action research case study examples

21 Action Research Examples (In Education)

Action research is an example of qualitative research . It refers to a wide range of evaluative or investigative methods designed to analyze professional practices and take action for improvement.

Commonly used in education, those practices could be related to instructional methods, classroom practices, or school organizational matters.

The creation of action research is attributed to Kurt Lewin , a German-American psychologist also considered to be the father of social psychology.

Gillis and Jackson (2002) offer a very concise definition of action research: “systematic collection and analysis of data for the purpose of taking action and making change” (p.264).

The methods of action research in education include:

• conducting in-class observations
• taking field notes
• surveying or interviewing teachers, administrators, or parents
• using audio and video recordings.

The goal is to identify problematic issues, test possible solutions, or simply carry-out continuous improvement.

There are several steps in action research : identify a problem, design a plan to resolve, implement the plan, evaluate effectiveness, reflect on results, make necessary adjustment and repeat the process.

Action Research Examples

• Digital literacy assessment and training: The school’s IT department conducts a survey on students’ digital literacy skills. Based on the results, a tailored training program is designed for different age groups.
• Library resources utilization study: The school librarian tracks the frequency and type of books checked out by students. The data is then used to curate a more relevant collection and organize reading programs.
• Extracurricular activities and student well-being: A team of teachers and counselors assess the impact of extracurricular activities on student mental health through surveys and interviews. Adjustments are made based on findings.
• Parent-teacher communication channels: The school evaluates the effectiveness of current communication tools (e.g., newsletters, apps) between teachers and parents. Feedback is used to implement a more streamlined system.
• Homework load evaluation: Teachers across grade levels assess the amount and effectiveness of homework given. Adjustments are made to ensure a balance between academic rigor and student well-being.
• Classroom environment and learning: A group of teachers collaborates to study the impact of classroom layouts and decorations on student engagement and comprehension. Changes are made based on the findings.
• Student feedback on curriculum content: High school students are surveyed about the relevance and applicability of their current curriculum. The feedback is then used to make necessary curriculum adjustments.
• Teacher mentoring and support: New teachers are paired with experienced mentors. Both parties provide feedback on the effectiveness of the mentoring program, leading to continuous improvements.
• Assessment of school transportation: The school board evaluates the efficiency and safety of school buses through surveys with students and parents. Necessary changes are implemented based on the results.
• Cultural sensitivity training: After conducting a survey on students’ cultural backgrounds and experiences, the school organizes workshops for teachers to promote a more inclusive classroom environment.
• Environmental initiatives and student involvement: The school’s eco-club assesses the school’s carbon footprint and waste management. They then collaborate with the administration to implement greener practices and raise environmental awareness.
• Working with parents through research: A school’s admin staff conduct focus group sessions with parents to identify top concerns.Those concerns will then be addressed and another session conducted at the end of the school year.
• Peer teaching observations and improvements: Kindergarten teachers observe other teachers handling class transition techniques to share best practices.
• PTA surveys and resultant action: The PTA of a district conducts a survey of members regarding their satisfaction with remote learning classes.The results will be presented to the school board for further action.
• Recording and reflecting: A school administrator takes video recordings of playground behavior and then plays them for the teachers. The teachers work together to formulate a list of 10 playground safety guidelines.
• Pre/post testing of interventions: A school board conducts a district wide evaluation of a STEM program by conducting a pre/post-test of students’ skills in computer programming.
• Focus groups of practitioners : The professional development needs of teachers are determined from structured focus group sessions with teachers and admin.
• School lunch research and intervention: A nutrition expert is hired to evaluate and improve the quality of school lunches.
• School nurse systematic checklist and improvements: The school nurse implements a bathroom cleaning checklist to monitor cleanliness after the results of a recent teacher survey revealed several issues.
• Wearable technologies for pedagogical improvements; Students wear accelerometers attached to their hips to gain a baseline measure of physical activity.The results will identify if any issues exist.
• School counselor reflective practice : The school counselor conducts a student survey on antisocial behavior and then plans a series of workshops for both teachers and parents.

Detailed Examples

1. cooperation and leadership.

A science teacher has noticed that her 9 th grade students do not cooperate with each other when doing group projects. There is a lot of arguing and battles over whose ideas will be followed.

So, she decides to implement a simple action research project on the matter. First, she conducts a structured observation of the students’ behavior during meetings. She also has the students respond to a short questionnaire regarding their notions of leadership.

She then designs a two-week course on group dynamics and leadership styles. The course involves learning about leadership concepts and practices . In another element of the short course, students randomly select a leadership style and then engage in a role-play with other students.

At the end of the two weeks, she has the students work on a group project and conducts the same structured observation as before. She also gives the students a slightly different questionnaire on leadership as it relates to the group.

She plans to analyze the results and present the findings at a teachers’ meeting at the end of the term.

2. Professional Development Needs

Two high-school teachers have been selected to participate in a 1-year project in a third-world country. The project goal is to improve the classroom effectiveness of local teachers. 

The two teachers arrive in the country and begin to plan their action research. First, they decide to conduct a survey of teachers in the nearby communities of the school they are assigned to.

The survey will assess their professional development needs by directly asking the teachers and administrators. After collecting the surveys, they analyze the results by grouping the teachers based on subject matter.

They discover that history and social science teachers would like professional development on integrating smartboards into classroom instruction. Math teachers would like to attend workshops on project-based learning, while chemistry teachers feel that they need equipment more than training.

The two teachers then get started on finding the necessary training experts for the workshops and applying for equipment grants for the science teachers.

3. Playground Accidents

The school nurse has noticed a lot of students coming in after having mild accidents on the playground. She’s not sure if this is just her perception or if there really is an unusual increase this year.  So, she starts pulling data from the records over the last two years. She chooses the months carefully and only selects data from the first three months of each school year.

She creates a chart to make the data more easily understood. Sure enough, there seems to have been a dramatic increase in accidents this year compared to the same period of time from the previous two years.

She shows the data to the principal and teachers at the next meeting. They all agree that a field observation of the playground is needed.

Those observations reveal that the kids are not having accidents on the playground equipment as originally suspected. It turns out that the kids are tripping on the new sod that was installed over the summer.

They examine the sod and observe small gaps between the slabs. Each gap is approximately 1.5 inches wide and nearly two inches deep. The kids are tripping on this gap as they run.

They then discuss possible solutions.

4. Differentiated Learning

Trying to use the same content, methods, and processes for all students is a recipe for failure. This is why modifying each lesson to be flexible is highly recommended. Differentiated learning allows the teacher to adjust their teaching strategy based on all the different personalities and learning styles they see in their classroom.

Of course, differentiated learning should undergo the same rigorous assessment that all teaching techniques go through. So, a third-grade social science teacher asks his students to take a simple quiz on the industrial revolution. Then, he applies differentiated learning to the lesson.

By creating several different learning stations in his classroom, he gives his students a chance to learn about the industrial revolution in a way that captures their interests. The different stations contain: short videos, fact cards, PowerPoints, mini-chapters, and role-plays.

At the end of the lesson, students get to choose how they demonstrate their knowledge. They can take a test, construct a PPT, give an oral presentation, or conduct a simulated TV interview with different characters.

During this last phase of the lesson, the teacher is able to assess if they demonstrate the necessary knowledge and have achieved the defined learning outcomes. This analysis will allow him to make further adjustments to future lessons.

5. Healthy Habits Program

While looking at obesity rates of students, the school board of a large city is shocked by the dramatic increase in the weight of their students over the last five years. After consulting with three companies that specialize in student physical health, they offer the companies an opportunity to prove their value.

So, the board randomly assigns each company to a group of schools. Starting in the next academic year, each company will implement their healthy habits program in 5 middle schools.

Preliminary data is collected at each school at the beginning of the school year. Each and every student is weighed, their resting heart rate, blood pressure and cholesterol are also measured.

After analyzing the data, it is found that the schools assigned to each of the three companies are relatively similar on all of these measures.

At the end of the year, data for students at each school will be collected again. A simple comparison of pre- and post-program measurements will be conducted. The company with the best outcomes will be selected to implement their program city-wide.

Action research is a great way to collect data on a specific issue, implement a change, and then evaluate the effects of that change. It is perhaps the most practical of all types of primary research .

Most likely, the results will be mixed. Some aspects of the change were effective, while other elements were not. That’s okay. This just means that additional modifications to the change plan need to be made, which is usually quite easy to do.

There are many methods that can be utilized, such as surveys, field observations , and program evaluations.

The beauty of action research is based in its utility and flexibility. Just about anyone in a school setting is capable of conducting action research and the information can be incredibly useful.

Aronson, E., & Patnoe, S. (1997). The jigsaw classroom: Building cooperation in the classroom (2nd ed.). New York: Addison Wesley Longman.

Gillis, A., & Jackson, W. (2002). Research Methods for Nurses: Methods and Interpretation . Philadelphia: F.A. Davis Company.

Lewin, K. (1946). Action research and minority problems. Journal of SocialIssues, 2 (4), 34-46.

Macdonald, C. (2012). Understanding participatory action research: A qualitative research methodology option. Canadian Journal of Action Research, 13 , 34-50. https://doi.org/10.33524/cjar.v13i2.37 Mertler, C. A. (2008). Action Research: Teachers as Researchers in the Classroom . London: Sage.

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Positive Punishment Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Dissociation Examples (Psychology)
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 15 Zone of Proximal Development Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ Perception Checking: 15 Examples and Definition

Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

• Chris Drew (PhD) #molongui-disabled-link 25 Positive Punishment Examples
• Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
• Chris Drew (PhD) #molongui-disabled-link 15 Zone of Proximal Development Examples
• Chris Drew (PhD) #molongui-disabled-link Perception Checking: 15 Examples and Definition

2 thoughts on “21 Action Research Examples (In Education)”

Where can I capture this article in a better user-friendly format, since I would like to provide it to my students in a Qualitative Methods course at the University of Prince Edward Island? It is a good article, however, it is visually disjointed in its current format. Thanks, Dr. Frank T. Lavandier

Hi Dr. Lavandier,

I’ve emailed you a word doc copy that you can use and edit with your class.

Best, Chris.

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What is case study research?

Last updated

8 February 2023

Reviewed by

Cathy Heath

Suppose a company receives a spike in the number of customer complaints, or medical experts discover an outbreak of illness affecting children but are not quite sure of the reason. In both cases, carrying out a case study could be the best way to get answers.

Organization

Case studies can be carried out across different disciplines, including education, medicine, sociology, and business.

Most case studies employ qualitative methods, but quantitative methods can also be used. Researchers can then describe, compare, evaluate, and identify patterns or cause-and-effect relationships between the various variables under study. They can then use this knowledge to decide what action to take. 

Another thing to note is that case studies are generally singular in their focus. This means they narrow focus to a particular area, making them highly subjective. You cannot always generalize the results of a case study and apply them to a larger population. However, they are valuable tools to illustrate a principle or develop a thesis.

Analyze case study research

Dovetail streamlines case study research to help you uncover and share actionable insights

• What are the different types of case study designs?

Researchers can choose from a variety of case study designs. The design they choose is dependent on what questions they need to answer, the context of the research environment, how much data they already have, and what resources are available.

Here are the common types of case study design:

Explanatory

An explanatory case study is an initial explanation of the how or why that is behind something. This design is commonly used when studying a real-life phenomenon or event. Once the organization understands the reasons behind a phenomenon, it can then make changes to enhance or eliminate the variables causing it. 

