the study of life and death experiences (e.g., attainment of theoretical insights and explanatory accounts of life and death). Philosophical inquiries, from our point of view, may to complement contrasting research discourses and help to yield scientific credence for support. Engaging in philosophical analysis, we contend, may serve to encourage researchers to think non-conventionally and outside the box. Higher-order thinking, reflection, etc. may give rise to contemplation of research propositions for discussion. Our intent over the past several years has been to expand the scope of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ) by seeking to understand the known and unknown “unknowns” of life and death experiences. This line of research development is somewhat different from other inquiries and research undertakings that place emphasis on the “knowns” of life and death experiences (e.g., the intimate process of grief). The “unknowns” of life and death are more interesting as they delve into unexplained complexities of human existence that do not have clear, consistent explanatory accounts.

2.3 Advancement in theoretical contributions

Our interest, aside from teaching and research purposes, also seeks to make meaningful theoretical contributions to the study of life and death education ( Chen, 2013 , Huang, 2014 , Seng and Lee, 2022 ). One aspect of our research development focuses on the examination and reading of the literatures, pertaining to the importance of variations of different historical-sociocultural contexts of life and death functioning. In brief, we note from our own research undertakings that different historical-sociocultural contexts offer unique insights into the viewpoint, opinion, perception, and interpretation of life and death experiences. For example, in terms of life functioning, we note that many Taiwanese believe in the attainment of “spiritual growth” in place of financial wealth. In a similar vein, many Taiwanese engage in the practice of “ancestor worshipping” ( Steadman et al., 1996 ) and believe in the “afterlife” ( Segal, 2004 ; Jones, 2016 ).

Gauging into the “historical-sociocultural contextualization” of life and death is meaningful as it offers unique understandings of life and death experiences. One distinction about this focus of inquiry is that unlike other disciplines and/or fields of research, the subject of life and death has comparable and contrasting viewpoints, opinions, perceptions, interpretations, etc. That understanding of life and/or of death (e.g., is there any validity to the notion of afterlife?), for example, differs for different ethnic-cultural groups. At present, one of our research undertakings seeks to understand the uniqueness of the Australian Aboriginal and Torres Strait Islander culture and her viewpoint, interpretation, status quo, etc. about life and death. One of our colleagues, who is a Torres Strait Islander, has shared with us some interesting facts for consideration. According to our colleague, many Australian Aboriginal and Torres Strait Islander peoples believe in the existence of rebirth where a deceased is transformed into a new “being”. To facilitate success in such a process, it is poignant that relatives and loved ones do not mention the deceased’s name for 12 months [e.g., “Do you remember when Sarah (i.e., the deceased) used to say this…?”].

3 The present conceptualization

Our aforementioned description of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ) has provided grounding for our philosophical inquiry and research undertaking, which delve into the nature of a proposed concept known as “trans-mysticism” or, alternatively, trans-mystical studies. For us, as a proposition, trans-mysticism is a combination or the unification of two distinct areas of research of trans-humanism: transpersonalism ( Strohl, 1998 ; Lancaster and Linders, 2019 ) and mysticism ( Schneiderman, 1967 ; Bronkhorst, 2022 ). It is important to note that our proposed term of trans-humanism differs from the more recent practice or use of the term (i.e., “trans-humanism”), which contends the possibility that we could use technological advances to augment human capabilities. Trans-mysticism, for us specifically, is a psychological premise that that may assist researchers, educators, students, etc. to understand, appreciate, and/or accept the existence of metaphysical contexts and the anomalistic and “non-realistic states” of life and death. More importantly, we rationalize that our philosophized concept of trans-mysticism (e.g., a “trans-mystical mindset”) may help to “normalize” and/or to “scientize” the subject matters of metaphysicism, mysticism, and the like. For example, one of our articles published recently ( Phan et al., 2021 ) introduces readers to a specific cultural belief (and/or the cultural practice) known as the “underworld” or the “other world” by which a person could travel to interact with loved ones who have moved on. This mentioning may, indeed, give rise to criticisms, disbeliefs, doubts, uncertainties, etc. In a similar vein, unbeknown to some or many in the Western world, perhaps, but the cultural practice of ancestor worshipping ( Townsend, 1969 ; Steadman et al., 1996 ; Lakos, 2010 ; Clark and Palmer, 2016 ) connotes a specific meaning for those in the Eastern world. Aside from veneration for the dead, this cultural practice also signifies the importance in what is known as “spiritual connectedness” or spiritual communication between the dead and the living – for instance, a daughter may pay homage to her deceased father by lighting incenses and asking for his specific blessing to assist her with the forthcoming final exams.

We reason and contend that philosophical research inquiries in the social sciences (i.e., a research inquiry that utilizes the discourse of philosophical psychology) may affirm one of two things: validating a proposed inquiry with supporting “philosophical” evidence or invalidating a proposed inquiry due to a lack of “philosophical” evidence – for example: that there is support for the proposed concept of trans-mysticism, which may help to provide robust explanations for metaphysical encounters. Of course, it is plausible to purport that trans-mysticism may simply be philosophical and lacks logical credence or legitimate merits for further consideration. One of our reviewers, in an earlier draft of the manuscript, offered an interesting critique: that resorting to the use of philosophical psychology ( Thagard, 2014 ; Thagard, 2018 ; Phan et al., 2024 ) or that philosophizing about the nature of a metaphysical context (e.g., one’s ability to interact with a loved one who has moved on) does not necessarily make it valid or credible for research development. Our conceptualized approach, in this case, argues that psychological tenets may be used to explain the underlying nature of metaphysical contexts and/or mystical experiences in life. That the psychological concept of trans-mysticism may, for example:

i. Help to “normalize”, “scientize”, and/or “legitimize” the study of metaphysical contexts and/or non-ordinary or extraordinary realms of human existence ( Rush, 2011 ; Pasi, 2015 ).

ii. Help us appreciate the trans-mystical nature of metaphysical contexts and/or mystical experiences (e.g., a person’s testament of her ability to “detect” dark spiritual “energy” of a loved one).

Over the course of our research development, from conception to subsequent refinement of the article, we have evolved in our thinking and deliberation. Poignant then is our main focus of inquiry, which seeks to capitalize on the use of psychological theories (e.g., transpersonalism) to explain the intricate nature of metaphysicism, mysticism, and the like. Central to our thesis is the robust explanatory account, epistemically objective in nature, of the aforementioned subject of one’s metaphysical or mystical encounters. That ultimately, perhaps, differing subjective universal encounters and/or experiences (e.g., the metaphysical encounter of a loved one who has moved on vs. the daily encounter of a next-door neighbor) may “subsume” within a common prism or theoretical lens for understanding. A related inquiry for future consideration, which falls outside the scope of the present article relates to the confirmation or the epistemic validation of the trans-mystical nature of metaphysical contexts and/or mystical experiences (e.g., that indeed there is something unique or mysterious about a particular metaphysical encounter, and this personal experience does not coincide with objective reality).

3.1 A brief account of transpersonalism and transpersonal psychology

In this section of the article, we briefly discuss a related topic known as transpersonalism ( Strohl, 1998 ; Lancaster and Linders, 2019 ) and transpersonal psychology ( Maslow, 1969 ; Hartelius et al., 2007 ). This topic, we contend, is important and relates to our theoretical premise of trans-mysticism. It is interesting to note that there is a distinction between transpersonalism and transpersonal psychology or that, in fact, the two areas or disciplines are not identical or equivalent ( Friedman, 2002 ; Shorrock, 2008 ). Friedman’s (2002) theoretical account offers a detailed analysis – for example:

“The former [i.e., transpersonalism] is a broadly defined domain of inquiry that can legitimately include a diversity of methods ranging from those of the humanities to those of a variety of scientific endeavors. Psychology, on the other hand, is defined by most psychologists as a scientific discipline; except for a few humanistic and transpersonal adherents who insist that including alternative, that is, nonscientific, approaches is important for the discipline, science is widely accepted as the mainstay of the discipline…. Furthermore, I see transpersonal psychology foremost as a field within the discipline of scientific psychology that focuses on those aspects of trans personal studies that involve the individual, including thoughts, feelings, and behaviors as found in the individual’s biological, cultural, social, and wider contexts” (pp. 180–181).

A more detailed explanation is noted in Shorrock’s (2008) book, titled “ The Transpersonal in Psychology, Psychotherapy, and Counselling ”. Shorrock’s (2008) account of transpersonalism and transpersonal psychology is comprehensive, outlining the genesis, complexity, and the numerous definitions and viewpoints that scholars over the years have proposed. The word count of the present article limits us from detailing Shorrock’s (2008) book and/or the complete gamut of definitions, viewpoints, perspectives, etc. of both disciplines. For the purpose of our rationale, we provide a few definitions of the two areas/disciplines for readers to appreciate ( Table 1 ). From Table 1 , a point of commonality between transpersonal psychology ( Tart, 1975 ; Lajoie and Shapiro, 1992 ; Cunningham, 2007 ) and transpersonalism ( Strohl, 1998 ; Lancaster and Linders, 2019 ), in this case, is the use of the prefix “trans” ( Lancaster and Linders, 2019 ) or the extended prefix or term “transpersonal”, which is defined as “as reaching beyond the personal realm or transcending the singular, personal state of being” ( Clark, 2016 ). Moreover, from our analysis, the significance or the uniqueness of transpersonalism and transpersonal psychology relates to the following: that decisions to accept or to reject transpersonalism and/or transpersonal psychology are largely based on scientific rigor and a researcher’s ability to empirically validate using scientific means (e.g., is it possible?) ( Friedman, 2002 ; Shorrock, 2008 ). Transpersonal psychology is considered as being more robust, valid, and/or legitimate for its scope, which closely aligns to the rigor of scientific psychology ( Friedman, 2002 ; Shorrock, 2008 ).

Table 1 . A summary of sample definitions of transpersonalism and transpersonal psychology.

Despite contrasting definitions ( Table 1 ), we argue that both transpersonalism ( Strohl, 1998 , Lancaster and Linders, 2019 ) and transpersonal psychology ( Tart, 1975 , Lajoie and Shapiro, 1992 , Cunningham, 2007 ) are comparable with each other in terms of interpretation, understanding, and inference. Central to this rationale is that regardless of methodological considerations (e.g., what methodological approach would be best to investigate…?), the study of transpersonalism and the study of transpersonal psychology both subsume within or fall under the umbrella of what we term as “trans-humanistic” development. That trans-humanistic studies, in their entirety, can offer insights and theoretical understandings into the underlying nature of “humanism”. Moreover, we premise that our philosophized nomenclature and/or concept of trans-mysticism, likewise, may subsume within the overarching framework of trans-humanism. In other words, for consideration, is the following extrapolation: that the trans-humanistic framework, especially the tenets of trans-mysticism may provide theoretical grounding to help us gauge into the logic , validity , and legitimacy (e.g., objectivity vs. subjectivity) of the study of metaphysical contexts and mystical life and death experiences – for example, near-death experiences, spiritually transformative experiences, spiritual awakenings, peak experiences, and ecstatic experiences.

3.2 Trans-mystical development: a proposition

Trans-mysticism , as a distinct concept, may contribute to the study of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ) by accentuating the significance of metaphysical contexts and mystical of life and death experiences, such as:

• The personal experience of “premonition” ( Cameron, 1958 ; Dossey, 2009 ).

• Personal belief in the concept of “reincarnation” ( Nagaraj et al., 2013 ; Barua, 2017 ), or the concept of the endless cycle of “birth-death-rebirth”.

• The personal experience of “spirit communication” with loved ones who have moved on (e.g., the ritual practice of Guan Lou Yin) ( Buckland, 2004 ; Phan et al., 2021 ).

• The personal experience of “time–space transcendence” (i.e., one’s ability to transcend to another time–space context) ( Phan et al., 2024 ).