Here is an example: How is co-teaching implemented in elementary schools? The title for a case study of this subject could be “Case Study of the Implementation of Co-Teaching in Elementary Schools.”

Descriptive

An illustrative or descriptive case study helps researchers shed light on an unfamiliar object or subject after a period of time. The case study provides an in-depth review of the issue at hand and adds real-world examples in the area the researcher wants the audience to understand. 

The researcher makes no inferences or causal statements about the object or subject under review. This type of design is often used to understand cultural shifts.

Here is an example: How did people cope with the 2004 Indian Ocean Tsunami? This case study could be titled "A Case Study of the 2004 Indian Ocean Tsunami and its Effect on the Indonesian Population."

Exploratory

Exploratory research is also called a pilot case study. It is usually the first step within a larger research project, often relying on questionnaires and surveys . Researchers use exploratory research to help narrow down their focus, define parameters, draft a specific research question , and/or identify variables in a larger study. This research design usually covers a wider area than others, and focuses on the ‘what’ and ‘who’ of a topic.

Here is an example: How do nutrition and socialization in early childhood affect learning in children? The title of the exploratory study may be “Case Study of the Effects of Nutrition and Socialization on Learning in Early Childhood.”

An intrinsic case study is specifically designed to look at a unique and special phenomenon. At the start of the study, the researcher defines the phenomenon and the uniqueness that differentiates it from others. 

In this case, researchers do not attempt to generalize, compare, or challenge the existing assumptions. Instead, they explore the unique variables to enhance understanding. Here is an example: “Case Study of Volcanic Lightning.”

This design can also be identified as a cumulative case study. It uses information from past studies or observations of groups of people in certain settings as the foundation of the new study. Given that it takes multiple areas into account, it allows for greater generalization than a single case study. 

The researchers also get an in-depth look at a particular subject from different viewpoints.  Here is an example: “Case Study of how PTSD affected Vietnam and Gulf War Veterans Differently Due to Advances in Military Technology.”

Critical instance

A critical case study incorporates both explanatory and intrinsic study designs. It does not have predetermined purposes beyond an investigation of the said subject. It can be used for a deeper explanation of the cause-and-effect relationship. It can also be used to question a common assumption or myth. 

The findings can then be used further to generalize whether they would also apply in a different environment.  Here is an example: “What Effect Does Prolonged Use of Social Media Have on the Mind of American Youth?”

Instrumental

Instrumental research attempts to achieve goals beyond understanding the object at hand. Researchers explore a larger subject through different, separate studies and use the findings to understand its relationship to another subject. This type of design also provides insight into an issue or helps refine a theory. 

For example, you may want to determine if violent behavior in children predisposes them to crime later in life. The focus is on the relationship between children and violent behavior, and why certain children do become violent. Here is an example: “Violence Breeds Violence: Childhood Exposure and Participation in Adult Crime.”

Evaluation case study design is employed to research the effects of a program, policy, or intervention, and assess its effectiveness and impact on future decision-making. 

For example, you might want to see whether children learn times tables quicker through an educational game on their iPad versus a more teacher-led intervention. Here is an example: “An Investigation of the Impact of an iPad Multiplication Game for Primary School Children.” 

• When do you use case studies?

Case studies are ideal when you want to gain a contextual, concrete, or in-depth understanding of a particular subject. It helps you understand the characteristics, implications, and meanings of the subject.

They are also an excellent choice for those writing a thesis or dissertation, as they help keep the project focused on a particular area when resources or time may be too limited to cover a wider one. You may have to conduct several case studies to explore different aspects of the subject in question and understand the problem.

• What are the steps to follow when conducting a case study?

1. Select a case

Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research.

2. Create a theoretical framework

While you will be focusing on a specific detail, the case study design you choose should be linked to existing knowledge on the topic. This prevents it from becoming an isolated description and allows for enhancing the existing information. 

It may expand the current theory by bringing up new ideas or concepts, challenge established assumptions, or exemplify a theory by exploring how it answers the problem at hand. A theoretical framework starts with a literature review of the sources relevant to the topic in focus. This helps in identifying key concepts to guide analysis and interpretation.

3. Collect the data

Case studies are frequently supplemented with qualitative data such as observations, interviews, and a review of both primary and secondary sources such as official records, news articles, and photographs. There may also be quantitative data —this data assists in understanding the case thoroughly.

4. Analyze your case

The results of the research depend on the research design. Most case studies are structured with chapters or topic headings for easy explanation and presentation. Others may be written as narratives to allow researchers to explore various angles of the topic and analyze its meanings and implications.

In all areas, always give a detailed contextual understanding of the case and connect it to the existing theory and literature before discussing how it fits into your problem area.

• What are some case study examples?

What are the best approaches for introducing our product into the Kenyan market?

How does the change in marketing strategy aid in increasing the sales volumes of product Y?

How can teachers enhance student participation in classrooms?

How does poverty affect literacy levels in children?

Case study topics

Case study of product marketing strategies in the Kenyan market

Case study of the effects of a marketing strategy change on product Y sales volumes

Case study of X school teachers that encourage active student participation in the classroom

Case study of the effects of poverty on literacy levels in children

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• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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Qualitative study design: Action research

• Qualitative study design
• Phenomenology
• Grounded theory
• Ethnography
• Narrative inquiry
• Action research
• Case Studies
• Field research
• Focus groups
• Observation
• Surveys & questionnaires
• Study Designs Home

Action research / Participatory Action Research

These methods focus on the emancipation, collaboration and empowerment of the participants. This methodology is appropriate for collaborative research with groups, especially marginalised groups, where there is more flexibility in how the research is conducted and considers feedback from the participants. 

Has three primary characteristics:  

Action oriented, participants are actively involved in the research.

involvement by participants in the research, collaborative process between participant and researcher - empowerment of participants. The participants have more of a say in what is being researched and how they want the research to be conducted.

cycle is iterative so that it is flexible and responsive to a changing situation.  

• Questionnaires
• Oral recordings
• Focus groups,
• Photovoice (use of images or video to capture the local environment / community and to share with others)
• Informal conversations 

Produces knowledge from marginalised people's point of view and can lead to more personalised interventions.  

Provides a voice for people to speak about their issues and the ability to improve their own lives. People take an active role in implementing any actions arising from the research. 

Transforms social reality by linking theory and practice.  

Limitations

Open ended questions are mainly used, and these can be misinterpreted by researcher – data needs to be cross-checked with other sources.

Data ownership between researcher and research participants needs to be negotiated and clearly stated from the beginning of the project.

Ethical considerations with privacy and confidentiality.

This method is not considered scientific as it is more fluid in its gathering of information and is considered an unconventional research method – thus it may not attract much funding.

Example questions

• What is the cultural significance of yarning amongst Aboriginal people?  

Macro Question:

• “What would it take to improve the stability of young people’s living situations?”  

Micro Questions:  

• “What can we do to better engage with accommodation service providers?”  
• “What can we do to improve the service knowledge of young people?”  
• “What can we do to measure stability outcomes for our clients?”  

(Department of Social Services)  

Example studies

• Miller, A., Massey, P. D., Judd, J., Kelly, J., Durrheim, D. N., Clough, A. R., . . . Saggers, S. (2015). Using a participatory action research framework to listen to Aboriginal and Torres Strait Islander people in Australia about pandemic influenza.  Rural and Remote Health , 15(3), 2923-2923.  
• Spinney, A. (2013). Safe from the Start? An Action Research Project on Early Intervention Materials for Children Affected by Domestic and Family Violence. Children & Society, 27(5), 397-405. doi:10.1111/j.1099-0860.2012.00454.x 
• Department of Social Services. (2019).  On PAR  - Using participatory action research to improve early intervention. 
• Liamputtong, P. (2013). Qualitative research methods (4th ed.). South Melbourne: Oxford  University Press. 
• Mills, J., & Birks, M. (2014). Qualitative Methodology: A Practical Guide. Retrieved from https://methods.sagepub.com/book/qualitative-methodology-a-practical-guide doi:10.4135/9781473920163 
• << Previous: Narrative inquiry
• Next: Case Studies >>
• Last Updated: Apr 8, 2024 11:12 AM
• URL: https://deakin.libguides.com/qualitative-study-designs

Frequently asked questions

What’s the difference between action research and a case study.

Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon.

Frequently asked questions: Methodology

Attrition refers to participants leaving a study. It always happens to some extent—for example, in randomized controlled trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Action research is focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. It is less focused on contributing theoretical input, instead producing actionable input.

Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible.

A cycle of inquiry is another name for action research . It is usually visualized in a spiral shape following a series of steps, such as “planning → acting → observing → reflecting.”

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

• Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

Content validity shows you how accurately a test or other measurement method taps  into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalizations —often the goal of quantitative research . As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research .

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones.

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is best used in the following cases:

• If there is no sampling frame available (e.g., people with a rare disease)
• If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
• If the research focuses on a sensitive topic (e.g., extramarital affairs)

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Reproducibility and replicability are related terms.

• Reproducing research entails reanalyzing the existing data in the same manner.
• Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data . 
• A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
• A successful replication shows that the reliability of the results is high.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Purposive and convenience sampling are both sampling methods that are typically used in qualitative data collection.

A convenience sample is drawn from a source that is conveniently accessible to the researcher. Convenience sampling does not distinguish characteristics among the participants. On the other hand, purposive sampling focuses on selecting participants possessing characteristics associated with the research study.

The findings of studies based on either convenience or purposive sampling can only be generalized to the (sub)population from which the sample is drawn, and not to the entire population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection, using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity ,  because it covers all of the other types. You need to have face validity , content validity , and criterion validity to achieve construct validity.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

• Convergent validity : The extent to which your measure corresponds to measures of related constructs
• Discriminant validity : The extent to which your measure is unrelated or negatively related to measures of distinct constructs

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as “people watching” with a purpose.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation).

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

• Open-ended and flexible
• Impossible to answer with “yes” or “no” (questions that start with “why” or “how” are often best)
• Unambiguous, getting straight to the point while still stimulating discussion
• Unbiased and neutral

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when: 

• You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
• You are constrained in terms of time or resources and need to analyze your data quickly and efficiently.
• Your research question depends on strong parity between participants, with environmental conditions held constant.

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

• You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
• Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

• You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions.
• Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
• You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses.
• Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts.

The four most common types of interviews are:

• Structured interviews : The questions are predetermined in both topic and order. 
• Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
• Unstructured interviews : None of the questions are predetermined.
• Focus group interviews : The questions are presented to a group instead of one individual.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

• Inductive generalization : You use observations about a sample to come to a conclusion about the population it came from.
• Statistical generalization: You use specific numbers about samples to make statements about populations.
• Causal reasoning: You make cause-and-effect links between different things.
• Sign reasoning: You make a conclusion about a correlational relationship between different things.
• Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Triangulation can help:

• Reduce research bias that comes from using a single method, theory, or investigator
• Enhance validity by approaching the same topic with different tools
• Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

• It’s time-consuming and labor-intensive, often involving an interdisciplinary team.
• Your results may be inconsistent or even contradictory.

There are four main types of triangulation :

• Data triangulation : Using data from different times, spaces, and people
• Investigator triangulation : Involving multiple researchers in collecting or analyzing data
• Theory triangulation : Using varying theoretical perspectives in your research
• Methodological triangulation : Using different methodologies to approach the same topic

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure. 