The proposed prefix or nomenclature “trans-mystical” is somewhat unique for its unification of two distinct areas of research: trans-humanistic studies (e.g., the study of a person’s experience of self-transcendence, which showcases a higher-order form of life functioning) + mystical studies (e.g., the study of a person’s esoteric experience of perceived spirit communication). Trans-mysticism, in accordance with our rationale, is closely associated with the specific subject matters of metaphysicism and mysticism. That our justification for the inclusion of the concept of trans-mysticism arises from the following understanding: that there is an intimate association between life/death context (i.e., metaphysical or mystical context) and a person’s individual mindset . Moreover, from our point of view, the theoretical premise of psychological concept of trans-mysticism is as follows: that personal experience of metaphysical contexts and/or mystical phenomena may give rise to the necessitation , development , and manifestation of a “trans-mystical mindset”. What is a trans-mystical mindset, which subsumes under the theoretical framework of trans-mysticism? For the context of the present article, we define a trans-mystical mindset as:

The ultimate human experience and/or a higher-order state of consciousness of a person, espousing her perception , judgment , belief , and attempted interpretation of metaphysical contexts and/or of life and death phenomena that are mystifying and fall outside the ordinary boundaries of human psyche.

Our philosophization contends that a trans-mystical mindset is contextual (i.e., it is contextualized or is situated within the metaphysical or the trans-mystical life and death contexts) and differs, in this case, from a person’s “ordinary” mindset ( Figure 1 ). There are perhaps a few unique characteristics for us to consider – namely:

i. A trans-mystical mindset is an internalized state that is perceived as being complex and/or higher-order. A trans-mystical mindset is different from an ordinary mindset, which espouses the “perception of normality” or the “realm of conventional human psyche”. An ordinary mindset, in this case, manifests and functions to facilitate successful adaptation of typical or standard daily life contexts (e.g., the context of academic learning in university or the context of a bank employee adapting to his new workplace environment).

ii. Existence of a trans-mystical mindset corresponds to and/or contextualizes to a specific metaphysical context, which may result in a person experiencing some form of mysticism (e.g., a person’s experience of premonition).

iii. There is a demarcation between what is “ordinary” and what is “extraordinary” and this distinction, in fact, explains the nature between an ordinary mindset and a trans-mystical mindset ( Figure 1 ).

Figure 1 . Structure of trans-mystical mindset.

Our philosophization has so far introduced an interesting discourse for consideration: the uniqueness in perception, interpretation, and understanding of life and death (i.e., the perspective of objectivity vs. the perspective of subjectivity). The perspective of objectivity ( Hanfstingl, 2022 ) emphasizes the importance of impartiality, unbiased interpretation and logical judgment, and the use of facts and verifiable evidence. For example, in terms of “negativity”, poverty, suffering, uncertainty, despair, and confusion ( Zhang, 2003 ; McCartney et al., 2007 ; Mistry et al., 2009 ) are attributes that many of us experience on a daily basis. Natural tendency, in this case, would dictate that one’s personal mindset seeks out opportunities, pathways, means, etc. to help rectify or resolve such negative life experiences. The perspective of subjectivity ( Lundberg et al., 2023 ), in contrast, emphasizes individualism, a person’s own sense of interpretation and point of view, and potentially biased judgment. For example, a person’s feeling and subjective interpretation may give rise to her conviction and insistence that spirit communication ( Buckland, 2004 ), premonition ( Cameron, 1958 ), time–space displacement, and the like are trans-mystical experiences that do not coincide with everyday objective reality. Subjectivity, in this sense, may associate with what we refer to as “subjective rationality” or “subjective rationalization”. It is interesting to note that unlike objectivity, subjective rationality may reflect and/or encompass the uniqueness of what we term as “social and/or cultural mediation”. That particular culture (e.g., Taiwanese culture), in this instance, may convey and/or mediate messages of acceptance, appropriateness, etc. of metaphysical experiences (e.g., premonition).

3.3 Ordinary mindset, trans-mystical mindset, and self-transcendence

An interesting position is that it is plausible to approach the study of metaphysicism and mysticism from a psychological point of view. There are in this sense several notable inquiries relating to the study of life and death education that are somewhat unique but, importantly, we are not able to address and/or answer here. Central to our thesis, as previously mentioned, is the use of philosophical psychology (e.g., the proposition of a trans-mystical mindset) to help normalize and/or to scientize the subject matters of metaphysicism and mysticism. Beyond the scope of our examination and something that is more contentious, perhaps, is the potential study of the epistemic validation of the underlying nature of metaphysicism – that, indeed, there is something mysterious about metaphysical contexts and that these do not coincide with the realm of ordinary boundaries (e.g., that the personal experience of premonition). In a similar vein, this mentioning of the “mystique” of metaphysicism raises several questions for future research to consider:

i. Is it a case of subjective rationalization or subjective rationality – that the perception of mystique of metaphysical contexts is subjective and individual and not universal in terms of rationalization (e.g., that a person’s subjective rationalization of metaphysical contexts does not necessarily hold for another person)?

ii. Is it beyond the scientific confines and/or the scientific rigor of psychology, as a distinct field of research, and that some alternative epistemology is required in order for us to study the complexity of metaphysicism?

iii. Is it a valid discourse for us to suggest that there is scientific credence to study the epistemic validation or invalidation of metaphysicism?

The present study context considers an interesting premise: that psychological understanding, situated within the boundary of realistic objectivity, may help explain the nature of metaphysicism and mysticism. In other words, a trans-mystical mindset, psychological in makeup, may assist a person to accommodate , adapt , resolve , and interpret the intricacies of metaphysical contexts. That indeed, from our considered viewpoint, metaphysical contexts (e.g., a daughter’s experience of spirit communication with her loved ones) do not necessarily differ from daily life contexts (e.g., a teenager’s romantic feeling for his classmate). Individual differences (e.g., a person’s insistence that he has reincarnated), in this sense, are perhaps subjective – that subjective rationalization is prevalent and may serve to attribute to one’s own conviction of a metaphysical experience.

Unlike an ordinary or a normal mindset, a trans-mystical mindset does not simply eventuate. It is not automatic, spontaneous, and/or instantaneous. Rather, the perceived “unknowns” of this world, or a specific unknown context that one may confront at a particular moment in time, may initiate and stimulate a trans-mystical mindset. Our philosophization contends that a trans-mystical mindset reflects a person’s experience of being able to “transcend” herself from an ordinary level of human psyche to an expansive, extraordinary level. More importantly, our embracement of objective rationality indicates that a trans-mystical mindset may add logic, validity, and scientific credence to the study of metaphysical contexts and mystical experiences. In other words, from our point of view, a trans-mystical mindset may serve as a theoretical lens, helping society and individuals to view the subject matters of metaphysicism objectively. That the metaphysical concept of premonition ( Cameron, 1958 ; Dossey, 2009 ) is non-mystical and/or is just a “norm” that some individuals may experience. We rationalize this position by considering an interesting benchmark or a point of equivalency – namely:

That a trans-mystical mindset, as extraordinary and higher-order, may equate to the humanistic state of transcendence .

3.3.1 Point of equivalency for consideration

The underlying account of our rationalization (i.e., a trans-mystical mindset ≈ state of transcendence) is that both a trans-mystical mindset and a state of transcendence are non-ordinary life states and/or non-everyday contexts ( Figure 1 ). For example, a student’s state of self-transcendence is somewhat different from her state of intrinsic motivation for mathematics learning, and/or that the personal context of bushwalking on a Saturday morning does not coincide with a teenager’s trans-mystical mindset. In terms of transcendence, there are numerous theoretical accounts [ Reed’s (1991) Self-Transcendence Theory] within the transpersonal psychology literature, but generally speaking, a popular account is from Maslow (1971) , which states the following:

Transcendence refers to the very highest and most inclusive or holistic levels of human consciousness, behaving and relating, as ends rather than means, to oneself, to significant others, to human beings in general, to other species, to nature, and to the cosmos” (p. 269).

An analysis of Maslow’s (1971) description of transcendence (e.g., self-transcendence) suggests, perhaps, a very concise, direct, and clear explanation (e.g., that a person’s state of self-transcendence indicates his complex state of consciousness…). At a deeper level, however, we note a few notable keywords or phrases that are somewhat complex – for example: “holistic levels of human consciousness”, “ends rather than means”, and “the cosmos”. We contend that these keywords or phrases serve to support our earlier mentioning: that the underlying nature of transcendence, similar to a trans-mystical mindset, is something that is higher-order and that a lay person does not necessarily experience on a daily basis.

There is research development that has, to date, explored the impact of transcendence. For example, a number of researchers have studied the underlying nature of “self-transcendence” ( Conn, 1998 ; Ruschmann, 2011 ; Llanos and Martínez Verduzco, 2022 ), which concerns a person’s ability to transcend beyond her perceived sense of self and, in the process, recognizing that there are elements in life (e.g., nature, social relationship, the universe, divine power, etc.) that constitute the notion of “whole” (e.g., the “wholeness” of a person consist of…). A person’s self-transcendence experience, in this case, showcases her deep understanding and appreciation that there are, perhaps, greater “powers” in life (e.g., a teenager’s perceived spiritual connectedness with God). As such then, this brief theoretical account supports our earlier mentioning regarding the significance and/or the intricacy of a state of self-transcendence: that it is an experience of a higher-order where some of us in society are fortunate or have been fortunate to have encountered.

Again, reiterating our earlier discussion, a state of self-transcendence is higher-order ( Maslow, 1969 , 1971 ) but it does not mean that such encounter and/or experience is mystical in any shape or form. It is a psychological state that we purport may adhere to and/or equate to what we term as “transformation” or the “process of transformation” ( Figure 1 ). Transformation for us, in this case, relates to the “transformation” of a person’s “ordinary” state of consciousness (i.e., ordinary mindset) to a more “complex” state of consciousness (i.e., a trans-mystical mindset). In other words, our conceptualization is as follows:

That transformation of a person’s contextual mindset (i.e., ordinary mindset → trans-mystical mindset) equates to or is analogous to a state of self-transcendence, helping her to rationalize, understand, and/or appreciate the nature of metaphysical contexts, mystical experiences, and the like.

The significance of the aforementioning lies in our attempt to objectively rationalize the nature of metaphysical contexts by equating the concept of a trans-mystical mindset with a state of self-transcendence ( Maslow, 1969 , 1971 ). In this analysis, a trans-mystical mindset is not some unknown, mysterious concept that only a few of us may experience. Rather, equating to a state of self-transcendence, a person’s transformed mindset (i.e., personal mindset → trans-mystical mindset) espouses his intimate sense and/or experience of quality attributes, such as awareness , realization , logical reasoning , acceptance , and enlightenment . As an example, consider a senior citizen who recently encounters a metaphysical life context (e.g., interaction with perceived dark energy of loved ones who have moved on). Such a metaphysical encounter could potentially “transform” the senior citizen’s mindset (i.e., personal mindset → trans-mystical mindset) to assist him to logically rationalize (e.g., he reasons that his experience of spiritual connection is normal), realize (e.g., he realizes that he is able to “sense” a loved one who has moved on nearby), and/or accept (e.g., he accepts that what he is feeling (i.e., sensing a spiritual connection) is normal) that his personal experience of mysticism is normal.

3.4 Innovation and intricacy

Figure 1 encapsulates our conceptualization, showcasing the process of transformation and the two major levels of human existence and/or human psyche (i.e., ordinary (Level 1)  → trans-mystical (Level 2) ). Innovatively and significantly, our conceptualization is intended to support and/or to accentuate our theoretical position: that the subject matters of metaphysicism (e.g., a teenager’s mystical experience) are, in fact, “normal” or that they coincide with the realm of objective rationalization. That we may, in fact, use psychological premises (e.g., the use of philosophical psychology) to decipher, normalize, and scientize the perceived “extraordinary” nature of metaphysical context, mystical experiences, and the like. By all accounts, one may perceive and view the context of premonition ( Cameron, 1958 ; Dossey, 2009 ) as being something that is extraordinary and situates outside or beyond the realm of ordinary boundaries of life and death. This standing, however, emphasizes the importance of subjective experience (e.g., something that is perceived and viewed as being “extraordinary” for one person may not be so for another person). Moreover, such differences in personal experience may make the same belief subjectively rational for one person but not another person. Upon reflection though, we offer an alternative account, which is illustrated here in this section, where we contend that variations in mystical or metaphysical contexts may “cross-reference” with Maslow’s (1969 , 1971) hierarchy of needs framework:

Level 1: an ordinary mindset: Ordinary boundaries of human existence and/or human psyche may give rise to the proposition of a person’s “ordinary mindset”. Ordinary boundaries of human existence and/or human psyche (e.g., a student’s love for mastery of classical music), from our rationalization, coincide with Maslow’s (1968 , 1969) proposition of physiological needs, safety needs, belonging and love needs, and esteem needs. Level 1, from our point of view, is considered as a basic level or a low level of human psyche.