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps: 

• First, the author submits the manuscript to the editor.
• Reject the manuscript and send it back to author, or 
• Send it onward to the selected peer reviewer(s) 
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made. 
• Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardization and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Every dataset requires different techniques to clean dirty data , but you need to address these issues in a systematic way. You focus on finding and resolving data points that don’t agree or fit with the rest of your dataset.

These data might be missing values, outliers, duplicate values, incorrectly formatted, or irrelevant. You’ll start with screening and diagnosing your data. Then, you’ll often standardize and accept or remove data to make your dataset consistent and valid.

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimize or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyze, detect, modify, or remove “dirty” data to make your dataset “clean.” Data cleaning is also called data cleansing or data scrubbing.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

In multistage sampling , you can use probability or non-probability sampling methods .

For a probability sample, you have to conduct probability sampling at every stage.

You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

No, the steepness or slope of the line isn’t related to the correlation coefficient value. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes.

To find the slope of the line, you’ll need to perform a regression analysis .

Correlation coefficients always range between -1 and 1.

The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.

The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation.

These are the assumptions your data must meet if you want to use Pearson’s r :

• Both variables are on an interval or ratio level of measurement
• Data from both variables follow normal distributions
• Your data have no outliers
• Your data is from a random or representative sample
• You expect a linear relationship between the two variables

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your sampling methods or criteria for selecting subjects
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Correlation describes an association between variables : when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.

Causation means that changes in one variable brings about changes in the other (i.e., there is a cause-and-effect relationship between variables). The two variables are correlated with each other, and there’s also a causal link between them.

While causation and correlation can exist simultaneously, correlation does not imply causation. In other words, correlation is simply a relationship where A relates to B—but A doesn’t necessarily cause B to happen (or vice versa). Mistaking correlation for causation is a common error and can lead to false cause fallacy .

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

• In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
• In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

• A positive correlation means that both variables change in the same direction.
• A negative correlation means that the variables change in opposite directions.
• A zero correlation means there’s no relationship between the variables.

Random error  is almost always present in scientific studies, even in highly controlled settings. While you can’t eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables .

You can avoid systematic error through careful design of your sampling , data collection , and analysis procedures. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment ; and apply masking (blinding) where possible.

Systematic error is generally a bigger problem in research.

With random error, multiple measurements will tend to cluster around the true value. When you’re collecting data from a large sample , the errors in different directions will cancel each other out.

Systematic errors are much more problematic because they can skew your data away from the true value. This can lead you to false conclusions ( Type I and II errors ) about the relationship between the variables you’re studying.

Random and systematic error are two types of measurement error.

Random error is a chance difference between the observed and true values of something (e.g., a researcher misreading a weighing scale records an incorrect measurement).

Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are).

On graphs, the explanatory variable is conventionally placed on the x-axis, while the response variable is placed on the y-axis.

• If you have quantitative variables , use a scatterplot or a line graph.
• If your response variable is categorical, use a scatterplot or a line graph.
• If your explanatory variable is categorical, use a bar graph.

The term “ explanatory variable ” is sometimes preferred over “ independent variable ” because, in real world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so “explanatory variables” is a more appropriate term.

The difference between explanatory and response variables is simple:

• An explanatory variable is the expected cause, and it explains the results.
• A response variable is the expected effect, and it responds to other variables.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

• A control group that receives a standard treatment, a fake treatment, or no treatment.
• Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

There are 4 main types of extraneous variables :

• Demand characteristics : environmental cues that encourage participants to conform to researchers’ expectations.
• Experimenter effects : unintentional actions by researchers that influence study outcomes.
• Situational variables : environmental variables that alter participants’ behaviors.
• Participant variables : any characteristic or aspect of a participant’s background that could affect study results.

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

• Only requires small samples
• Statistically powerful
• Removes the effects of individual differences on the outcomes

Disadvantages:

• Internal validity threats reduce the likelihood of establishing a direct relationship between variables
• Time-related effects, such as growth, can influence the outcomes
• Carryover effects mean that the specific order of different treatments affect the outcomes

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

• Prevents carryover effects of learning and fatigue.
• Shorter study duration.
• Needs larger samples for high power.
• Uses more resources to recruit participants, administer sessions, cover costs, etc.
• Individual differences may be an alternative explanation for results.

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a dice to randomly assign participants to groups.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomization. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

• It’s caused by the independent variable .
• It influences the dependent variable
• When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered.

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

There are three key steps in systematic sampling :

• Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
• Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
• Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups.

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

• In single-stage sampling , you collect data from every unit within the selected clusters.
• In double-stage sampling , you select a random sample of units from within the clusters.
• In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

The American Community Survey  is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity  as they can use real-world interventions instead of artificial laboratory settings.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference with a true experiment is that the groups are not randomly assigned.

Blinding is important to reduce research bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

• In a single-blind study , only the participants are blinded.
• In a double-blind study , both participants and experimenters are blinded.
• In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalization .

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
• You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

• The type of soda – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

Using careful research design and sampling procedures can help you avoid sampling bias . Oversampling can be used to correct undercoverage bias .

Some common types of sampling bias include self-selection bias , nonresponse bias , undercoverage bias , survivorship bias , pre-screening or advertising bias, and healthy user bias.

Sampling bias is a threat to external validity – it limits the generalizability of your findings to a broader group of people.

A sampling error is the difference between a population parameter and a sample statistic .

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment and situation effect.

The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).

The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Discrete and continuous variables are two types of quantitative variables :

• Discrete variables represent counts (e.g. the number of objects in a collection).
• Continuous variables represent measurable amounts (e.g. water volume or weight).

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

• The  independent variable  is the amount of nutrients added to the crop field.
• The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables .

External validity is the extent to which your results can be generalized to other contexts.

The validity of your experiment depends on your experimental design .

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Action Research vs. Case Study

What's the difference.

Action research and case study are both research methodologies used in social sciences to investigate and understand complex phenomena. However, they differ in their approach and purpose. Action research is a collaborative and participatory approach that involves researchers and practitioners working together to identify and solve practical problems in real-world settings. It aims to bring about positive change and improvement in the context being studied. On the other hand, case study is an in-depth and detailed examination of a particular individual, group, or situation. It focuses on understanding the unique characteristics and dynamics of the case being studied and often involves extensive data collection and analysis. While action research emphasizes practical application and problem-solving, case study emphasizes detailed exploration and understanding of a specific case.

Further Detail

Introduction.

Action research and case study are two widely used research methodologies in various fields. While both approaches aim to gain insights and understanding, they differ in their focus, design, and implementation. This article will explore the attributes of action research and case study, highlighting their similarities and differences.

Action Research

Action research is a participatory approach that involves collaboration between researchers and practitioners to address real-world problems. It emphasizes the active involvement of stakeholders in the research process, aiming to bring about practical change and improvement. Action research typically follows a cyclical process, consisting of planning, action, observation, and reflection.

One of the key attributes of action research is its focus on generating knowledge that is directly applicable to the context in which it is conducted. It aims to bridge the gap between theory and practice by actively involving practitioners in the research process. This participatory nature allows for a deeper understanding of the complexities and nuances of the problem being investigated.

Action research often involves multiple iterations, with each cycle building upon the insights gained from the previous one. This iterative approach allows for continuous learning and adaptation, enabling researchers to refine their interventions and strategies based on the feedback received. It also promotes a sense of ownership and empowerment among the participants, as they actively contribute to the research process.

Furthermore, action research is characterized by its emphasis on collaboration and co-learning. It encourages the exchange of ideas and knowledge between researchers and practitioners, fostering a sense of shared responsibility and collective action. This collaborative approach not only enhances the quality of the research but also increases the likelihood of successful implementation of the findings.

In summary, action research is a participatory and iterative approach that aims to generate practical knowledge through collaboration between researchers and practitioners. It focuses on addressing real-world problems and promoting positive change within specific contexts.

Case study, on the other hand, is an in-depth investigation of a particular phenomenon, event, or individual. It involves the detailed examination of a specific case or cases to gain a comprehensive understanding of the subject under study. Case studies can be conducted using various research methods, such as interviews, observations, and document analysis.

One of the key attributes of case study research is its ability to provide rich and detailed insights into complex phenomena. By focusing on a specific case, researchers can delve deep into the intricacies and unique aspects of the subject, uncovering valuable information that may not be easily captured through other research methods.

Case studies are often used to explore and understand real-life situations in their natural settings. They allow researchers to examine the context and dynamics surrounding the case, providing a holistic view of the phenomenon under investigation. This contextual understanding is crucial for gaining a comprehensive and nuanced understanding of the subject.

Furthermore, case studies are particularly useful when the boundaries between the phenomenon and its context are not clearly defined. They allow for the exploration of complex and multifaceted issues, enabling researchers to capture the interplay of various factors and variables. This holistic approach enhances the validity and reliability of the findings.

Moreover, case studies can be exploratory, descriptive, or explanatory in nature, depending on the research questions and objectives. They can be used to generate hypotheses, provide detailed descriptions, or test theoretical frameworks. This versatility makes case study research applicable in various fields, including psychology, sociology, business, and education.

In summary, case study research is an in-depth investigation of a specific phenomenon, providing rich and detailed insights into complex situations. It focuses on understanding the context and dynamics surrounding the case, allowing for a comprehensive exploration of multifaceted issues.

Similarities

While action research and case study differ in their focus and design, they also share some common attributes. Both approaches aim to gain insights and understanding, albeit through different means. They both involve the collection and analysis of data to inform decision-making and improve practice.

Furthermore, both action research and case study can be conducted in naturalistic settings, allowing for the examination of real-life situations. They both emphasize the importance of context and seek to understand the complexities and nuances of the phenomena under investigation.

Moreover, both methodologies can involve multiple data collection methods, such as interviews, observations, and document analysis. They both require careful planning and design to ensure the validity and reliability of the findings.

Additionally, both action research and case study can contribute to theory development. While action research focuses on generating practical knowledge, it can also inform and contribute to theoretical frameworks. Similarly, case studies can provide empirical evidence that can be used to refine and expand existing theories.

In summary, action research and case study share common attributes, including their aim to gain insights and understanding, their focus on real-life situations, their emphasis on context, their use of multiple data collection methods, and their potential contribution to theory development.

Action research and case study are two distinct research methodologies that offer unique approaches to gaining insights and understanding. Action research emphasizes collaboration, participation, and practical change, while case study focuses on in-depth investigation and contextual understanding. Despite their differences, both approaches contribute to knowledge generation and have the potential to inform theory and practice. Researchers should carefully consider the nature of their research questions and objectives to determine which approach is most suitable for their study.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

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1 What is Action Research for Classroom Teachers?

ESSENTIAL QUESTIONS

• What is the nature of action research?
• How does action research develop in the classroom?
• What models of action research work best for your classroom?
• What are the epistemological, ontological, theoretical underpinnings of action research?

Educational research provides a vast landscape of knowledge on topics related to teaching and learning, curriculum and assessment, students’ cognitive and affective needs, cultural and socio-economic factors of schools, and many other factors considered viable to improving schools. Educational stakeholders rely on research to make informed decisions that ultimately affect the quality of schooling for their students. Accordingly, the purpose of educational research is to engage in disciplined inquiry to generate knowledge on topics significant to the students, teachers, administrators, schools, and other educational stakeholders. Just as the topics of educational research vary, so do the approaches to conducting educational research in the classroom. Your approach to research will be shaped by your context, your professional identity, and paradigm (set of beliefs and assumptions that guide your inquiry). These will all be key factors in how you generate knowledge related to your work as an educator.