Level 2: a trans-mystical mindset: Extraordinary boundaries of human existence and/or human psyche may give rise to the proposition of a “trans-mystical mindset”. Extraordinary boundaries of human existence and/or human psyche (e.g., a teenager’s perceived ability to transcend to another time–space realm), from our rationalization, coincide with Maslow’s (1968 , 1969) proposition of self-actualization and self-transcendence. Level 2, from our point of view, is considered as a complex level or a higher level of human psyche.

Our philosophization, summarized in Figure 1 , is innovative for its proposition of an active process of transformation of a person’s psychological mindset. That a person’s mindset is contextual ( Phan et al., 2024 ) and changes with reference to a specific context at hand (i.e., Level 1 → L2). Moreover, from our point of view, normalizing and/or scientizing the subject matters of metaphysicism, mysticism, and the like may consist of the equivalency between two higher-order concepts: a trans-mystical mindset ≈ a state of self-transcendence. Variations in human experiences, ranging from ordinary and perceived realistic levels (e.g., one’s personal desire to live a cherished and self-fulfilling life) to extraordinary and perceived complex levels (e.g., one’s personal desire to seek theoretical understanding of the unknowns) may serve to change one’s psychological mindset (i.e., personal mindset → trans-mystical mindset).

4 Importance of antecedents: life wisdom and historical-sociocultural contextualization

Approaching the study of life and death education from a mystical perspective ( Phan et al., 2021 , 2023 ), or from the perspective objectivity vs. subjectivity, is insightful and interesting, as it may help advance theoretical understanding of the subject matters. An important issue for consideration, in this case, relates to one’s inclination to accept or to reject the enigma of the subject of trans-mysticism (e.g., a person’s perceived mystical life experience, such as his ability to transcend to another time–space context). Our attempt over the past few years has involved the use of philosophical analysis to help normalize the subject matter of mystical experiences and metaphysical contexts. That psychological premises, for example, may enable us to scientize the nature of metaphysicism. Interestingly, one of our reviewers recently mentioned a pivotal point, contending that philosophizing the relevance and/or the uniqueness of mystical experiences and metaphysical contexts does necessarily make them any more valid. That a person’s willingness to embrace the subject of trans-mysticism, likewise, may simply reflect and/or indicate his sense of curiosity, interest, etc. and nothing more. If this is the case, then it may be plausible to purport that universal contexts (e.g., the context of mastery and enjoyment of visual arts vs. the context of reincarnation) do not conjecture any “mystique” or “extraordinariness”. A specific life context is only mysterious or extraordinary (e.g., a teenager’s conviction that her personal experience of spiritual connection with a loved one who has moved on), perhaps, from a subjective point of view. Having said this, however, we want to briefly introduce two theoretical concepts that may offer grounding and discount the objective logic, validity, and/or legitimacy of trans-mysticism, metaphysical contexts, and the like:

i. The importance of life wisdom.

ii. The importance of historical-sociocultural contextualization.

To offer a balanced overview and to encourage scholarly dialogues, we have chosen to consider an alternative and/or a related viewpoint: that acquired life wisdom and/or one’s historical-sociocultural upbringing may predominate and support and/or strengthen the perspective of subjective rationality. This viewpoint considers the importance of subjectivity, personal experience and interpretation, and individual differences and contends that perhaps there is something mysterious about the study of metaphysicism. For example, life wisdom is an interesting commodity that may impart contextual epistemological beliefs, expectations, reflective thoughts, and the like. In a similar vein, historical-sociocultural grounding and/or upbringing may cultivate the cultural belief that ancestor worshipping ( Steadman et al., 1996 ; Lakos, 2010 ) enables a person to engage in spirit communication.

4.1 The importance of life wisdom

Life wisdom or life knowledge is somewhat different from contextual subject knowledge (e.g., knowledge of Algebra) as it connotes the importance of “generality”. Situating within the context of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ), life wisdom is defined as:

“A lifelong process that reflects cognitive maturity, diverse life experiences, and the continuation of acquired knowledge of different contexts. A person's wisdom of life, in this sense, is not analogous with his/her intellectual or cognitive development” ( Phan et al., 2021 ).

Unlike specific content knowledge, procedural knowledge, and/or conceptual knowledge (e.g., Algebra), life knowledge, or life wisdom, is somewhat generic and reflects a person’s maturity and diverse life experiences (e.g., a Buddhist nun’s life knowledge of spirituality). Progress in life, in this sense, may coincide with a person’s acquirement and/or development of life knowledge. It is interesting to note life and death education teaching considers the importance of “active transformation” of life wisdom, or life knowledge, into practice for positive and/or effective life functioning ( Phan et al., 2021 , 2023 ). Active transformation, importantly, emphasizes the nexus between theory and practical purposes. In terms of the present context, however, we posit that life wisdom may help to assist a person to view metaphysical contexts and mystical experiences somewhat differently. In other words, resonating with our earlier mentioning, a person’s life wisdom may in fact assist him with his subjective interpretation and rationalization – that, indeed, there is logic to the argument that metaphysical cases of reincarnation, premonition, spirit communication, etc. are extraordinary and situate outside the realm of ordinary boundaries of life and death.

4.2 The importance of historical-sociocultural and ethno-anthropological contextualization

Historical-sociocultural background and upbringing (e.g., a South African child who was born and grows up in Indonesia) may help to shape a person’s epistemological belief, cultural value, customary practice, etc. Extensive research development, to date, has acknowledged the importance of what is known as “sociocultural contextualization” or “situational placement” of one’s learning experiences and personal development ( Wertsch et al., 1995 ; Kozulin, 1999 ; Mahn, 1999 ). There are specific examples, briefly introduced here, that support the potency of historical-sociocultural and ethno-anthropological premises of life and death experiences. That a person’s specific historical-sociocultural upbringing may play a prominent role, helping to convince her that subjective, metaphysical, and extraordinary contexts are perhaps logical. For example, unlike their Western counterparts, Tibetans in general have been brought up from an early age to appreciate the importance of Tibetan Buddhist teaching ( Lama and Chodron, 2019 , Prude, 2019 ), which emphasizes the premise of reincarnation ( Burley, 2014 ; Barua, 2017 ) or the notion of the “birth-death-rebirth” cycle ( Park, 2014 ; Sarao, 2017 ). It is their collective cultural belief perhaps, that upon death, one would reincarnate to a new “being” or a new life. In a similar vein, as we cited earlier, many Taiwanese believe in what is known as an “underworld”, or a place where one could meet and communicate with loved ones who have moved on ( Phan et al., 2021 ). It is interesting to note though, that some Western scholars ( Greber, 1979 ; Buckland, 2004 ; Tymn, 2014 ; Pócs, 2019 ) have also made reference to the notion of “spirit communication”.

The brief accounts, as mentioned here, emphasize the potential relevance and applicability of personal upbringing, grounded in historical-sociocultural contexts. Similar to the case of life wisdom, we posit that historical-sociocultural contexts may support the theoretical lens of subjective rationalization. That a particular historical-sociocultural grounding may instill conviction, personal resolve, and/or firm belief that metaphysical encounters, mystical contexts, and the like are ontologically subjective not rational in perception, interpretation, etc.

5 Summation

In summation, the study of life and death education ( Chen, 2013 ; Huang, 2014 ; Seng and Lee, 2022 ) has established strong grounding for learning, research, and practical purposes. Central to this thesis is a pervasive desire for individuals to appreciate life and death experiences in all different forms. Philosophical, conceptual, and empirical research undertakings have been plentiful, resulting in a myriad of findings and viewpoints for consideration. Our own research inquiries of life and death education over the years, likewise, have provided some interesting findings and insights for continuing teaching and research development. One particular aspect for continuing development relates to the context of universality. Do all of us view, perceive, and/or interpret universal contexts the same or differently? That perhaps, for some of us, life and death contexts are different and exist outside or beyond the ordinary and realistic boundaries of humankind (e.g., a person’s perceived feeling and/or experience of time–space transportation). Indeed, as a recap, we have briefly explored this metaphysical or mystical topic of human agency in a few of our recent articles. This concerted effort has provided preliminary grounding for our proposition of a related psychological concept known as “trans-mysticism”.

The present article considers an interesting discourse: that we may, in fact, subsume and/or frame different subjective viewpoints and interpretations of universal contexts within one common objective, psychological lens. That a resulting trans-mystical mindset, in this case, may help to “objectivize” or scientize the subject matters of metaphysicism, mysticism, and the like. Relating to this proposition is our conceptualization of an equivalency between the process of transformation of an ordinary mindset and a personal state of self-transcendence (i.e., a trans-mystical mindset ≈ a state of self-transcendence). Our philosophization (e.g., situating the concept of a “trans-mystical mindset” within Maslow’s (1968 , 1969) hierarchy of needs framework), in this analysis, is intended to achieve three major feats:

i. To promote the possibility of normalization and acceptance of metaphysical contexts and mystical life and death experiences from the perspective of psychology.

ii. To introduce an alternative nomenclature or psychological concept, known as trans-mysticism, into mainstream trans-humanistic literatures for consideration – for example, a person’s contextual mindset may situate within a hierarchy, transforming from an ordinary level to a higher-order level or a trans-mystical level.

iii. To advance the study of life and death education by considering the legitimacy, logic, and validity of non-conventional or non-objective themes (e.g., the personal experience of premonition).

Overall, then, the focus of our philosophical inquiry raises several notable issues for consideration and/or acknowledgment. That innovatively and creatively, we have utilized psychological premises (e.g., the study of transpersonalism) and the formal teaching and research of life and death education ( Chen, 2013 , Huang, 2014 , Seng and Lee, 2022 ) to normalize and/or to scientize the subject matters of metaphysicism. Equally important is a focus that we briefly mentioned for future development, which seeks to elucidate the epistemic legitimacy or validation of personal conviction and belief that metaphysical contexts and/or mystical experiences are truly unique [e.g., is there something truly unique, objectively, about one’s mystical belief of a metaphysical encounter (e.g., his conviction that spirit communication is unique and does not coincide with everyday objective reality?)].

6 Inquiries for consideration: teaching, educational, and practical purposes

We acknowledge that it is somewhat difficult to conceptualize concretely the concept of trans-mysticism, and/or to convince someone that there is scientific truth to the subject matters of metaphysicism and mysticism. Unlike other theories, concepts, relationships, etc. in the social sciences (e.g., the study of human motivation for effective learning), trans-humanism in its entirety is somewhat abstract, subjective, and individualized, requiring philosophical analysis, reasoned judgment, and contemplation to assist with the attainment of meaningful understanding. In this section of the article, we introduce a few proposed inquiries that may add valuable insights and support our aforementioned proposition for further development.

6.1 Teaching and practical purposes

Quality teaching (e.g., on-campus) and innovative curriculum development, as a whole, is a central element of successful schooling and academic learning experiences. The nexus between research and learning outcomes may involve active transformation of research findings into practice, where possible [e.g., how do we transform the premise of premonition ( Cameron, 1958 , González-González, 2019 ) into positive daily practice?]. Our interest in this matter over the past few years has been to develop a “unifying” framework of life and death education that may take into account different theoretical lenses – psychological , philosophical , sociological , anthropological , etc. Such a unifying framework could, perhaps, help to provide complementary information for holistic understanding of the subject contents of life and death [e.g., a psychological viewpoint (e.g., psychological process of grief) + historical-sociocultural viewpoint (e.g., the Eastern viewpoint about death) of death].