Action research is an approach to educational research that is commonly used by educational practitioners and professionals to examine, and ultimately improve, their pedagogy and practice. In this way, action research represents an extension of the reflection and critical self-reflection that an educator employs on a daily basis in their classroom. When students are actively engaged in learning, the classroom can be dynamic and uncertain, demanding the constant attention of the educator. Considering these demands, educators are often only able to engage in reflection that is fleeting, and for the purpose of accommodation, modification, or formative assessment. Action research offers one path to more deliberate, substantial, and critical reflection that can be documented and analyzed to improve an educator’s practice.

Purpose of Action Research

As one of many approaches to educational research, it is important to distinguish the potential purposes of action research in the classroom. This book focuses on action research as a method to enable and support educators in pursuing effective pedagogical practices by transforming the quality of teaching decisions and actions, to subsequently enhance student engagement and learning. Being mindful of this purpose, the following aspects of action research are important to consider as you contemplate and engage with action research methodology in your classroom:

• Action research is a process for improving educational practice. Its methods involve action, evaluation, and reflection. It is a process to gather evidence to implement change in practices.
• Action research is participative and collaborative. It is undertaken by individuals with a common purpose.
• Action research is situation and context-based.
• Action research develops reflection practices based on the interpretations made by participants.
• Knowledge is created through action and application.
• Action research can be based in problem-solving, if the solution to the problem results in the improvement of practice.
• Action research is iterative; plans are created, implemented, revised, then implemented, lending itself to an ongoing process of reflection and revision.
• In action research, findings emerge as action develops and takes place; however, they are not conclusive or absolute, but ongoing (Koshy, 2010, pgs. 1-2).

In thinking about the purpose of action research, it is helpful to situate action research as a distinct paradigm of educational research. I like to think about action research as part of the larger concept of living knowledge. Living knowledge has been characterized as “a quest for life, to understand life and to create… knowledge which is valid for the people with whom I work and for myself” (Swantz, in Reason & Bradbury, 2001, pg. 1). Why should educators care about living knowledge as part of educational research? As mentioned above, action research is meant “to produce practical knowledge that is useful to people in the everyday conduct of their lives and to see that action research is about working towards practical outcomes” (Koshy, 2010, pg. 2). However, it is also about:

creating new forms of understanding, since action without reflection and understanding is blind, just as theory without action is meaningless. The participatory nature of action research makes it only possible with, for and by persons and communities, ideally involving all stakeholders both in the questioning and sense making that informs the research, and in the action, which is its focus. (Reason & Bradbury, 2001, pg. 2)

In an effort to further situate action research as living knowledge, Jean McNiff reminds us that “there is no such ‘thing’ as ‘action research’” (2013, pg. 24). In other words, action research is not static or finished, it defines itself as it proceeds. McNiff’s reminder characterizes action research as action-oriented, and a process that individuals go through to make their learning public to explain how it informs their practice. Action research does not derive its meaning from an abstract idea, or a self-contained discovery – action research’s meaning stems from the way educators negotiate the problems and successes of living and working in the classroom, school, and community.

While we can debate the idea of action research, there are people who are action researchers, and they use the idea of action research to develop principles and theories to guide their practice. Action research, then, refers to an organization of principles that guide action researchers as they act on shared beliefs, commitments, and expectations in their inquiry.

Reflection and the Process of Action Research

When an individual engages in reflection on their actions or experiences, it is typically for the purpose of better understanding those experiences, or the consequences of those actions to improve related action and experiences in the future. Reflection in this way develops knowledge around these actions and experiences to help us better regulate those actions in the future. The reflective process generates new knowledge regularly for classroom teachers and informs their classroom actions.

Unfortunately, the knowledge generated by educators through the reflective process is not always prioritized among the other sources of knowledge educators are expected to utilize in the classroom. Educators are expected to draw upon formal types of knowledge, such as textbooks, content standards, teaching standards, district curriculum and behavioral programs, etc., to gain new knowledge and make decisions in the classroom. While these forms of knowledge are important, the reflective knowledge that educators generate through their pedagogy is the amalgamation of these types of knowledge enacted in the classroom. Therefore, reflective knowledge is uniquely developed based on the action and implementation of an educator’s pedagogy in the classroom. Action research offers a way to formalize the knowledge generated by educators so that it can be utilized and disseminated throughout the teaching profession.

Research is concerned with the generation of knowledge, and typically creating knowledge related to a concept, idea, phenomenon, or topic. Action research generates knowledge around inquiry in practical educational contexts. Action research allows educators to learn through their actions with the purpose of developing personally or professionally. Due to its participatory nature, the process of action research is also distinct in educational research. There are many models for how the action research process takes shape. I will share a few of those here. Each model utilizes the following processes to some extent:

• Plan a change;
• Take action to enact the change;
• Observe the process and consequences of the change;
• Reflect on the process and consequences;
• Act, observe, & reflect again and so on.

Figure 1.1 Basic action research cycle

There are many other models that supplement the basic process of action research with other aspects of the research process to consider. For example, figure 1.2 illustrates a spiral model of action research proposed by Kemmis and McTaggart (2004). The spiral model emphasizes the cyclical process that moves beyond the initial plan for change. The spiral model also emphasizes revisiting the initial plan and revising based on the initial cycle of research:

Figure 1.2 Interpretation of action research spiral, Kemmis and McTaggart (2004, p. 595)

Other models of action research reorganize the process to emphasize the distinct ways knowledge takes shape in the reflection process. O’Leary’s (2004, p. 141) model, for example, recognizes that the research may take shape in the classroom as knowledge emerges from the teacher’s observations. O’Leary highlights the need for action research to be focused on situational understanding and implementation of action, initiated organically from real-time issues:

Figure 1.3 Interpretation of O’Leary’s cycles of research, O’Leary (2000, p. 141)

Lastly, Macintyre’s (2000, p. 1) model, offers a different characterization of the action research process. Macintyre emphasizes a messier process of research with the initial reflections and conclusions as the benchmarks for guiding the research process. Macintyre emphasizes the flexibility in planning, acting, and observing stages to allow the process to be naturalistic. Our interpretation of Macintyre process is below:

Figure 1.4 Interpretation of the action research cycle, Macintyre (2000, p. 1)

We believe it is important to prioritize the flexibility of the process, and encourage you to only use these models as basic guides for your process. Your process may look similar, or you may diverge from these models as you better understand your students, context, and data.

Definitions of Action Research and Examples

At this point, it may be helpful for readers to have a working definition of action research and some examples to illustrate the methodology in the classroom. Bassey (1998, p. 93) offers a very practical definition and describes “action research as an inquiry which is carried out in order to understand, to evaluate and then to change, in order to improve educational practice.” Cohen and Manion (1994, p. 192) situate action research differently, and describe action research as emergent, writing:

essentially an on-the-spot procedure designed to deal with a concrete problem located in an immediate situation. This means that ideally, the step-by-step process is constantly monitored over varying periods of time and by a variety of mechanisms (questionnaires, diaries, interviews and case studies, for example) so that the ensuing feedback may be translated into modifications, adjustment, directional changes, redefinitions, as necessary, so as to bring about lasting benefit to the ongoing process itself rather than to some future occasion.

Lastly, Koshy (2010, p. 9) describes action research as:

a constructive inquiry, during which the researcher constructs his or her knowledge of specific issues through planning, acting, evaluating, refining and learning from the experience. It is a continuous learning process in which the researcher learns and also shares the newly generated knowledge with those who may benefit from it.

These definitions highlight the distinct features of action research and emphasize the purposeful intent of action researchers to improve, refine, reform, and problem-solve issues in their educational context. To better understand the distinctness of action research, these are some examples of action research topics:

Examples of Action Research Topics

• Flexible seating in 4th grade classroom to increase effective collaborative learning.
• Structured homework protocols for increasing student achievement.
• Developing a system of formative feedback for 8th grade writing.
• Using music to stimulate creative writing.
• Weekly brown bag lunch sessions to improve responses to PD from staff.
• Using exercise balls as chairs for better classroom management.

Action Research in Theory

Action research-based inquiry in educational contexts and classrooms involves distinct participants – students, teachers, and other educational stakeholders within the system. All of these participants are engaged in activities to benefit the students, and subsequently society as a whole. Action research contributes to these activities and potentially enhances the participants’ roles in the education system. Participants’ roles are enhanced based on two underlying principles:

• communities, schools, and classrooms are sites of socially mediated actions, and action research provides a greater understanding of self and new knowledge of how to negotiate these socially mediated environments;
• communities, schools, and classrooms are part of social systems in which humans interact with many cultural tools, and action research provides a basis to construct and analyze these interactions.

In our quest for knowledge and understanding, we have consistently analyzed human experience over time and have distinguished between types of reality. Humans have constantly sought “facts” and “truth” about reality that can be empirically demonstrated or observed.

Social systems are based on beliefs, and generally, beliefs about what will benefit the greatest amount of people in that society. Beliefs, and more specifically the rationale or support for beliefs, are not always easy to demonstrate or observe as part of our reality. Take the example of an English Language Arts teacher who prioritizes argumentative writing in her class. She believes that argumentative writing demonstrates the mechanics of writing best among types of writing, while also providing students a skill they will need as citizens and professionals. While we can observe the students writing, and we can assess their ability to develop a written argument, it is difficult to observe the students’ understanding of argumentative writing and its purpose in their future. This relates to the teacher’s beliefs about argumentative writing; we cannot observe the real value of the teaching of argumentative writing. The teacher’s rationale and beliefs about teaching argumentative writing are bound to the social system and the skills their students will need to be active parts of that system. Therefore, our goal through action research is to demonstrate the best ways to teach argumentative writing to help all participants understand its value as part of a social system.

The knowledge that is conveyed in a classroom is bound to, and justified by, a social system. A postmodernist approach to understanding our world seeks knowledge within a social system, which is directly opposed to the empirical or positivist approach which demands evidence based on logic or science as rationale for beliefs. Action research does not rely on a positivist viewpoint to develop evidence and conclusions as part of the research process. Action research offers a postmodernist stance to epistemology (theory of knowledge) and supports developing questions and new inquiries during the research process. In this way action research is an emergent process that allows beliefs and decisions to be negotiated as reality and meaning are being constructed in the socially mediated space of the classroom.

Theorizing Action Research for the Classroom

All research, at its core, is for the purpose of generating new knowledge and contributing to the knowledge base of educational research. Action researchers in the classroom want to explore methods of improving their pedagogy and practice. The starting place of their inquiry stems from their pedagogy and practice, so by nature the knowledge created from their inquiry is often contextually specific to their classroom, school, or community. Therefore, we should examine the theoretical underpinnings of action research for the classroom. It is important to connect action research conceptually to experience; for example, Levin and Greenwood (2001, p. 105) make these connections:

• Action research is context bound and addresses real life problems.
• Action research is inquiry where participants and researchers cogenerate knowledge through collaborative communicative processes in which all participants’ contributions are taken seriously.
• The meanings constructed in the inquiry process lead to social action or these reflections and action lead to the construction of new meanings.
• The credibility/validity of action research knowledge is measured according to whether the actions that arise from it solve problems (workability) and increase participants’ control over their own situation.

Educators who engage in action research will generate new knowledge and beliefs based on their experiences in the classroom. Let us emphasize that these are all important to you and your work, as both an educator and researcher. It is these experiences, beliefs, and theories that are often discounted when more official forms of knowledge (e.g., textbooks, curriculum standards, districts standards) are prioritized. These beliefs and theories based on experiences should be valued and explored further, and this is one of the primary purposes of action research in the classroom. These beliefs and theories should be valued because they were meaningful aspects of knowledge constructed from teachers’ experiences. Developing meaning and knowledge in this way forms the basis of constructivist ideology, just as teachers often try to get their students to construct their own meanings and understandings when experiencing new ideas.  

Classroom Teachers Constructing their Own Knowledge

Most of you are probably at least minimally familiar with constructivism, or the process of constructing knowledge. However, what is constructivism precisely, for the purposes of action research? Many scholars have theorized constructivism and have identified two key attributes (Koshy, 2010; von Glasersfeld, 1987):

• Knowledge is not passively received, but actively developed through an individual’s cognition;
• Human cognition is adaptive and finds purpose in organizing the new experiences of the world, instead of settling for absolute or objective truth.

Considering these two attributes, constructivism is distinct from conventional knowledge formation because people can develop a theory of knowledge that orders and organizes the world based on their experiences, instead of an objective or neutral reality. When individuals construct knowledge, there are interactions between an individual and their environment where communication, negotiation and meaning-making are collectively developing knowledge. For most educators, constructivism may be a natural inclination of their pedagogy. Action researchers have a similar relationship to constructivism because they are actively engaged in a process of constructing knowledge. However, their constructions may be more formal and based on the data they collect in the research process. Action researchers also are engaged in the meaning making process, making interpretations from their data. These aspects of the action research process situate them in the constructivist ideology. Just like constructivist educators, action researchers’ constructions of knowledge will be affected by their individual and professional ideas and values, as well as the ecological context in which they work (Biesta & Tedder, 2006). The relations between constructivist inquiry and action research is important, as Lincoln (2001, p. 130) states:

much of the epistemological, ontological, and axiological belief systems are the same or similar, and methodologically, constructivists and action researchers work in similar ways, relying on qualitative methods in face-to-face work, while buttressing information, data and background with quantitative method work when necessary or useful.

While there are many links between action research and educators in the classroom, constructivism offers the most familiar and practical threads to bind the beliefs of educators and action researchers.  

Epistemology, Ontology, and Action Research

It is also important for educators to consider the philosophical stances related to action research to better situate it with their beliefs and reality. When researchers make decisions about the methodology they intend to use, they will consider their ontological and epistemological stances. It is vital that researchers clearly distinguish their philosophical stances and understand the implications of their stance in the research process, especially when collecting and analyzing their data. In what follows, we will discuss ontological and epistemological stances in relation to action research methodology.

Ontology, or the theory of being, is concerned with the claims or assumptions we make about ourselves within our social reality – what do we think exists, what does it look like, what entities are involved and how do these entities interact with each other (Blaikie, 2007). In relation to the discussion of constructivism, generally action researchers would consider their educational reality as socially constructed. Social construction of reality happens when individuals interact in a social system. Meaningful construction of concepts and representations of reality develop through an individual’s interpretations of others’ actions. These interpretations become agreed upon by members of a social system and become part of social fabric, reproduced as knowledge and beliefs to develop assumptions about reality. Researchers develop meaningful constructions based on their experiences and through communication. Educators as action researchers will be examining the socially constructed reality of schools. In the United States, many of our concepts, knowledge, and beliefs about schooling have been socially constructed over the last hundred years. For example, a group of teachers may look at why fewer female students enroll in upper-level science courses at their school. This question deals directly with the social construction of gender and specifically what careers females have been conditioned to pursue. We know this is a social construction in some school social systems because in other parts of the world, or even the United States, there are schools that have more females enrolled in upper level science courses than male students. Therefore, the educators conducting the research have to recognize the socially constructed reality of their school and consider this reality throughout the research process. Action researchers will use methods of data collection that support their ontological stance and clarify their theoretical stance throughout the research process.

Koshy (2010, p. 23-24) offers another example of addressing the ontological challenges in the classroom:

A teacher who was concerned with increasing her pupils’ motivation and enthusiasm for learning decided to introduce learning diaries which the children could take home. They were invited to record their reactions to the day’s lessons and what they had learnt. The teacher reported in her field diary that the learning diaries stimulated the children’s interest in her lessons, increased their capacity to learn, and generally improved their level of participation in lessons. The challenge for the teacher here is in the analysis and interpretation of the multiplicity of factors accompanying the use of diaries. The diaries were taken home so the entries may have been influenced by discussions with parents. Another possibility is that children felt the need to please their teacher. Another possible influence was that their increased motivation was as a result of the difference in style of teaching which included more discussions in the classroom based on the entries in the dairies.

Here you can see the challenge for the action researcher is working in a social context with multiple factors, values, and experiences that were outside of the teacher’s control. The teacher was only responsible for introducing the diaries as a new style of learning. The students’ engagement and interactions with this new style of learning were all based upon their socially constructed notions of learning inside and outside of the classroom. A researcher with a positivist ontological stance would not consider these factors, and instead might simply conclude that the dairies increased motivation and interest in the topic, as a result of introducing the diaries as a learning strategy.

Epistemology, or the theory of knowledge, signifies a philosophical view of what counts as knowledge – it justifies what is possible to be known and what criteria distinguishes knowledge from beliefs (Blaikie, 1993). Positivist researchers, for example, consider knowledge to be certain and discovered through scientific processes. Action researchers collect data that is more subjective and examine personal experience, insights, and beliefs.

Action researchers utilize interpretation as a means for knowledge creation. Action researchers have many epistemologies to choose from as means of situating the types of knowledge they will generate by interpreting the data from their research. For example, Koro-Ljungberg et al., (2009) identified several common epistemologies in their article that examined epistemological awareness in qualitative educational research, such as: objectivism, subjectivism, constructionism, contextualism, social epistemology, feminist epistemology, idealism, naturalized epistemology, externalism, relativism, skepticism, and pluralism. All of these epistemological stances have implications for the research process, especially data collection and analysis. Please see the table on pages 689-90, linked below for a sketch of these potential implications:

Again, Koshy (2010, p. 24) provides an excellent example to illustrate the epistemological challenges within action research:

A teacher of 11-year-old children decided to carry out an action research project which involved a change in style in teaching mathematics. Instead of giving children mathematical tasks displaying the subject as abstract principles, she made links with other subjects which she believed would encourage children to see mathematics as a discipline that could improve their understanding of the environment and historic events. At the conclusion of the project, the teacher reported that applicable mathematics generated greater enthusiasm and understanding of the subject.

The educator/researcher engaged in action research-based inquiry to improve an aspect of her pedagogy. She generated knowledge that indicated she had improved her students’ understanding of mathematics by integrating it with other subjects – specifically in the social and ecological context of her classroom, school, and community. She valued constructivism and students generating their own understanding of mathematics based on related topics in other subjects. Action researchers working in a social context do not generate certain knowledge, but knowledge that emerges and can be observed and researched again, building upon their knowledge each time.

Researcher Positionality in Action Research

In this first chapter, we have discussed a lot about the role of experiences in sparking the research process in the classroom. Your experiences as an educator will shape how you approach action research in your classroom. Your experiences as a person in general will also shape how you create knowledge from your research process. In particular, your experiences will shape how you make meaning from your findings. It is important to be clear about your experiences when developing your methodology too. This is referred to as researcher positionality. Maher and Tetreault (1993, p. 118) define positionality as:

Gender, race, class, and other aspects of our identities are markers of relational positions rather than essential qualities. Knowledge is valid when it includes an acknowledgment of the knower’s specific position in any context, because changing contextual and relational factors are crucial for defining identities and our knowledge in any given situation.

By presenting your positionality in the research process, you are signifying the type of socially constructed, and other types of, knowledge you will be using to make sense of the data. As Maher and Tetreault explain, this increases the trustworthiness of your conclusions about the data. This would not be possible with a positivist ontology. We will discuss positionality more in chapter 6, but we wanted to connect it to the overall theoretical underpinnings of action research.

Advantages of Engaging in Action Research in the Classroom

In the following chapters, we will discuss how action research takes shape in your classroom, and we wanted to briefly summarize the key advantages to action research methodology over other types of research methodology. As Koshy (2010, p. 25) notes, action research provides useful methodology for school and classroom research because:

Advantages of Action Research for the Classroom

• research can be set within a specific context or situation;
• researchers can be participants – they don’t have to be distant and detached from the situation;
• it involves continuous evaluation and modifications can be made easily as the project progresses;
• there are opportunities for theory to emerge from the research rather than always follow a previously formulated theory;
• the study can lead to open-ended outcomes;
• through action research, a researcher can bring a story to life.

Action Research Copyright © by J. Spencer Clark; Suzanne Porath; Julie Thiele; and Morgan Jobe is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Home » Education » Difference Between Action Research and Case Study

Difference Between Action Research and Case Study

Main difference – action research vs case study.

Research is the careful study of a given field or problem in order to discover new facts or principles. Action research and case study are two types of research, which are mainly used in the field of social sciences and humanities. The main difference between action research and case study is their purpose; an action research study aims to solve an immediate problem whereas a case study aims to provide an in-depth analysis of a situation or case over a long period of time.

1. What is Action Research?      – Definition, Features, Purpose, Process

2. What is Case Study?      – Definition, Features, Purpose, Process

What is Action Research

Action research is a type of a research study that is initiated to solve an immediate problem. It may involve a variety of analytical, investigative and evaluative research methods designed to diagnose and solve problems. It has been defined as “a disciplined process of inquiry conducted by and for those taking the action. The primary reason for engaging in action research is to assist the “actor” in improving and/or refining his or her actions” (Sagor, 2000). This type of research is typically used in the field of education. Action research studies are generally conductors by educators, who also act as participants.

Here, an individual researcher or a group of researchers identify a problem, examine its causes and try to arrive at a solution to the problem. The action research process is as follows.

Action Research Process

• Identify a problem to research
• Clarify theories
• Identify research questions
• Collect data on the problem
• Organise, analyse, and interpret the data
• Create a plan to address the problem
• Implement the above-mentioned plan
• Evaluate the results of the actions taken

The above process will keep repeating. Action research is also known as cycle of inquiry or cycle of action since it follows a specific process that is repeated over time.

What is a Case Study

A case study is basically an in-depth examination of a particular event, situation or an individual. It is a type of research that is designed to explore and understand complex issues; however, it involves detailed contextual analysis of only a limited number of events or situations. It has been defined as “an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used.” (Yin, 1984)

Case studies are used in a variety of fields, but fields like sociology and education seem to use them the most. They can be used to probe into community-based problems such as illiteracy, unemployment, poverty, and drug addiction. 

Case studies involve both quantitative and qualitative data and allow the researchers to see beyond statistical results and understand human conditions. Furthermore, case studies can be classified into three categories, known as exploratory, descriptive and explanatory case studies.