Aside from a unifying framework that incorporates different theoretical lenses, what else can we consider for effective teaching and learning experiences? Consider, in this case, innovative curriculum development that places emphasis on daily relevance and applied educational and non-educational practices. Does a trans-mystical mindset have any practicality for consideration? Can a student utilize her trans-mystical life experience or an encountered metaphysical context to “better” herself and/or others? Is there a program for implementation that an educator could develop, which takes into account the importance of trans-mystical life/death contexts? These sample questions emphasize the importance of practicality or the transformation of theory into practice. To answer such questions, we would need to consider the potential negative perception of the subject matter itself – that:

i. Some or many students, in general, may not appreciate and/or view trans-mystical life/death contexts as a credible subject for studying (e.g., for their future study and/or career pathways).

ii. It is somewhat difficult to associate trans-mystical life/death contexts with everyday relevance and/or applicability.

iii. Some or many students may have differing viewpoints, religious faiths, cultural beliefs, etc. that would prevent them from embracing the subject of trans-mystical life/death contexts.

Mathematics, Biology, Chemistry, Economics, etc. are “hard pure theoretical” disciplines ( Becher, 1989 ; Becher, 1994 ) that are concrete, relatively straightforward in terms of comprehension, processing, and/or understanding, and may reflect daily life relevance. Where does the subject of metaphysical contexts and/or the subject of mystical experiences, in contrast, rank in terms of “intellectual categorization” (e.g., is there any “academic basis” to the study of trans-mysticism?) ( Becher, 1989 , 1994 )? Becher’s (1989 , 1994) framework of intellectual categorizations (e.g., treating the subject content of a trans-mystical mindset as a “soft pure theoretical” subject), in this case, may help to define or redefine the “intellectual rigor” of the subject matters of trans-mysticism, metaphysical contexts, and the like. In a similar vein, the pedagogical practice of theoretical infusion ( Phan et al., 2023 , 2024 ), as described earlier, may lend support and strengthen the perception of intellectual or “academic rigor” to the subject matters of trans-mysticism, metaphysical contexts, and the like. For example, the pedagogical practice of Buddhist infusion ( Yeshe and Rinpoche, 1976 ; Metzner, 1996 ; Master Sheng Yen, 2010 ) may associate trans-mysticism with the subject matter of Buddhist spirituality (e.g., that personal experience and/or feeling of Buddhist spirituality is non-ordinary or extraordinary, reflecting the uniqueness of mysticism), adding valuable academic insights for consideration.

The study of trans-mysticism, in its entirety (e.g., a trans-mystical mindset), may impart some relevant insights for daily life purposes. Daily life relevance, in this case, does not necessarily equate to useful practicalities for positive life functioning. Rather, from our point of view, life relevance arising from in-depth knowledge and personal understanding of trans-mysticism may relate to one’s ability to appreciate and accept the broad “humanistic” nature of life and death. Furthermore, appreciating the concept of trans-mysticism may enable and/or assist a person to recognize that interpretation of life and death can incorporate and involve different theoretical lenses – for example, objective reality vs. individual subjectivity.

6.2 Self-reflection and holistic state of consciousness-subconsciousness

We now turn our attention to another focus of inquiry, which seeks to consider the potential impact of a person’s trans-mystical mindset on her state of personal reflection. Personal reflection , as Schön (1983 , 1987) contends, may espouse two different types: “in-action” reflection (i.e., during the event) and “on-action” reflection (i.e., after the event). This theoretical premise is relevant and may, in fact, relate to the context of our discussion of trans-mysticism. There are a few inquiries that we have formulated for researchers, educators, etc. to consider:

i. Does a trans-mystical mindset coincide with or help a person to develop reflective thinking skills?

ii. Does an encounter with a particular trans-mystical context and/or mystical life/death experience help a person to develop reflective thinking skills?

iii. Can personal reflection assist a person to reason, accept, and/or embrace trans-mystical life/death contexts?

iv. Can reflective thinking serve as an informational source, helping to necessitate, prepare, facilitate, and/or sustain a trans-mystical mindset?

The main issue, from our point of view, is whether trans-mystical mindset and reflective practice are interrelated with each other. In terms of life and death contexts, specifically, we prefer to use the term “self-contemplation” or “personal contemplation” ( Chattopadhyay, 2022 ) over that of self-reflection. For us, self-contemplation is more than just a state of personal reflection of different types of life functioning. Rather, self-contemplation is transpersonal and reflects a person’s concerted introspection to seek deep understanding about life experiences and the true meaning of higher-order life attainments. Moreover, from our point of view, self-contemplation emphasizes the importance of one’s own self-analysis and philosophization about the true meaning of aestheticism and altruism. It would be an interesting endeavor to explore the self-contemplative nature of trans-mysticism. To facilitate this line of questioning, we propose a term that we coin as “trans-mystical contemplation” or “trans-mystical introspection” – for example: does a person’s experience of trans-mysticism (e.g., a person’s conviction and belief that she is able to connect spiritually with loved ones who have moved on) reflect his contemplative or introspective thoughts?

Our recent article introduced a mindfulness-related methodological approach known as “meditative-reflective documentation” ( Phan et al., 2024 ). Meditative-reflective documentation is an approach that encourages a person to document and note down specific phrases, drawings, keywords, etc. that could describe his “meditative-reflective” experience. This theoretical account of meditative-reflective experience contends that in-depth meditation may enable a person to attain and/or to experience a higher-order “meditative-reflective” state – for example, his perceived feeling of “extraordinariness”, such as the perceived feeling of out-of-body experience (e.g., self-awareness of the perception of “disassociation” of body and mind from the present time–space context). As a result of this mentioning, we wonder whether there is credence to consider an interesting proposition: that the totality of a person’s state of consciousness and subconsciousness may consist of a unification or a combination of similar states: a trans-mystical state , a meditative-reflective state , a self-actualizing state , a transcendence state , etc., ( Figure 2 ).

Figure 2 . A proposed holistic state of consciousness-subconsciousness here.

Our seminal idea, as described, considers the possibility that some discourse and/or course of action could act to facilitate the unification of different states of consciousness and subconsciousness (e.g., a trans-mystical state, a meditative-reflective state, a self-actualizing state, and a transcendence state). This unification, we philosophize, may serve to encapsulate the “entirety” of a person’s state of consciousness-subconsciousness. Our narrative, in this case, contends that metaphysical contexts and/or mystical experiences may help initiate, unify, and sustain the four aforementioned states of consciousness-subconsciousness.

6.3 Research development for consideration

In this final section of the article, we discuss a few research propositions that may assist to support our advocation for the study of the entirety of trans-humanism, including the proposed concept of a trans-mystical mindset. We acknowledge that overall, the subject of trans-humanism is abstract, philosophical, and can be somewhat incomprehensible at times, making it difficult for students, individuals, etc. to understand and appreciate. Even more difficult, perhaps, is the development of research undertakings that could in effect help to validate such representation(s). There are a couple of questions, at present, for us to consider:

i. How do we accurately measure and assess the underlying nature of a trans-mystical mindset?

ii. How do we measure, assess, and/or evaluate one’s perceived feeling of a metaphysical context, mystical experience, and the like?

iii. How do we validate the proposition of a holistic state of consciousness-subconsciousness ( Figure 2 ), which may consider the following: a trans-mystical state, a meditative-reflective state, a self-actualizing state, a transcendence state, etc.?

iv. How do we objectively validate, legitimize, and/or confirm that a trans-mystical mindset is unique or that metaphysical experiences are extraordinary and situate outside the realm of ordinary boundaries?

The sample questions above illustrate the complexities of the study of the entirety of trans-humanism. For example, how would we soundly and/or accurately undertake a research inquiry into the nature of a trans-mystical mindset? This question places emphasis on a research-related issue or matter known as “methodological appropriateness” ( Esterberg, 2002 ; Creswell, 2003 ; Creswell, 2008 ). Methodological appropriateness, in brief, relates to the development of an appropriate methodological design for usage that would, in turn, enable a researcher to measure and assess a concept, phenomenon, relationship, etc. adequately and accurately In the social sciences, there are a couple of robust and stringent methodological designs for researchers, educators, students, etc. to consider (e.g., Likert-scale inventories, surveys, open-ended interviews). Likert-scale inventories and/or open-ended surveys are relatively straightforward and, in this case, may offer simple, direct opportunities and/or pathways for the attainment of evidence into the perception of trans-mystical life/death experiences (e.g., I perceive that there is something out there, divine, that I cannot explain…).

An important line of inquiry for consideration entails a comparative analysis of viewpoints, perspectives, interpretations, opinions, etc. of the study of trans-humanism in its entirety. We purport that a “sociocultural-anthropological” approach could offer a more interesting account of perception, interpretation, understanding, etc. of metaphysical contexts, mystical experiences, and the like. A sociocultural-anthropological approach ( Phan et al., 2024 ), we contend, places emphasis on the importance of diverse customary practices, cultural values, epistemological beliefs, protocols, etc. As we mentioned earlier, historical-sociocultural grounding and personal upbringing may play a prominent role, helping to shape or influence a person’s behavior, viewpoint, interpretation, epistemological belief, etc. (e.g., that there is logic and relevance to the cultural practice of ancestor worshipping). In this analysis, research undertakings that place emphasis on ethnographic-anthropological differences or similarities (e.g., the contrasting viewpoints regarding a trans-mystical mindset in reception, belief, and conviction towards the notion of premonition) may lend support for a wider scope in study of perspectives, beliefs, opinions, and ideas of metaphysical contexts, etc.

7 Conclusion

The present conceptual analysis article, we contend, has advanced the study of transpersonalism in its entirety ( Maslow, 1969 ; Strohl, 1998 ; Hartelius et al., 2007 ; Lancaster and Linders, 2019 ) by considering an alternative – namely, the nomenclature “trans-humanism” and, in this case, the philosophized psychological concept of trans-mysticism. Our focus of inquiry, philosophically and theoretically, attempts to analyze the potential relevance and significance of trans-mysticism by situating its nature within the framework of life and death education ( Phan et al., 2021 ; Lei et al., 2022 ; Seng and Lee, 2022 ; Shu et al., 2023 ). Specifically, we purport that metaphysical contexts, mystical experiences, and the like may transform a person’s ordinary mindset to a trans-mystical mindset, helping him to appreciate, rationalize, and make reasoned judgments about the nature of such “extraordinary” encounters.

Overall, then, we contend that our focus of inquiry has added valuable insights for research, teaching, and practical purposes. Central to this thesis is our use of philosophical analysis to normalize and scientize a subject area that is perceived as being somewhat non-conventional. This utilization of personal philosophization has provided grounding for consideration of several interesting endeavors: (i) viewing life and death from contrasting theoretical lenses (e.g., objective reality vs. individual subjectivity), (ii) seeking to engage in higher-order human practices (e.g., meditative-reflection) in order to encounter and/or to experience metaphysical contexts and the like, and (iii) embracing the importance of “normalization” of extraordinary human psyche for daily functioning.

Author contributions

HP: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing. BN: Conceptualization, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing. C-SH: Conceptualization, Investigation, Methodology, Project administration, Resources, Validation, Writing – review & editing. S-CC: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing. LW: Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

HP would like to express his appreciation to the University of New England, Armidale, Australia for allowing him to undertake his sabbatical in late 2022, which led to the preparation and writeup of this article. A special thank you to the National Taipei University of Education and, in particular, the Department of Education for hosting the first author’s sabbatical. Finally, the five authors would like to extend their gratitude and appreciation to the Associate Editor and the two reviewers for their insightful comments, which have helped to enhance the articulation of this conceptual analysis article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: life and death education, trans-mystical mindset, transpersonalism, trans-mysticism, hierarchy of needs, mediative-reflective state, transcendence state, self-actualizing state

Citation: Phan HP, Ngu BH, Hsu C-S, Chen S-C and Wu L (2024) Expanding the scope of “trans-humanism”: situating within the framework of life and death education – the importance of a “trans-mystical mindset”. Front. Psychol . 15:1380665. doi: 10.3389/fpsyg.2024.1380665

Received: 02 February 2024; Accepted: 10 April 2024; Published: 23 April 2024.