However, case studies are also criticised since the study of a limited number of events or cases cannot easily establish generality or reliability of the findings. The process of a case study is generally as follows:

Case Study Process

• Identifying and defining the research questions
• Selecting the cases and deciding techniques for data collection and analysis
• Collecting data in the field
• Evaluating and analysing the data
• Preparing the report

Action Research : Action research is a type of a research study that is initiated to solve an immediate problem.

Case Study : Case study is an in-depth analysis of a particular event or case over a long period of time.                         

Action Research : Action research involves solving a problem.

Case Study : Case studies involve observing and analysing a situation.

Action Research : Action research studies are mainly used in the field of education.

Case Study : Case studies are used in many fields; they can be specially used with community problems such as unemployment, poverty, etc.

Action Research : Action research always involve providing a solution to a problem.

Case Study : Case studies do not provide a solution to a problem.

Participants

Action Research : Researchers can also act as participants of the research.

Case Study : Researchers generally don’t take part in the research study.

Zainal, Zaidah.  Case study as a research method . N.p.: n.p., 7 June 2007. PDF.

 Soy, Susan K. (1997).  The case study as a research method . Unpublished paper, University of Texas at Austin.

Sagor, Richard.  Guiding school improvement with action research . Ascd, 2000.

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Case Study With a Participatory Approach: Rethinking Pragmatics of Stakeholder Engagement for Implementation Research

Catherine hudon.

1 Department of Family Medicine and Emergency Medicine, University of Sherbrooke, Sherbrooke, Quebec, Canada

Maud-Christine Chouinard

2 Faculty of Nursing, University of Montreal, Montreal, Quebec, Canada

Mathieu Bisson

Alya danish, marlène karam, ariane girard, pierre-luc bossé, mireille lambert.

3 Integrated University Health and Social Services Centre, Chicoutimi, Quebec, Canada

Associated Data

The case study design is particularly useful for implementation analysis of complex health care innovations in primary care that can be influenced by the context of dynamic environments. Case studies may be combined with participatory approaches where academics conduct joint research with nonacademic stakeholders, to foster translation of findings results into practice. The aim of this article is to clarify epistemological and methodological considerations of case studies with a participatory approach. It also aims to propose best practice recommendations when using this case study approach. We distinguish between the participatory case study with full co-construction and co-governance, and the case study with a participatory approach whereby stakeholders are consulted in certain phases of the research. We then compare the epistemological posture of 3 prominent case study methodologists, Yin, Stake, and Merriam, to present the epistemological posture of case studies with a participatory approach. The relevance, applications, and procedures of a case study with a participatory approach methodology are illustrated through a concrete example of a primary care research program (PriCARE). We propose 12 steps for designing and conducting a case study with a participatory approach that may help guide researchers in the implementation analysis of complex health care innovations in primary care.

Over the last 40 years, case study research has become increasingly popular and has evolved rapidly in many disciplines. By allowing in-depth analysis of complex phenomena in real-world contexts, 1 the case study design is particularly useful in health services research, 2 for implementation analysis of complex interventions that can be influenced by the context of dynamic environments. 3 Public health and primary care research encourage a participatory approach because involvement of stakeholders fosters translation of research findings into practice. 4 This was the case of the PriCARE primary care research program. In this multijurisdictional Canadian study, the research team and stakeholders aimed to evaluate the implementation of a case management intervention in 10 primary care clinics, for frequent users of health care services with chronic diseases and complex care needs. 5 , 6 It is important to first distinguish the case study with a participatory approach from the participatory case study before proceeding with the example of the PriCARE program.

Participatory Research and the Case Study

Participatory research is a systematic inquiry whereby academics conduct joint research with nonacademic partners affected by the issue being studied, for purposes of education and taking action or promoting social change. 7 , 8 Participatory research conducted for empowerment or social change relies on the transformative/postmodern interpretative paradigm, in which knowledge is not neutral and reflects the power and social relationships within a society. The purpose of knowledge construction is to help people improve society. 9 Each phase of the research process is an opportunity to create knowledge through a collaborative effort to develop or refine the research questions, select the methodology, develop data collection methods and tools, choose outcome measures, interpret findings, craft the message, and disseminate the results, feasibility, and outcomes. 4 Rosemary C. Reilly, PhD, MEd 10 proposes that a case study may adopt a participatory focus with full co-governance where participants are fully involved as contributing researchers in all phases of the research process, from conceptualization of the study to write-up and dissemination of the findings.

Within the different participatory research approaches, the transformational intent of stakeholder involvement may, however, range from empowerment to more pragmatic considerations. The case study with a participatory approach may be adopted to facilitate knowledge translation and practice changes 4 in the implementation of a complex intervention such as case management, where several components interact with each other and with their context, and where there are multiple highly adaptable effects. 11 The intensity of stakeholder involvement will vary from full co-construction and involvement in all stages of the research to involvement or consultation in only certain phases of the research, balancing stakeholder engagement and availability. The participatory case study with a full co-governance structure relies on the transformative/postmodern interpretative paradigm, but what are the epistemological assumptions of the case study with a participatory approach? What steps should be taken to ensure the validity of this approach when applied to the case study? In this article, we aim to clarify epistemological and methodological considerations of case studies with a participatory approach. We also propose best practice recommendations when applying this approach to the case study.

EPISTEMOLOGICAL ASSUMPTIONS OF 3 PROMINENT CASE STUDY METHODOLOGISTS

Three prominent case study methodologists—Robert K. Yin, PhD, Robert E. Stake, PhD, and Sharan B. Merriam, MEd, EdD—brought differing perspectives to move case study knowledge forward in educational and social science research. All 3 provided definitions, designs, applications, and procedures to follow when conducting case study research. 12 Table 1 summarizes and compares their epistemological positions and assumptions, which we discuss in more detail below.

Comparison of Epistemological Assumptions of Yin, Stake, Merriam, and Reilly (Inspired by Patton 15 )

Yin: Postpositivism

Yin’s realist–postpositivist epistemological posture 1 , 13 defines a case study as “an empirical inquiry that investigates a contemporary phenomenon (the ‘case’) within its real-life context.” 14 Although reality cannot be entirely apprehended, the knowledge generated from the case study is the result of the combination of experimentations leading to a closer approximation of actual mechanisms. 15 Yin suggests combining quantitative and qualitative sources, viewing them as equally instrumental. He places considerable emphasis on preparing a detailed design at the outset of the research and advises that investigators make only minor changes in the design after they begin data collection. 16 Interaction with research participants therefore needs to be minimized and subjectivity managed to avoid biasing the results. 16

Stake: Constructivism

Stake’s epistemological commitment is to constructivism, which leads him to define the case study as the “study of the particularity and complexity of a single case, coming to understand its activity within important circumstances.” 17 Unlike Yin, Stake considers knowledge as a construction rather than the result of an empiric inquiry developed within a logical sequence. He argues that reality is multiple and subjective. 17 This assertion implies that human experiences can be known through every perspective of a given situation, all of which are equally valuable. While suggesting that every viewpoint of a situation be represented in the case study, he recommends minimal interaction between the researchers and the context of the case or the involved individuals. 18

Merriam: Constructivist Pragmatism

Merriam’s constructivist pragmatism appears similar to Stake’s at the outset. Reality is an intersubjective construction. 19 Where she diverges from Stake is mostly in the finality of knowledge, which is to address concrete problems and give answers or direction to progress. 15 In this perspective, the truth is what works in practice. 15 Merriam’s approach to case study design combines elements of Yin’s positivist standpoint with Stake’s constructivism. For her, a case study is essentially an in-depth description and analysis of a bounded system. 19 Merriam proposes a structured approach to designing research in a step-by-step process: conducting a literature review; constructing a theoretical framework; identifying a research problem; crafting and sharpening research questions; and selecting the sample (purposeful sampling). 19

Yet, Merriam recommends that the study design remain flexible to a certain degree, which means, for example, that sample selection may occur before or in conjunction with data collection. 16 As it is the unit of analysis that defines the case, other types of approaches can be combined with the case study. 19 The design will depend on the theoretical framework of the study, its purpose, and the research questions. 19 In Merriam’s constructivist pragmatism, participatory research is an approach to enhance internal validity. 16 This epistemological posture is compatible with a participatory approach to case study research.

THE WHY AND HOW OF USING A CASE STUDY WITH A PARTICIPATORY APPROACH IN IMPLEMENTATION RESEARCH

Which case study approach should be used in implementation research? The answer will depend on the epistemological assumptions on which the methods will rely. On one hand, a research team adopting a postpositivist standpoint (as proposed by Yin) will want to maintain independence from stakeholders and will conduct the implementation analysis from an external/objective point of view that precludes a participatory approach. On the other hand, a team adopting a constructivist perspective (as proposed by Stake) will plan qualitative methods to shed light on the multiple perspectives of stakeholders without involving them as co-researchers in the study. Then again, researchers who adopt a transformative posture (as proposed by Reilly) will work closely with community or organizational partners in the co-construction of the implementation using a participatory case study approach. Finally, a “middle ground” approach20 may be to adopt a pragmatic posture (as proposed by Merriam), where researchers use a case study with a participatory approach to conduct an implementation analysis of a health care innovation while consulting community or organizational stakeholders in certain phases of the research. Adopting this epistemological posture, we will present the example of the PriCARE program 5 , 6 in the next section.

TWELVE STEPS FOR CONDUCTING CASE STUDIES WITH A PARTICIPATORY APPROACH IN HEALTH CARE IMPLEMENTATION RESEARCH

Building on Merriam’s previously mentioned step-bystep process, 19 we propose 12 steps for conducting case studies with a participatory approach in health care implementation research. Figure 1 illustrates the proposed research process. Steps 1 through 10 are sequential and iterative, whereas steps 11 and 12 are concurrent and ongoing.

Twelve steps to conduct a case study with a participatory approach.

(1) Think About What a Pragmatic Posture Means

Disagreements during the project within the academic research team, or between the academic research team and stakeholders, may be related to differences of epistemological posture or values. Being aware of and sharing this posture from the beginning of the project will help maintain the coherence of methodological choices throughout the project. For the PriCARE program, in accordance with the pragmatic posture of Merriam, the academic research team decided on consultation of varying intensity, rather than full partnership, depending on the category of stakeholders.

(2) Identify Stakeholders and Determine a Governance Structure for Consultation

To optimize the implementation process and practice changes, various stakeholders—decision makers, clinicians, and patient partners—may collaborate with the academic research team according to their interest, availability, and expertise. In PriCARE, decision makers and clinicians were consulted based on the relevance of their expertise to certain phases of the project, and to accommodate time constraints, whereas most patient partners were engaged as co-researchers in all steps of the project. Many stakeholders were involved before the grant was obtained and in a pragmatic context (people changing jobs or people expressing interest in being involved), whereas other stakeholders joined the team during the project (new patient partners, new case managers, etc). Supplemental Table 1 (available at https://www.AnnFamMed.org/lookup/suppl/doi:10.1370/afm.2717/-/DC1 ) identifies the committees and roles of stakeholders within the PriCARE program.

Four types of stakeholders were involved corresponding to the categories proposed by Damschroder et al21 in their Consolidated Framework for Implementation Research (Supplemental Figure 1, available at https://www.AnnFamMed.org/lookup/suppl/doi:10.1370/afm.2717/-/DC1 ). Their roles and contributions are detailed below.