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Copyright © 2024 Phan, Ngu, Hsu, Chen and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Huy P. Phan, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Explainable AI in the military domain

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• Volume 26 , article number  29 , ( 2024 )

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Artificial intelligence (AI) has become nearly ubiquitous in modern society, from components of mobile applications to medical support systems, and everything in between. In societally impactful systems imbued with AI, there has been increasing concern related to opaque AI, that is, artificial intelligence where it is unclear how or why certain decisions are reached. This has led to a recent boom in research on “explainable AI” (XAI), or approaches to making AI more explainable and understandable to human users. In the military domain, numerous bodies have argued that autonomous and AI-enabled weapon systems ought not incorporate unexplainable AI, with the International Committee of the Red Cross and the United States Department of Defense both explicitly including explainability as a relevant factor in the development and use of such systems. In this article, I present a cautiously critical assessment of this view, arguing that explainability will be irrelevant for many current and near-future autonomous systems in the military (which do not incorporate any AI), that it will be trivially incorporated into most military systems which do possess AI (as these generally possess simpler AI systems), and that for those systems with genuinely opaque AI, explainability will prove to be of more limited value than one might imagine. In particular, I argue that explainability, while indeed a virtue in design, is a virtue aimed primarily at designers and troubleshooters of AI-enabled systems, but is far less relevant for users and handlers actually deploying these systems. I further argue that human–machine teaming is a far more important element of responsibly using AI for military purposes, adding that explainability may undermine efforts to improve human–machine teamings by creating a prima facie sense that the AI, due to its explainability, may be utilized with little (or less) potential for mistakes. I conclude by clarifying that the arguments are not against XAI in the military, but are instead intended as a caution against over-inflating the value of XAI in this domain, or ignoring the limitations and potential pitfalls of this approach.

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Introduction

Artificial intelligence (AI) is revolutionizing society, and entire industries are being reshaped in the wake of increased automation and artificial governance. However, though “AI has many constructive applications... [i]t is also being used as a weapon of repression and to gain military advantage”. Footnote 1 In fact, most militarized states regard autonomous and AI-enabled systems as pivotal technologies in the fight for supremacy in the global order. Footnote 2 The incorporation of AI into military systems naturally leads to a host of worries concerning responsibility, predictability, safety, and basic tenets of humanity in war. This is especially the case when such systems are opaque, that is, “the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity”. Footnote 3 Opaque AI systems are seen to present unique challenges because they undermine human users’ abilities to fully understand a system, to follow the processes which led to the system’s outputs, and to reliably predict the behaviors of the system. To address these issues, there is a growing body of research on explainable AI (XAI), on “developing approaches to explain and make artificial systems understandable to human stakeholders”. Footnote 4 This is no less true for AI in the military, and both the International Committee of the Red Cross (ICRC) and the United States Department of Defense (US DoD) have picked out explainability as a key factor in the responsible development and use of autonomous and AI-enabled technologies in war. Footnote 5

In this article, I develop a cautiously critical view of the importance of XAI in the military domain. In particular, I argue that while the methodologies, approaches, and overall goals of XAI point toward clear virtues of engineering and design, these virtues are ones which are not as relevant within the context of contemporary military deployments, many of which will likely see increasing use of autonomous weapons. I further argue that a host of autonomous and AI-enabled technologies used for military purposes fall outside the scope of XAI, due to these systems either not incorporating AI at all, or to them incorporating AI systems that are simple or rudimentary enough that explainability will be trivially present. However, we can expect at least some AI systems which are truly opaque, either due to in-principle limitations to their explainability or to practical limitations in humans that make them unexplainable to us (even though they may theoretically be explainable). For these, I argue that while explainability is a virtue, it is one aimed more toward engineers designing such systems or troubleshooting systems which have exhibited novel unwanted behaviors. However, for the military personnel who must deploy and rely on AI-enabled systems, the ways AI systems are teamed with human combatants will far outweigh any value to be had by explainability. Thus, I argue that for AI in the military domain, the key component for responsibly and safely deploying such systems is that these are integrated into well-established and tightly knit human–machine teams, where the human can reliably predict the AI’s behavior and respond accordingly, even when that human does not have a full explanation of the AI’s behavior. In developing this point, I draw analogy between sophisticated AI systems and animals fulfilling combat roles, and likewise, explore human–machine teamings through analogy to human-animal teamings. I conclude that XAI does have a role in military affairs, but maintain that this role is related primarily to the development and troubleshooting of AI systems, and has less role in actual deployments of AI in military contexts.

The arguments are structured as follows. First, I begin (Sect. 2 ) by clarifying a number of key definitional points. With these in place, I examine simple autonomous and AI-enabled systems which are currently in use in the military or will be in the near future (Sect. 3 ). In canvassing such existing and near-future systems, I highlight that XAI plays little role in the military systems of today, due to the relative transparency of AI processes in these systems. Yet though current military systems have simpler or more transparent AI systems, this will not always be the case, and in Sect. 4 I continue by examining the role XAI may play for more distant AI systems in the military. In exploring this, I examine how opaque AI can contribute to unpredictability in systems (Sect. 4.1 ) and I compare the values offered by XAI against those to be gained through a richer implementation of human–machine teaming in the military (Sect. 4.2 ). In these discussions, I emphasize that there are limitations to the practical value of explanations, and highlight that the value will vary depending on where XAI is implemented and for whom. Finally, I conclude (Sect. 5 ) by reiterating that XAI does have value in the military domain, but that this value is not one primarily related to responsible deployments of AI, but rather to responsible innovation and design of these systems and effective troubleshooting of systems which exhibit novel unwanted behaviors.

Autonomous weapons, AI in the military, and explainability

Before beginning any discussion of AI, autonomous weapons, or opaque systems in the military, it is crucial that the exact understanding of these terms be made explicit at the outset, as “underdeveloped or underclarified view[s] can, and most likely will, lead to confusion, error, and much time and effort squandered”. Footnote 6 This is especially the case for emerging technologies, where there are likely to be many competing definitions, each of which holds some merit. This section will thus be devoted to providing brief explications of what I mean in this article by “autonomous weapon system”, “human–machine teaming”, “artificial intelligence”, “opacity”, and “explainable AI”. However, it is worth stressing that I am not arguing for the definitions or understandings provided (as there is reasonable room for disagreement), and instead am merely clarifying the meaning of the terms as they will be used throughout what follows.

Now, as many debates surrounding AI in the military focus on autonomous weapon systems (AWS), we will begin with these. In the past decade and a half, there have been many definitions of AWS provided by scholars, states, and non-governmental organizations. Footnote 7 However, there is increasing acceptance of the definition put forward by both the ICRC and the US DoD, namely that AWS are to be understood as weapon systems that have autonomy in the “critical functions” required for selecting and engaging targets, Footnote 8 and that they can select and engage targets without human intervention. Footnote 9 This definition captures the essential features of autonomous weapon systems, namely that they are autonomous in their core tasks, but it does not imply that such systems possess any sophisticated internal AI programming, nor that they are opaque, unpredictable, or even necessarily lethal. In fact, under this definition, there are many AWS which have been in use around the world for decades, from anti-radiation missiles to close-in weapon systems, as well as many others. Footnote 10

In evaluating the impact of any of these systems, it is also critical to look not just to the capabilities and limitations of the systems themselves, but to also pay heed to how these systems are integrated with humans into cohesive units. This is what is known as human–machine teaming, and pertains to every technology in war. At the upper end, we might think of systems like unmanned aircraft which can carry out complex tasks autonomously, even selecting and engaging targets, but which have humans overseeing them and giving the green light on distinct engagement decisions. In this type of teaming, the human must understand the system, its capabilities and limitations, and the engagement context well enough to competently gauge the reliability of the system and halt it if necessary. But human–machine teamings go all the way down to the lowest tech items in war as well. Recall the words of the Rifleman’s Creed of the United States Marine Corps:

This is my rifle. There are many like it, but this one is mine. My rifle is my best friend. It is my life. I must master it as I must master my life. Without me, my rifle is useless. Without my rifle, I am useless.

For any technological system in war, even a rifle, its capacity to provide advantage is deeply entwined with its integration into capable and reliable human–machine systems (or perhaps human-artifact systems, for simpler things like firearms). More than this, responsible use of any technological system demands that the humans making use of these have a sufficient understanding of the system itself. This is central to human–machine teaming. Footnote 11

Returning to autonomous weapons and artificial intelligence, while it is true that many of the AWS currently in use utilize little to no AI, or have only rudimentary AI systems enabled, this is already and rapidly changing. As such, it is also critical that we are clear about precisely what we mean by “artificial intelligence”. Following some of the pioneers of AI research, we may with our definition “wish to indicate the same scope of intelligence as we see in human action: that in any real situation behavior appropriate to the ends of the system and adaptive to the demands of the environment can occur, within some limits of speed and complexity”, Footnote 12 or that we are “concerned with methods of achieving goals in situations in which the information available has a certain complex character”. Footnote 13 These notions are somewhat vague though, and for the sake of precision I follow (Wang, 2019 ), taking for granted that

[i]ntelligence is the capacity of an information-processing system to adapt to its environment while operating with insufficient knowledge and resources. Footnote 14

The degree to which a military system possesses “AI” will thus be determined by that system’s capacity for adapting to its environment given insufficient data. The more a system is able to accomplish goals and secure gains while operating under such limited conditions, the more strongly we may maintain that it is AI-enabled. And since military systems will, as a rule, usually be operating with limited information and resources, there will be pressure to develop more and more sophisticated AI systems, even when this entails that such systems may by necessity be less transparent or understandable. Which brings us to opacity and the push for explainable AI.

As AI systems become more complex, it becomes increasingly difficult for humans to be able to fully comprehend, understand, or explain how they function. This may be due to simple practical limitations (e.g., the AI makes use of too many interconnected functions and algorithms for a human to feasibly be able to parse the code, even if it is in principle possible) or be the result of genuine barriers to understanding (e.g., the AI makes use of machine learning approaches or deep neural networks which prevent a human from being able to understand the underlying reasoning processes). In such cases, we may consider these systems to be opaque , or to use alternative terminology, we may call such a system “a ‘black box’... a system for which we know the inputs and outputs but can’t see the process by which it turns the former into the latter”. Footnote 15 In the military domain, such “black boxes” would appear to present a uniquely thorny problem, and it is unsurprising that XAI efforts were spearheaded by military researchers, with the growing visibility of this research owing much to projects run by the United States Defense Advanced Research Projects Agency (DARPA). Footnote 16

In order to remedy these difficulties, XAI seeks to “(1) produce more explainable models while maintaining a high level of learning performance (e.g., prediction accuracy), and (2) enable humans to understand, appropriately trust, and effectively manage the emerging generation of artificially intelligent partners”. Footnote 17 More simply, “[t]he purpose of an explainable AI (XAI) system is to make its behavior more intelligible to humans by providing explanations”. Footnote 18 Given the recent boom in research on XAI, a number of approaches and methods have been proposed, Footnote 19 but in general all methodologies will be aiming toward some version of goals 1) and 2) above. In the military domain, this is no different, as those designing and deploying potentially opaque AI systems will always be balancing the military advantages of speed and precision against the moral and legal need to have systems which are both predictable and sufficiently understandable to the combatants making use of these technologies.

As a final point, it is worth making clear that throughout the arguments to come, I am assuming that the actors involved in the development and deployment of AI in the military are (at least) trying to act in good faith and in the spirit of the ethics and laws of war. At a minimum, I assume that such good faith requires efforts to adhere to Article 36 of Geneva Protocol I Additional to the Geneva Conventions, namely that in the development or adoption of a new weapon parties try to “determine whether its employment would, in some or all circumstances, be prohibited by this Protocol or by any other rule of international law”. And following on this, given the assumption of actors acting in good faith, we can further assume that the programming of AI systems in the military domain will in general and by default be set to conservative targeting parameters; i.e., autonomous and AI-enabled systems will be designed so as to aim to minimize false positives in targeting, taking as a cost an expected increase in false negatives. Footnote 20

With this rough definitional groundwork laid, we can now move onto the arguments. However, before doing so, it should again be noted that I am not arguing that any of the above definitions or understandings ought to be considered the definition or in some sense “better than” alternative views. I have opted for definitions in keeping with either a broad selection of scholarship or reflecting the views of central state and non-governmental organizations, but there is merit in probing alternative definitions and their implications. For the purposes of this article, we will move forward with the understandings just sketched, but one may reasonably examine these topics through other lenses as well.