Opinion leaders. Decision makers, who are referred to as opinion leaders, 21 are in a good position to inform the team regarding the broad context of implementation and to play a role in disseminating results and applying new knowledge. In the PriCARE program, decision makers were health center chief executive officers, primary care services directors, and representatives of health ministries. The academic research team consulted decision makers from each participating province while writing the grant request to ensure consideration of the global context in which the project would be implemented. Decision makers were consulted for strategic decisions and for knowledge transfer activities.

Champions. As champions, 21 clinicians working on the ground are usually aware of the specific dynamics in their setting and can give useful advice to the research team regarding feasibility, potential challenges, or adaptation required before implementation. Champions can be helpful in convincing their colleagues to participate in the project and in encouraging them toward change. The academic research team was in contact, in person or by telephone, with family physicians as well as managers in the clinics to facilitate case management implementation.

Formally appointed internal implementation leaders. Individuals from within the organization who have been formally appointed with responsibility for implementing the intervention—as a part of their job—are called formally appointed internal implementation leaders. 21 In PriCARE, the case manager nurses were identified during recruitment of the participating clinics at the beginning of the project. In addition to doing fieldwork, they informed the academic research team about the challenges they were facing or about what helped them to carry out the intervention as the project was progressing. The academic research team organized formal training and a virtual community of practice bringing all case managers together to deploy co-development activities.

External change agents. Finally, patient partners may play the role of external change agents. 21 They bring an experiential perspective to research, provide valuable advice to the team about patient recruitment and data collection, and validate and interpret aspects of the analysis. In PriCARE, regular meetings with patient partners (not related to the clinics) and research assistants were organized to advise the team on different aspects of the project (questionnaires, patient recruitment, analysis, knowledge transfer plan, etc). Patient partners also contributed to training the case managers and met with them to advise them on approaching patients with complex needs.

Discussions with stakeholders addressed expectations and preferences regarding their contribution, as well as the management of interaction, engagement, and communication. A clear governance structure was proposed ( Supplemental Figure 1 ). Most communication was virtual and by e-mail to accommodate geographic realities. The way the team functioned always considered the various circumstances of different stakeholders, their level of involvement, and their ability to contribute during the project.

(3) Consult Stakeholders About the Research Problem

PriCARE decision makers and clinicians in each province helped the academic research team to understand their context of implementation and what was needed in that province in terms of adapting the intervention and training. We also consulted patient partners to develop a broader understanding of the problem.

(4) Conduct a Literature Review

The literature review determines the knowledge gap, which in turn allows the relevant research questions to be presented and specified for the project. In PriCARE, 2 literature reviews on case management were conducted: a systematic review by the academic research team22 and a realist synthesis by the research team engaging stakeholders in the steering committee, including decision makers, clinicians, and patient partners. 23 Both reviews were summarized and shared with stakeholders.

(5) Sharpen Research Questions or Objectives

The final research questions of the PriCARE program were formulated, after consultation with stakeholders, by the academic research team. They are as follows: what are the facilitators of and barriers to case management implementation in primary care clinics across Canada; what are the relationships between the actors, contextual factors, mechanisms, and outcomes of the case management intervention; and what are the next steps toward case management scale-up in primary care across Canada?

(6) Choose or Construct a Theoretical Framework

A theoretical framework emerging from the literature review helps elaborate research questions and points of emphasis. 24 It also often helps in the building of data collection tools (eg, interview guides and questionnaires) and in guiding the analysis process. Although stakeholders may contribute to this step, in PriCARE, it was the academic research team who decided to use a combination of the Consolidated Framework for Implementation Research 21 and the Rainbow Model of Integrated Care Framework, 25 combining the concepts of primary care and integrated care. 6 The academic research team took responsibility for explaining theoretical frameworks to stakeholders through brief, informal online meetings, to ensure a common comprehension and facilitate participation and engagement of all stakeholders throughout the research process.

(7) Define the Case and Its Boundaries

In implementation research, the case is often an innovation implemented in a specific primary care setting. To select the case and establish the research design, we recommend identifying the focus and refining the parameters of the case including the participants, location, and/or process to be explored, and also establishing the timeframe for investigating the case. 19 The focus and boundaries may also be influenced by the resources and time available to accomplish the research project. In PriCARE, stakeholders, especially opinion leaders and champions, helped delimit the cases. Each case was the case management intervention implemented in the individual clinic.

(8) Design the Methods and Collect the Data

We encourage researchers to use multiple methods of data collection to provide a more comprehensive view of the subject being studied. Data collection methods for case studies are usually qualitative but may also be quantitative. 1 Use of software is highly recommended for regrouping and managing all the data. 9 , 15 The complete design and data collection methods of PriCARE, which had a multiple-case, embedded, mixed methods design, are described elsewhere. 5 , 6 The research team designed the methods. Clinicians and case managers identified eligible patient participants registered to the clinic, who were contacted by the latter. Patient partners, well positioned to understand the situation of participants, contributed to explaining the research project in lay language, and to answering their questions to obtain their consent for participation. They were also involved in developing recruitment and data collection tools to adapt the scientific language to a lay audience.

Case study research with a participatory approach allowed the PriCARE academic research team to observe participants during meetings with stakeholders. The academic research team carefully planned interactions to manage key messages to be delivered to stakeholders and to record and document all interactions so that meetings were also opportunities for data collection, for promoting change, and for facilitating implementation. The impact of this approach on data collection and results must be rigorously documented, analyzed, and discussed. 9 , 26

(9) Do the Analysis

Although the various analytic strategies suggested by the 3 methodologists 13 , 19 , 27 remain relevant, the particulars of case studies with a participatory approach make it possible to involve partners in various steps, to better understand, to coanalyze, or to validate results. In PriCARE, patient partners participated in key steps of the analysis to ensure meaningful interpretation.

(10) Reflect on the Impact of the Participatory Approach on the Results

The case study with participatory approach should document the role of the research team during observation and consider it to be a contextual element in the analysis of each case. For example, positive relationships between the individuals involved in a case may promote implementation and improve impact. 28 This situation may differ with another group of individuals in another case. Although such facilitation is considered a desirable extra benefit of the participatory approach, its impact on the results still has to be made explicit and discussed. 8

In PriCARE, the research team used a logbook to document interactions and reflections to maintain a reflexive distancing. 9 , 19 We sought to involve all stakeholders in these reflections, to better understand the impacts of the participatory approach, both positive and negative, which were transparently discussed in reports or articles.

(11) Plan Strategies to Ensure Rigor

As a concurrent, ongoing step, the team has to plan strategies to ensure the rigor of the research. 29 In PriCARE, we ensured credibility through in-depth description and analysis of context using qualitative and quantitative data collection in each province. We kept an audit trail of all decisions and collected data to ensure dependability. We promoted triangulation of the expertise of team members (researchers of various backgrounds, diverse health care professionals, patient partners, decision makers) and reflexivity through team discussions and interactions. We made a thick description of each clinic’s context to promote transferability. We also respected rigor criteria when administering questionnaires. 30

(12) Elaborate and Apply a Knowledge Transfer Plan

Researcher and stakeholder collaboration throughout the research process is a strong predictor that research findings will be put into practice, 31 so stakeholders should be involved in the elaboration and the application of the knowledge transfer plan. In PriCARE, team members and stakeholders of each province representing each targeted audience (population, clinicians, decision makers, and researchers) helped to write the plan throughout the study, tailor messages, and disseminate case study findings. 31 All stakeholders mobilized within the case study contributed to knowledge transfer.

CONCLUSIONS

Engaging stakeholders in the design and conduct of case studies may enhance implementation analysis of complex health care interventions in primary care, whereby stakeholders are consulted to foster translation of findings results into practice. Ensuring transparency and rigor of the approach remains crucial as it lays the groundwork for critical evaluation of this strategy. The 12 steps we propose here constitute a major milestone toward attaining this goal. Future research could contribute to testing and refining these steps, and demonstrating the contribution of this approach to implementation in health care.

Supplementary Material

Acknowledgments.

We would like to acknowledge all team members and partners who were engaged in the PriCARE program.

Conflicts of interest: authors report none.

To read or post commentaries in response to this article, go to https://www.AnnFamMed.org/content/19/6/540/tab-e-letters .

Authors’ contributions: C.H. proposed a first draft of the manuscript. C.H., M-C.C., M.B., A.D., M.K., A.G., P-L.B., and M.L. substantially contributed to subsequent drafts. All authors read and approved the final manuscript.

Funding support: This work was supported by the Canadian Institutes of Health Research (CIHR).

Disclaimer: The views expressed are solely those of the authors and do not necessarily represent official views of the authors’ affiliated institutions or funder.

Supplemental materials: Available at https://www.AnnFamMed.org/lookup/suppl/doi:10.1370/afm.2717/-/DC1 .

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Please note you do not have access to teaching notes, an action research case study: digital equity and educational inclusion during an emergent covid-19 divide.

Journal for Multicultural Education

ISSN : 2053-535X

Article publication date: 22 January 2021

Issue publication date: 4 June 2021

This paper aims to share responses from current literature, a small case study about perceptions and practices of the school of education faculty toward multicultural and educational issues concerning the rapid rise in online environments during coronavirus (COVID-19) experiences and just-in-time strategies for addressing digital equity and educational inclusion in K-16 online educational settings.

Design/methodology/approach

This is a conceptual paper that emerged from an action research case study. The study included four faculty in an urban school of education. The faculty participants were asked to provide examples of educational inclusion strategies used during transitioning their courses and advising to online environments in a Research I university. Faculty included one educational leadership, one sports management, one special education and one teacher education professor. Central issues explored practices related to language, technology access, curriculum design and technological competencies and assessment. A driving question was: How do institutions, schools or educators provide learning opportunities to support digital equity and inclusive education practice to maintain and strengthen relationships and core practices of multicultural education during a time of physical distancing during COVID-19? And what are the experiences, barriers, successes?

Research-based transformative knowledge, real situations and practical resources for considering inclusive education curriculum concepts were found that are connecting educators, teachers, learners and communities during this time of crisis.

Research limitations/implications

Methodological limitations that influenced the research design include conducting research in a totally virtual environment, small sample size, lack of diversity in curriculum content and one research site. The data collection was limited to written responses from the faculty participants. This action research study took place in a time frame limited by COVID-19 conditions during a four-month period.

Practical implications

In theory and practice, this new online movement suggests learners, teachers, educators and leaders are gaining experience and knowledge about resources and strategies for using new technologies, assessments and flexible curriculum as powerful tools for building language, curriculum and social-cultural communication bonds across generations and including special needs populations. Such new and emerging strategies could be used to bridge gaps in a time of distancing to support inclusive and equitable learning environments in education to minimize the effects of an emergent COVID-19 digital divide. Social learning culture as constructed, performed and captured in patterns of cooperation among faculties shows the world becoming more open and less restricted by borders. In conclusion, an emerging new conceptual framework is presented in Figure 2 to support action planning to bridge the digital equity access and learning gaps created by COVID-19.

Social implications

It is in times of strife and difficulty that problems and issues become exacerbated. While some educators easily adapted and took on the challenges of online learning, others needed time for learning and mourning (literally and figuratively). The issues of equity and access have become even more apparent as this paper takes inventory of intersections between multicultural education, special education, sports education and K-16 education overall. This is an excellent time to reflect on how education can address the cultural, economic and social barriers that impact student learning globally for all learners.