Rudimentary AWS and AI

Advanced militaries have long had access to autonomous weapons and systems enabled with at least rudimentary forms of AI. Importantly, the vast majority of autonomous weapons currently in use are either advanced autonomous munitions or anti-materiel platforms which operate based on rather clear targeting parameters. Footnote 21 For these, the question of explainability is moot, as such systems are in most cases not utilizing AI of any sort. Rather, anti-radiation missiles locate and engage objects emitting radio signatures associated with radar stations and jammers, anti-tank munitions utilize seismic, acoustic, or high-frequency radar to track heavy vehicles and armor, and close-in weapon systems used for missile defense take primarily speed and heading of aircraft as parameters to determine whether or not something is a threat. In these and other similar systems, many of which have been in use for decades, AI is not necessary, and is usually not present (except perhaps for limited purposes). As such, explainability holds no particular relevance for AWS per se . Rather, the critical value is predictability ; if a combatant can reliably predict how an AWS will function in the contexts where they plan to deploy it, then that may suffice for responsibly and safely utilizing such systems. Moreover, if a simpler AWS is predictable, there is no clear reason why the combatant deploying it would need to be able to explain its “actions”. Knowing when it will function correctly and when it won’t, and responding accordingly to that knowledge, will suffice for the ethical and legal use of these systems. Knowing why the system makes certain targeting decisions in certain contexts might help combatants to more quickly grasp the “dos and don’ts” of deploying AWS, but one need not be an engineer or programmer in order to recognize that some battlefield situation is one which is likely to cause an accident. After all, training in the use of weapon systems is meant to teach combatants when such systems will and won’t work, but knowing this does not require the users of those systems to be troubleshooters, repairmen, and designers of those systems as well. At any rate, there are a host of autonomous weapons with no AI, and for these, XAI is not needed.

However, in addition to simpler AWS, we are seeing increasing development toward advanced AI-enabled systems which can operate with far less human oversight, and which can accomplish far more complex tasks. In fact, the major global powers are increasingly locked in what might be seen as an arms race for AI, with Vladimir Putin claiming that “[a]rtificial intelligence is the future... [and] whoever becomes the leader in this sphere will become the ruler of the world”, Xi Xinping adding that “[s]cience and technology has become the main battleground of global power rivalry”. Footnote 22 In response to such positions, the United States has recently announced plans to begin using thousands of new autonomous systems over the next 2 years. Footnote 23

Yet statements on the importance of AI, and even plans to utilize a greater number and variety of AWS do not imply that AI in the military will rapidly be dominated by opaque “black box” systems. Rather, for those current and near-future systems which do have some form of AI (which is only a portion of all autonomous systems in the military), many of these utilize more rudimentary programs which are (likely to be) transparent. And for those with aspects which may be opaque, these often relate to unobjectionable applications of AI. For example, DARPA’s Air Combat Evolution program has made use of many recent breakthroughs in AI research to develop autonomous AI systems capable of effectively engaging in dogfights (close-range air-to-air engagements). In a recent competition, the AlphaDogfight Trials, AI pilots were even able to reliably outperform humans in a number of areas. Footnote 24 These AI systems are highly complex, and due to how they were designed and trained, are almost certain to be opaque with regards to a number of decisions they may make. However, in the arena of air-to-air combat between jet fighters, there is far less likelihood of targeting mistakes or novel unwanted or ethically suspect behaviors developing. Thus, even when opacity comes into the equation, this will not automatically imply that there is a problem, nor that XAI is needed. Explanations may prove useful for a variety of reasons, but their having value does not indicate that their lack speaks against a certain AI system or its deployment to theaters of combat.

Advanced AWS and AI in the military

Rudimentary AWS often possess no AI, and for many of those that do, the AI is simple or straightforward enough to be transparent by default. And for many current AI systems in the military which are opaque, their opacity does not necessarily undermine their ethical or legal permissibility (as the opacity may only impinge on ethically neutral decisions or decisions where mistakes are extremely unlikely by default). However, as AI continues to improve, continues to be applied to a greater array of tasks, and continues to become increasingly complex (and likewise, opaque), it may begin to appear necessary that XAI be treated as a basic requirement for responsibly utilizing AI systems. In this section, I resist this broad conclusion. In particular, I argue that XAI will often be irrelevant to responsible deployments of AI (though it will likely have value at other stages of an AI’s design- and life-cycle), that rich and deeply integrated human–machine teamings present a much stronger method for mitigating the possible negative consequences of opacity, and that XAI may even undermine responsible deployments by serving as a form of “check box” for permissibility and thus reducing the impetus for strong human–machine teams.

Unpredictable AWS and opaque AI

AI systems may be practically opaque in virtue of the sheer number and complexity of (interrelated) functions and algorithms operating in their background. Additionally, autonomous weapons or AI systems which are designed around deep neural networks (or which, more broadly, make use of machine learning for their training) are apt to be in principle opaque due to the fact that a designer or engineer cannot fully track what the system has learned and how it has gone from training inputs and operational data to discrete outputs. Some authors further argue that machine learning not only impacts on the opacity of a system, but will in fact make AI-enabled systems inherently unpredictable as well. Footnote 25 If we return to the definition of intelligence presented in Sect.  2 above, we can see why this may indeed be the case.

Intelligence is the capacity of an information-processing system to adapt to its environment while operating with insufficient knowledge and resources . Footnote 26

If we understand “artificially intelligent” systems in the above manner, it is to be expected that these will have some capacity for acting in ways which we would deem unpredictable. This is because such systems will need to be trained on massive data samplings in order to be at all effective or to be responsibly deployed. However, that training will inevitably not include every possible scenario they may encounter, or at least not include every scenario from every angle, in every environment, in every type of weather, etc. Quite simply, the system will need to be trained to a sufficient degree of robustness, but it will still have to make calls during actual deployments which are made against a backdrop of incomplete information or information which it has not directly encountered during training. In this way, such systems will almost always have some inherent capacity to surprise us, simply because we cannot have trained them for everything, and when they come across some novel scenario (or a previously encountered scenario, but from a new angle), they may act in novel ways. Importantly, this is not to say they must have in situ , or real-time machine learning capabilities, as this can lead to much deeper types of unpredictability and significant challenges for responsibly deploying such systems. Footnote 27 However, systems must be able to, in keeping with the training they have received, act in partially novel ways to achieve goals in not only environments their trainers have foreseen, but also environments and contexts that may involve unanticipated variables. Such adaptive problem solving may moreover sometimes lead to behaviors which we cannot fully predict. At least, this much seems plausible. However, the fact that one cannot fully predict certain behavior does not imply that this behavior is unpredictable (in some troubling sense). To see this, let us consider Holland Michel’s words on predictability presented in a recent report of the United Nations Institute for Disarmament Research (UNIDIR).

All autonomous systems exhibit a degree of inherent operational unpredictability, even if they do not fail or the outcomes of their individual action can be reasonably anticipated. This is because, by design, such systems will navigate situations that the operators cannot anticipate. Consider a fully autonomous drone that maps the interior of a network of tunnels. Even if the drone exhibits a high degree of technical predictability and exceptional reliability, those deploying the drone cannot possibly anticipate exactly what it will encounter inside the tunnels, and therefore they will not know in advance what exact actions the drone will take. Footnote 28

Michel is correct in pointing out that one cannot “know in advance what exact actions the drone will take”, especially when one is considering systems with opaque architectures. However, the same is true of human combatants sent to carry out similar missions. In fact, if we consider fully determinate computer systems, where each input has a clear unique output, it is also the case that for these we cannot know in advance exactly what they will do. This is because we cannot know in advance what they will encounter. But even though we do not know exactly what they will do , we do know what they will do given certain situations . The same is true, though to a lesser degree, for human combatants sent on missions like the one Michel imagines. The question thus should not be whether we can predict what will happen, but rather whether we can predict what will happen given various inputs . For the sake of argument, let us assume that opacity alone undermines our ability to do this, to reliably predict what will happen given particular inputs. Footnote 29 Would XAI greatly improve the situation or remove this element of unpredictability?

In order to answer this, we must first differentiate between systems which are truly autonomous and will be deployed without contemporaneous human oversight of any kind (human off-the-loop), those where the system functions autonomously but can have its decisions overridden by a human (human on-the-loop), and those where a human at least partially controls (some of) the system’s functions and targeting decisions (human in-the-loop). Looking first to off-the-loop AWS and AI-enabled systems, we will see that XAI can have no real role during deployments of these.

If we are envisioning truly autonomous weapon systems imbued with opaque AI, these will be carrying out missions without any contemporaneous human oversight. Footnote 30 Designing these systems to provide intelligible and helpful explanations for every decision taken can greatly facilitate the speedy and effective training of such systems, and in the event that a system makes a mistake or does some novel and unwanted thing, provisioning of its “reasoning” will likewise streamline the troubleshooting process. However, for AI systems operating without human oversight, explanations hold zero value during deployments. More than this, it is not possible to have a useful review of explanations pre-deployment as a sort of “check” on the system’s expected reliability. This is due, first and foremost, to Michel’s concerns about predictability just discussed; an AI system may possess the capacity to provide explanations for its actions, even ex ante , but one cannot know in advance exactly what the system will encounter during deployment, or even if one can know this, one cannot know the precise details of how particular objects or targets will be encountered (the angles of approach, ambient temperatures, visual and other lighting of the objects, etc.). These factors are all apt to be highly relevant for the machine’s decision-making processes, and the only possible sort of explanation that could be given ex ante thus would be an unwieldy listing of factors which may be relevant and may be encountered. Such a list will invariably include too many items to present a useful aid to humans pre-deployment, or it will need to be trimmed and curated, leaving off potential constellations of input data which might impact on the decisions reached. In short, for systems acting without contemporaneous human oversight, explanations before the fact will almost certainly be either too numerous to prove useful or be limited but not fully representative of what the machine may encounter (or some combination of both). And even if these issues can be surmounted, there is the fundamental obstacle that off-the-loop systems have no one to review the decisions while the machine is in operation (though they may before or after deployment). As such, while XAI may improve the pre- or post-deployment development and troubleshooting of such AWS, it will not provide a useful tool for these during deployment .

What of systems where humans are on- or in-the-loop? If humans can override the machine’s decisions or are part of that decision-making process, it would seem that explanations, especially intelligible ones, could help us to more predictably, reliably, and responsibly use such systems. However, before we become too enamored by this possibility, we have a responsibility to grapple with the challenges associated with XAI and the risks it may bring when deploying AI in military contexts. The remainder of this and the following subsection will be devoted to examining some of these risks and challenges.

The first area of potential worry is the design of XAI systems, and whether the explanations provided are actually doing any good for combatants responsible for overseeing AI systems deployed to combat environments. This is a significant area where care is required, as poor explanations or explanations which do not highlight the right factors underpinning the AI’s evaluation are apt to lead to mistakes. For example, Rudin ( 2019 ) presents the case of an AI system tasked with identifying images, and shows how faulty “explanations” may lead to confusion and over- or under-confidence in systems. In point of fact, Rudin’s example centers around an image of a dog and two accompanying heatmaps showing the points the AI found relevant for two separate identifications of the image. Both heatmaps are remarkably similar, but one is explaining what points the AI system found relevant for its assessment of “Evidence for animal being a Siberian husky”, whereas the second shows the points relevant for “Evidence for animal being a transverse flute”. Footnote 31 The similarity of “explanation” for these wildly divergent assessments indicate just how flawed and misleading explanations can be.

This is especially problematic given the tempo of modern warfare and the need for overseers of AI systems to make rapid decisions. If a combatant has seen the AI-enabled system perform well across a variety of contexts, and has always associated the explanations given with something akin to justifications for targeting decisions, then it is entirely possible that flawed explanations may not be easily or reliably noted. More than this, explanations which highlight the wrong elements or do not include the aspects which the AI is apt to misidentify may fail to give combatants any significant opportunity to confidently intervene when necessary. This is not to say that explanations necessarily will be flawed in this way or cannot be done well, but merely to indicate that XAI can create serious risks if executed poorly.

One may hope to mitigate the above worry by including explanations that are richer, or which highlight what factors are included in the explanation, which are excluded, and what weightings are placed on various input data. However, just as explanations which provide too little (or unhelpful) information may cause problems, so too will those which present more than is necessary. First, there is the obvious problem that modern warfare places combatants under increasingly strict time constraints, limiting their ability to engage with lengthy and involved explanations. Moreover, there is the added difficulty that explanations which are rich enough to clarify the underlying problems that may be lurking in the machine’s reasoning processes are likely to be complex, delve into aspects of the system’s programming and training, or require presentation of large amounts of factors (as many details will likely go into every decision made by the AI system). These may prove to demand more of combatants than is reasonable, requiring that deployers of AI systems be trained as computer scientists and engineers, in addition to their training as warfighters. Footnote 32 At any rate, XAI will, by necessity, have to strike a balance between too much and too little in explanations, as either end of the spectrum brings risks of its own.

These are design problems though, and perhaps we can reasonably assume that these will be addressed in time. Even so, the inclusion of XAI during deployments of AI systems is apt to create further obstacles to responsible use of such systems. The primary issue is that the provisioning of rich, intelligible, and informative explanations may give rise to the perception that AI systems may be deployed with more ease or with a possibility of having generally trained users which can reliably and responsibly handle a variety of such systems.

There are two distinct issues at play here. The first is that the presence of XAI may give a perception that humans trained on similar systems (but not the exact system to be deployed) can reliably utilize other systems. The presence of explanations for action, coupled with a humans’ training on AI systems generally, may lead to a belief that one can swap between systems with relative ease. However, opaque systems, even ones which give explanations for their actions, are apt to have many subtle factors which go into each decision. These subtle factors may not always be present in explanations, and are in fact likely to not be present if explanations are compact and simple enough to be usable during combat. As such, understanding these and responding to them will require that handlers of such systems are deeply familiar with the particular systems being deployed . However, XAI may lead to a perception that “one training fits all”, undermining the human–machine teamings necessary for responsible deployment.

Second, on a related point, XAI may also lead to a perception that humans may simply “operate” AI-enabled systems without needing to be teamed with them in a rich way at all. This is because the presence of rich and informative explanations may lead to a belief or general sense that anyone can utilize the system so long as they are engaging with the explanations in a critical and thoughtful manner and understand the system and warfighting context well enough to intervene when the system is going to make a mistake. However, as above, the explanations provided are very unlikely to include all of the subtle factors and cues which underpin a specific engagement decision. Moreover, the ability to grapple with the subtleties of a particular AI system will likely require that a human have somewhat intimate and firsthand knowledge of that system’s functioning. This is likely to only be accessible to humans through their incorporation into rich teamings of humans with machines (ideally, involving cooperative training of both the system and human together). By deploying AI systems which are explainable but are under the purview of those who are uninitiated (or poorly initiated), we would create significant risks for mistake simply in virtue of the fact that “users” of those systems would not possess the relevant knowledge to know which explanations may themselves be suspect, or which might require additional scrutiny.

All of that being said, XAI clearly does have value for military uses of artificial intelligence. However, that value is primarily one related to design and troubleshooting. Knowing the reasons an AI system has for some action can greatly help engineers and programmers in developing systems that are responding correctly to information gathered about their environment, that are giving conservative targeting selections, and that are acting in accordance with the legal and moral requirements of war. In a similar vein, if an AI system makes a mistake during a deployment or begins to display novel and unwanted behaviors, explainability can represent significant value by making the troubleshooting process much quicker, simpler, and more effective; the more clearly an AI system can identify and communicate its reasoning for some action, the better engineers, programmers, and machine trainers can address whatever aspects of its programming or training led it to carry out the unwanted action. These are all ways in which XAI can promote both the development and improvement of AI systems used in the military domain.

However, these are tasks related to the pre- and post-deployment phases, and do not indicate that XAI greatly contributes to the responsible use of AI in discrete military applications. Moreover, the arguments above indicate that XAI will often be irrelevant during engagements, and could even be counter-productive. The core problem is that XAI, if successful, will provide more information to combatants, but it will not necessarily imply that said information is well utilized. More importantly, XAI has no innate or necessary connection to human–machine teaming, given that humans may be paired with systems and given adequate training without necessarily having a deep understanding of exactly why a system does what it does. Moreover, that human–machine teaming is a central factor for responsibly using AI in the military domain, and while it is possible that XAI might supplement these teamings and improve how well combatants can deploy advanced artificial intelligence on the battlefield, critically, such success will depend first and foremost on the teamings themselves, and will, at best, be further aided by XAI, at worst, undermined by it. We should therefore be cautious in our optimism about the benefits of explainability for combatants deploying AI for warfighting purposes.

Human–machine teaming

For autonomous weapons and AI systems which are opaque and potentially unpredictable, explanations may help in designing these systems better or improving those which show faults, but they are unlikely to mitigate the negative effects of opacity and unpredictability during actual military uses of these systems. Moreover, rich and informative explanations may undermine the perceived need for strong human–machine teams, and it is these which are most crucial for reliable, predictable, and responsible uses of AI in the military. In particular, we must ensure that we will have human–machine teams developed from training of AI systems up through their deployments, and with an eye to having dedicated handlers responsible for individual AI-enabled combat systems (or possibly small groups of interlinked systems).

Building on the arguments developed in Wood ( 2023b ), Footnote 33 the first point worth stressing is that for opaque AI systems, we ought to recast our thinking about how we engage with these. In particular, we ought to dispense with the language of humans as “users” of these systems, and instead view humans as “deployers”, or, better yet, “handlers” of AI-enabled systems. Further still, we should conceptualize an AI system’s actions and our impact on them as relevantly analogous not to those of other technical artifacts, but rather to animals’ actions. Footnote 34 The reasons for this are many, but let us briefly canvas the main points.

If we are assuming that actors are acting in good faith, opaque AI systems used in the military will not simply be built and then deployed. Rather, they will undergo extensive training which familiarizes them with the greatest possible array of situations and complicating factors. They will also be tested against a large variety of combat situations, in contexts where certain variables are apt to lead to errors or mistakes. In point of fact, responsible developers will “look for problems as hard as they can and then find solutions ”. Footnote 35 All of this will result in systems which, while still potentially opaque, behave in predictable ways across a large number of contexts. However, despite our ability to generally predict their behavior, that opacity, coupled with the system’s own inbuilt capacity for autonomous action, will mean that AI-enabled systems can act in wholly unpredictable ways. In other words, responsibly developed AI systems will be generally predictable, but capable of acting unpredictably.

This is the same situation for animal combatants used in war. Animals have long been a part of mankind’s warfare, fulfilling a wide variety of roles, Footnote 36 but for the sake of specificity, we may imagine an opaque military AI system as analogous to a combat assault dog. Footnote 37 Such dogs are given extensive training, teamed with a human who understands them extremely well, and put into combat situations to carry out certain tasks that humans cannot, or that humans cannot do as well as the dog could. Importantly, due to the amount and quality of training they receive, as well as the quality of their teaming with a human, combat assault dogs are generally very predictable. Yet even so, they are still autonomous, and can act in novel and sometimes unwanted ways. It is the responsibility of their human handler to recognize situations where the dog is apt to act unpredictability (for whatever reason), and to respond accordingly. And though there is a gap in the law regarding animal combatants, Footnote 38 it is reasonable to hold the handlers responsible in the event that mistakes are made. Footnote 39

Connecting this to the discussion of XAI, human handlers responsible for animal combatants will generally have a strong understanding of when their four-footed friends may be expected to behave normally and when they may be unpredictable. Yet an animal’s mind is not something that can be accessed, and it is not possible for handlers to extricate the exact reasons for their charges’ actions. Quite simply, animals are opaque. This opacity does not mean that they are wholly unpredictable though, nor even that they are generally unpredictable, or prone to unpredictable action at all. But critically, the predictability of an animal combatant has much to do with who is doing the predictions .

Handlers responsible for animals may be extremely reliable predictors of the animals’ actions, while other combatants may have no idea at all. Additionally, one’s general understanding of the underlying reasons for some animal’s actions may also not provide strong predictive reliability. Thus, an animal psychologist may be able to say what drives dogs in general, what reasons they might have for certain actions, and even what may drive particular dogs in combat situations. However, the psychologist looking from the outside is likely to be a far worse predictor of some dog’s actions than its handler would be. And this is apt to be the case even if the psychologist has some deeper understanding of the underlying reasons driving the animal; familiarity and mutual trust simply provide far more than mere explanations ever could. And finally, there is the critical point that not only will handlers know when animals may be unpredictable (in potentially unwanted ways), but also when they will be predictably misbehaved. Predictable misbehavior is a key limitation of where and when autonomous agents, organic or otherwise, may be deployed, and knowing when this is likely is best achieved through rich teamings of humans and other agents. Moreover, provisioning of explanations to individuals who are otherwise unfamiliar with an agent, be it a dog or AI, is unlikely to suddenly impart the necessary general understanding required for responsible deployment of such subordinate agents. To see this, consider an example.

Buddy : I have a dog who I take for a walk every day (his name is Buddy, and he is a good boy). As his owner (and handler) I know him very well, to the point that I can reliably recognize (at least) six distinct forms of sniffing he may exhibit: (1) sniffing to just generally engage with the world, (2) sniffing to find a place to go to the bathroom, (3) sniffing because a lady dog came by recently, (4) sniffing because he thinks there might be food, (5) sniffing because he knows there is food and he is trying to find it before I stop him, and (6) sniffing because there is something disgusting he would like to roll in.

Each of these forms of sniffing is rather distinct and can be easily distinguished from the other. Moreover, the different types of sniffing result in different actions I might or must take. If he is looking for a place to go to the bathroom, I should bring him to a patch of grass. If he is aimlessly looking for food, it may be prudent to put him on the leash (though that is not necessary). If he clearly knows food is near and is trying to find it before I do, I have a responsibility to put him on the leash immediately (some common food items we eat can be lethally poisonous to dogs). At any rate, it is clear that why he is sniffing impacts on what responsibilities I have. Moreover, these types of sniffing make him predictable. However, and critically, he is predictable to me (and my wife). Another individual without deep familiarity with Buddy will simply see a dog sniffing. More than this, I could provide detailed explanations of what each type of sniffing looks like, what they mean, and what responses the human should undertake. However, even these are apt to be unhelpful. After all, his sniffing is a bit faster and more frantic if he’s sniffing because he knows there is food. But to the uninitiated, the natural question is “Faster and more frantic than what ?”. Without knowing him already, without having a baseline of understanding concerning his usual behavior, what markers he presents, and what factors are relevant, the explanation provides little. More than this, there are with certainty a number of visual and other cues which I take note of but which I cannot fully explain myself. In point of fact, humans are opaque, and our opacity means that we cannot fully understand exactly why we sometimes know that certain agents will or won’t act in certain ways. Quite simply, familiarity breeds a sort of understanding that mere explanations cannot capture, and we ignore that to our peril. And this is true whether the familiarity is with an animal or an artifact; every dog owner knows there are things your dog does that your brain subconsciously understands, even if they cannot express in words what it is they are understanding, and every fighter pilot, tanker, or other military professional depending for their lives on a machine has a sort of understanding for that machine, one bred not from textbooks and explanations but from sitting inside the thing and simply gaining an understanding.

Finally, there is the added problem that if XAI is achieved for some (set of) systems, there is a risk that this may perversely lead to less responsible deployments of AI systems. This is because overemphasis on explainability may lead XAI to be seen as a sort of “check box” for permissible use of AI systems. Yet, as argued above, it is possible for systems to be explainable in unhelpful ways, and it is possible that individuals better able to understand explanations may be less competent in actually predicting an autonomous agent’s actions in dynamic environments. Thus, that AWS or military AI-systems are explainable in principle or practice may not imply that operators and handlers can understand the explanations or make reliable predictions based on them. The real efforts need to be in trust and teaming, not in technical accomplishments, and failure to do so can lead to disastrous consequences. As an example, consider the downing of Iran Air Flight 655, one of the deadliest military mistakes related to failures of human–machine teaming.

The crew of the USS Vincennes , a missile cruiser outfitted with a state-of-the-art Aegis combat system, misidentified a civilian airliner as an Iranian F-14, and due to “overconfidence in the abilities of the system, coupled with a poor human–machine interface”, proceeded to engage and down the aircraft, killing the 290 civilians aboard. Footnote 40 While the systems on board the Vincennes were likely practically opaque at that time, there was nothing that would plausibly make them in principle opaque. More than this, it is certainly feasible that they could be made transparent and explainable using the current methods of XAI. But this is besides the point. The downing of Iran Air Flight 655 was not caused by opaque systems or a lack of understanding about the processes built into the Aegis combat system. It was the result of a series of failures in human–machine teaming and in cooperation between various combat units, and simply facilitating better communication between these groups would have allowed one to avoid the incident. Again, the core problem during deployments is not whether a system is explainable, but rather whether the system, explainable or not, is well-integrated into reliable human–machine teams which exhibit reasonable levels of trust and have individuals who know when and when not to rely on the system.

As a final word in this section, I again will stress that XAI does have value. That value is just not on the battlefield, but rather in design and troubleshooting labs. The upshot of this is thus not that we should abandon XAI, but rather that we should be cognizant of the limits of its benefits. If we are not, we may be blinded by an over-hyped research program and fail to recognize the extreme importance of other values (like human–machine teaming). Footnote 41 Moreover, we may find ourselves with an “ethical check box” which allows systems to be deployed to battle even when they have no one who can responsibly handle them or reliably predict their actions.

XAI does have value in the military domain. By making opaque systems explainable, artificially intelligent systems may be more quickly, effectively, and reliably trained, designers may more rapidly remove processes that might lead to error or novel unwanted behavior, and the presence of understandable explanations can greatly streamline troubleshooting efforts when systems do act in unwanted ways. However, it is critical that we also understand that there are limitations to the good that XAI can provide. More than this, we must pay heed to the fact that implementing XAI in certain contexts has the potential to lead to mistakes as well, and that it may undermine the perceived need for highly trained handlers of AI systems who are intimately familiar with the capabilities, limitations, and quirks of reasoning in these systems. XAI can thus help us to more safely, reliably, and responsibly develop and maintain AI systems in the military domain (pre- and post-deployment value), but an uncritical implementation of these approaches across the board brings significant risks as well.

In closing, it is worth stressing that the overall intent of this article has not been to argue that XAI is a good or bad thing in the military, but rather to highlight that its value will be context-dependent and vary depending on who is engaging with the explanations provided. For engineers, designers, and troubleshooters, explanations are almost certain to be beneficial and ought to be incorporated to the greatest extent possible. However, XAI will do little to improve (or detract from) AI systems deployed without contemporaneous human oversight, and for those with a human in- or on-the-loop, XAI may create obstacles to responsible deployment of complex AI systems. Most importantly though, responsible deployments will require, first and foremost, strong human–machine teams where the human acts as a “handler” of the AI and not a “user” or “operator”. In developing such teamings, looking to the analogy of human-animal teams in war provides a useful departure point and can inform us of the sorts of risks and pitfalls that are likely to arise if we treat potentially opaque AI systems as mere artifacts which can be easily understood and predicted provided one has an explanation of its reasoning processes.

Data availability

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Code availability

Scharre ( 2023 , p. 4).

Scharre ( 2023 ) provides extension discussion of the geopolitical battles surrounding AI development and the importance global powers such as the United States, China, and Russia have placed on this technology. See also Horowitz ( 2020 ) and Ding and Dafoe ( 2023 ).

Peters ( 2022 , p. 963).

Langer et al. ( 2021 , p. 1). See also Miller ( 2019 ) and Mittelstadt et al. ( 2019 ).

See, respectively, International Committee of the Red Cross ( 2021a , p. 7), US Department of Defense ( 2023 , pp. 4, 6).

Wood ( 2023a , p. 10).

See Williams ( 2015 ), Boothby ( 2016 ), Altmann and Sauer ( 2017 ), Caron ( 2020 ), Taddeo and Blanchard ( 2022 ) for overviews and taxonomical work. See also Pacholska ( 2024 ) for discussion of subtle differences between certain core definitions from states and non-state actors.

International Committee of the Red Cross ( 2014 , p. 5).

International Committee of the Red Cross ( 2021b , p. 1), US Department of Defense ( 2023 , p. 21).

Boulanin et al. ( 2020 ), International Committee of the Red Cross ( 2021a ), Heller ( 2023 ), Wood ( 2023a ), and Wood ( 2023b ).

Human–machine teaming, the ways it may be pursued, and XAI generally have direct and important implications for the idea of “meaningful human control” (MHC) of AWS, a guiding principle which has become central in many debates on autonomy in military systems. However, though there are clear touch-points between these, the depth and breadth of the discussions of MHC makes it impracticable to explore these within the context of this work. For discussion of MHC at a general level and specifically with regards to AWS, see respectively, e.g., Santoni de Sio and van den Hoven ( 2018 ), Mecacci and Santoni de Sio ( 2019 ), Ekelhof ( 2019 ), Human Rights Watch ( 2016 ), and Bode and Watts ( 2021 ).

Newell and Simon ( 1976 , p. 116).

McCarthy ( 1988 , p. 308). See also Minsky ( 1985 ).

Wang ( 2019 , p. 19). See also Wang ( 1995 ) and the 2020 special issue of the Journal of Artificial General Intelligence dedicated to discussing Wang’s view (Volume 11, Issue 2). For a slightly more technical definition from the law, see the EU AI Act, esp. p. 39.

Michel ( 2020 , p. iii).

Adadi and Berrada ( 2018 , p. 52144). See also Gunning et al. ( 2019 ), Gunning and Aha ( 2019 ), and Gunning et al. ( 2021 ) for discussion specific to the DARPA project on XAI and Michel ( 2020 ) for overarching assessments of explainability and predictability in military systems.

Arrieta et al. ( 2020 , p. 83).

Gunning et al. ( 2019 , p. 1). For the role of social and ethical considerations in XAI methodologies, see, e.g., Miller ( 2019 ), Langer et al. ( 2021 ), and Peters ( 2022 ).

For surveys and taxonomical discussions on the state of the art, see Adadi and Berrada ( 2018 ), Das and Rad ( 2020 ), Arrieta et al. ( 2020 ), Fiok et al. ( 2021 ), Speith ( 2022 ), and Cambria et al. ( 2023 ). See Ross ( 2022 ) for critical remarks on the push for transparency.

Article 50.1 of Additional Protocol I stipulates that “in case of doubt whether a person is a civilian, that person shall be considered to be a civilian”, setting the basic justification for such conservative targeting parameters. Many thanks to Maciej Zając for suggesting this clarification.

Wood ( 2023b , pp. 4–10).

Quotations found in Scharre ( 2023 , p. 9). See Hunter and Bowen ( 2023 ) for critique of the AI hype in the defense domain.

Layton ( 2023 ).

DeMay et al. ( 2022 ), and Scharre ( 2023 , pp. 1–3).

Blanchard and Taddeo ( 2022 ). Note that Blanchard and Taddeo are utilizing a rather stringent definition of AWS, which greatly impacts on their arguments. For fuller discussion of their definition, see Taddeo and Blanchard ( 2022 ).

Wang ( 2019 , p. 19), emphasis added.

This is precisely the objection laid out in Blanchard and Taddeo ( 2022 ). Haugh et al. ( 2018 ) and Verbruggen ( 2022 ) present additional concerns relating to the testing and evaluation of autonomous and AI-enabled systems, and McFarland and Assaad ( 2023 ) discusses the legal challenges in weapons review raised by in situ learning. However, McFarland and Assaad, while indicating a number of complications raised by such online learning, do not argue that this by default or necessity renders such weapons inherently unpredictable or illegal to use. Rather, real-time learning alters the necessary review process for weapons with this capability, making it far more stringent. At any rate, to simplify the arguments developed here, I am assuming AI systems which do not make use of in situ learning.

Michel ( 2020 , p. 5).

Note that this need not necessarily be the case, or may potentially be mitigated through extensive training, testing, and evaluation. For discussion of ways in which training, testing, and evaluation may raise our confidence in opaque systems, see Zając ( unpublished manuscript ).

Some argue that such systems present ethical and legal challenges of their own, given that these necessitate that decisions to potentially kill human beings will be delegated to machines. Going into these debates here is beyond the scope of this article, but it is worth mentioning that there already exist many autonomous systems that can carry out lethal engagements without human oversight. For example, many missile defense systems are designed to intercept both incoming missiles and high-speed aircraft, the latter of which engagements may obviously be lethal. These are, however, routinely not subjected to outcry or objections from AWS critics. This is arguably due to the necessarily defensive nature of such systems, but it highlights that neither complete autonomy nor lethality are at the root of objections to AWS. Nor indeed can the delegation of life-and-death decisions to machines be the essential objection, otherwise these systems would also see this form of critique (which they do not).

Rudin ( 2019 , p. 209). See also Ch. 5 of Michel ( 2020 ) for further discussion of this case and discussion of problems with XAI.

Additional data coupled with the tempo of warfare is also apt to lead to information overload, nullifying any gain had by the explanations themselves. For general discussion of this issue, see, e.g., Buchanan and Kock ( 2001 ) and Phillips-Wren and Adya ( 2020 ).

See also Roff and Danks ( 2018 ) and Baker ( 2022 ) for similar points and analogies.

Now, there are obviously many dis analogies between animals and AI-enabled autonomous systems, but there are deep analogies as well, and ones which are central to the debates here; with sufficient training and testing, both act predictably and reliably; despite that, both can act unpredictably in certain contexts; both are opaque to those handling them; both create possible uncertainties about responsibility for the outcomes brought about by their actions (i.e., who is to be held responsible if something goes wrong); and finally, both occupy an uncertain moral and legal space in warfare. For further discussion of these analogous and disanalogous aspects, see Crootof ( 2018 , pp. 76–78), Wood ( 2023b , pp. 10–12). See also Flemisch et al. ( 2003 ) for useful broader discussion of analogies for autonomous systems.

Wood ( 2023c ).

See Nowrot ( 2015 ).

Though animals have been increasingly phased out of most functions they previously fulfilled, there are still certain animals, dogs in particular, that continue to work alongside human combatants, sometimes in combat roles. See Baker ( 2022 , pp. 16–19).

Crootof ( 2018 , pp. 76–78).

Wood ( 2023b , pp. 11–12).

Galliott ( 2020 , p. 163). See also Sagan ( 1991 , pp. 97–101) and Rogers et al. ( 1992 ).

See Shneiderman ( 2022 ) for extensive elaboration of a similar general point.

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Acknowledgements

I must thank both Steven Umbrello and my wife Anna, both of whom listened to my first idea for this paper and encouraged me to pursue it. I am also deeply indebted to Maciek Zając, who was serving as a co-author for a time. We decided each of our papers would be better off standing alone, with more room to develop their respective ideas, but he helped this come to fruition in significant ways before moving onto his own manuscript, and for that I am very grateful. And finally, I must thank my dog Buddy, who somehow provided me with some of the most insightful thoughts of this article, and who is also a very good boy!

A portion of this work was supported by the Grantová agentura C̆eské republiky (Czech Science Foundation), under Grant # 24-12638I.

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Wood, N.G. Explainable AI in the military domain. Ethics Inf Technol 26 , 29 (2024). https://doi.org/10.1007/s10676-024-09762-w

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Accepted : 15 March 2024

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DOI : https://doi.org/10.1007/s10676-024-09762-w

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