Originality/value

The brief collective case study reports educational experiences during a time of crisis that stimulates creative and innovative approaches to creating inclusive and equitable online learning environments to address diverse learning needs. The various and often contrasting educator responses from faculty facing digital and educational challenges present ideas that might be applicable in the global learning environment beyond the COVID-19 pandemic.

• Online learning
• New technologies
• Transformative knowledge

Acknowledgements

World Council on Curriculum and Instruction -WCCI (UNESCO-NGO) Newsletter, Winter 2020 Content cited by Toh Swee-Hin (S.H.Toh) President, WCCI. Professor Emeritus, University of Alberta. Laureate, UNESCO Prize for Peace Education (2000).

Pittman, J. , Severino, L. , DeCarlo-Tecce, M.J. and Kiosoglous, C. (2021), "An action research case study: digital equity and educational inclusion during an emergent COVID-19 divide", Journal for Multicultural Education , Vol. 15 No. 1, pp. 68-84. https://doi.org/10.1108/JME-09-2020-0099

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Copyright © 2020, Emerald Publishing Limited

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Action Research

Understanding and analyzing your actions is vital for self-improvement. It would help if you recognized how your actions affect your future. Examining your progress is called action research. This method applies to psychology, marketing, and education. Action research is used by teachers to find solutions to problem areas or formulate research plans for factors that need improvement. The results of action research are useful to the participants since it helps them better themselves for the next tasks. This research has guaranteed relevance because the researchers get to decide what the focus of the study is. They are also the ones who will make use of the results.

Every action someone makes has a ripple effect on the future. One small act of kindness can lead to great fortunes. Likewise, any lousy act can turn into something terrible. A person’s mistakes are what makes him who he is today. Ziad K. Abdelnour even said, “Never erase your past. It shapes who you are today and will help you to be the person you’ll be tomorrow.” For one to grow as a person, one needs to be able to recognize one’s mistakes and learn from them. Perhaps you need to create an action plan or conduct action research to help yourself out.

The Power of Three

Not all types of research are useful for all fields; some are effective only on specific studies. Luckily, action research can serve many disciplines. Although most applicable to educational research settings, the action research design works for an endless variation of studies. This research approach can also be used by individuals or by groups of researchers. The difference in researchers also signifies a difference in purpose.

Reflective Practitioner When an individual practitioner decides to look into his way of teaching, he unconsciously analyzes his actions to improve the instruction. The more he studies himself, the more he masters the science and process of it all.

Large-Scale Progress In education, as the school progresses, the students progress with it. That is why many schools continuously seek ways to strengthen their instruction to build schoolwide improvement. When instructors come together to fix a single issue, organizational growth is bound to occur.

Professional Culture Medical and educational professionals don’t always agree on particular methods. Sometimes they need to do what they think is appropriate. The only important thing is that they lean towards the same organizational goal . With their differing approaches, they can share their own discoveries to their colleagues, making for more holistic improvement.

13+ Action Research Examples

The best way to improve yourself is by analyzing your actions and making adjustments along the way. This is a research method called action research. To help you further understand what action research is, here are multiple action research examples you can check out.

1. Research Action Plan Template

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2. Research Corrective Action Plan Template

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3. Research Project Action Plan Template

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4. Sample Action Research Example

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5. Action Orientation Research Example

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6. Art Article Action Research Example

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7. Basic Action Research Example

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8. Five Phases of Action Research Example

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10. Action Research in Teacher Education Example

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11. Action Research Support Notes Example

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12. Handbook for Action Research Example

13. Action Research in PDF

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14. Action Research for Professional Development Example

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Segments of a Cycle

Action research is an approach that lets an individual study one’s action to help enhance their basic skills and knowledge of a given task or topic. There is a cycle that this research follows to make continuous improvements to a group or individual. As with any research projects, there are steps you need to follow to accomplish your project goals.

1. Selecting Focus

The action research cycle begins with identifying an area that you think needs improvement. Only the researcher can assess if the research focus is worth the time. The outcome of the focus should be the betterment of a practitioner’s work. Thus, picking the right center is extremely important.

2. Clarifying Theories

The next step is figuring out what approach works best for the problem area. You can try out different methods to solve your problem. This way, you can identify what process flow you are going to follow for the duration of the research. Studying various methods, beliefs, and theories can help you decide what you feel is most effective.

3. Collecting data

Your data should be valid and reliable to guarantee improvement. That is why it would be wrong to just stick to one source of data. If you can find various academic references to answer any of your questions, you should utilize them. This way, you can match the right technique with the unique qualities your research holds.

4. Analyzing Data

When conducting data analysis , you need not use complex calculations and statistical methods; you just need to examine the data you have collected. In studying the patterns and trends in your research data, you just need to answer two questions. What story does the data tell? Why is the story executed this way?

In a day, teachers face more students than fellow teachers. That’s why, given a chance to speak with their colleagues, teachers make share their discoveries from their research. This way, they get to express organizational knowledge they think is useful for other teachers while gaining insight as well.

The last step of the research action plan is, of course, to take action. This part is where teachers make their lesson plans . This part is satisfying to teachers because they feel they have gotten wiser with every piece of knowledge they have uncovered.

Everyone should learn from their mistakes. With every trial and error is a new way of looking at things. You just need to be vigilant with all your actions and know that there is always a better way of doing things. Once you’ve refined your skills, you are sure to become a master.

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Research for Organizing

A Toolkit for Participatory Action Research from TakeRoot Justice

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This toolkit is designed for organizations and individuals that want to use participatory action research (PAR) to support their work towards social justice.  PAR helps us to analyze and document the problems that we see in our communities; allows us to generate data and evidence that strengthens our social justice work and ensures that we are the experts about the issues that face our communities.  

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In this toolklit you will find case studies, workshops, worksheets and templates that you can download and tailor to meet your needs.

• Step-by-step Timeline of a Participatory Action Research Project

• Case Studies

Right to the City National We Call These Projects Home

Vocal-NY Syringe Access Report

Domestic Workers United Research Project

• Example Activities
• Community Mapping Training
• Facilitating a Focus Group
• Survey Administration Training
• Example Tools
• Survey Template
• Interview Guide Template
• Choosing the Right Research Tool
• Informed Consent Form Template

Alternative Courses of Action in Case Study: Examples and How To Write

The ultimate goal of creating a case study is to develop a feasible action that can solve the problem it raised.

One way to achieve this is by enumerating all the possible solutions for your case study’s subject. The portion of the case study where you perform this is called ACA or Alternative Courses of Action.

Are you struggling with writing your case study’s ACA?  Do not worry; we have provided you with the most detailed guide on writing the Alternative Courses of Action (ACA) of a case study.

Table of Contents

What are alternative courses of action (aca) in a case study.

Alternative Courses of Action (ACA) are the possible actions a firm or organization can implement to address the problem indicated in the case study. These are suggested actions that a firm can consider to arrive at the most feasible and effective solution to the problem. 

This portion doesn’t provide the actual and optimal solution yet. Instead, it contains proposed alternatives that will still undergo an evaluation of their respective advantages and disadvantages to help you come up with the best solution. 

The ACA you will offer and indicate will be based on your case study’s SWOT analysis in the “ Areas of Consideration ” portion. Thus, a SWOT analysis is performed first before writing the ACA.

What Is the Importance of Alternative Courses of Action (ACA) in a Case Study?

Given the financial, logistical, and operational limitations, developing solutions that the firm can perform can be challenging. By enumerating and evaluating the ACA of your case study, you can filter out the alternatives that can be a potential solution to the problem, given the business’s constraints 1 . This makes your proposed solutions feasible and more meaningful.

How To Write Alternative Courses of Action in Case Study

Here are the steps on how to write the Alternative Courses of Action for your case study:

1. Analyze the Results of Your SWOT Analysis

Using the SWOT analysis, consider how the firm can use its strengths and opportunities to address its weaknesses, mitigate threats, and eventually solve the case study’s problem. 

Suppose that the case study’s problem is declining monthly sales, and the SWOT analysis showed the following:

• Strength : Creative marketing team 
• Opportunity : Increasing trend of using social media to promote products

Then, you may include an ACA about developing the digital marketing arm of the firm to attract more customers and boost monthly sales. This can also address one of the possible threats the firm faces, which is increasing direct marketing costs.

2. Write Your Proposed Solutions/Alternative Courses of Action (ACA) for Your Case Study’s Problem

Once you have reviewed your SWOT analysis and come up with possible solutions, it’s time to write them formally in your manuscript. Each solution does not have to be too detailed and wordy. State the specific action that the firm must perform concisely.

Going back to our previous example in Step 1, here is one of the possible ACA that can be included:

ACA #1: Utilize digital platforms such as web pages and social media sites as an alternative marketing platform to reach a wider potential customer base. Digital marketing, together with the traditional direct marketing strategy currently employed, maximizes the business’ market presence, attracting more customers, and potentially driving revenues upward.

In our example above, there is a clear statement of the firm’s action: to use web pages and social media sites to reach more potential customers and increase market presence. Notice how the ACA above provides only an overview of “what to do” and not a complete elaboration on “how to do it.” 

3. Identify the Advantages and Disadvantages of Each ACA You Have Proposed

After specifying the ACA, you must evaluate them by stating their respective advantages (pros) and disadvantages (cons). In other words, you must state how your ACA favors the firm (advantages) and its downsides and limitations (disadvantages).

Again, your evaluation does not have to be too detailed but make sure that it is relevant to the ACA that it pertains to. 

Let’s return to the ACA we developed from step 2, utilizing digital platforms (e.g., social media sites) to reach more potential customers. What do you think will be the pros and cons of this ACA?

Let’s start with its potential benefits (advantages). Using digital platforms is cheaper than using print ads or direct marketing. So, this will save some funds for the firm. In short, it is cost-effective. 

Second, digital platforms offer analytical tools to measure your ads’ reach, making it easier to evaluate people’s perceptions of your offering. 

Third, using social media sites makes communicating with any potential customer easier. You can quickly respond to their queries, especially if they are interested in your product. 

Lastly, you can reach as many types of people as possible by taking advantage of the internet algorithm.

Now, let us consider its disadvantages 2 . First, using digital marketing takes time and effort to learn, and you must be able to adapt quickly to the changes in trends and new strategies to keep up with the competition. 

Second, you must deal with the increasing market competition, as many businesses already use digital platforms. 

Third, you have to deal with negative feedback from your customers that are visible to the public and may affect their perception of your brand.

After pondering over the pros and cons of your ACA, it’s time to write them concisely in your manuscript. You can present it in two ways: by tabulating it or by simply listing them.

Example in Table Form:

Examples of Alternative Courses of Action (ACA) in a Case Study

Case Study Problem: Xenon Pastries faces a problem handling larger orders as Christmas Day approaches. With an estimated 15% increase in customer demand, this is the most significant increase in their daily orders since 2012. The management aims to maximize profit opportunities given the rise in customer demand. 

ACA #1: Hire part-time workers to increase staff numbers and meet the overwhelming seasonal increase in customer orders. Currently, Xenon Pastries has a total of 9 workers who are responsible for the accommodation of orders, preparation, and delivery of products, and addressing customers’ inquiries and complaints. Hiring 2 – 3 part-time workers can increase productivity and meet the daily order volume.

• Do not require too much effort to implement since hiring announcements only require signages or social media postings
• High certainty of finding potential workers due to the high unemployment rate
• Improve overall productivity of the business and the well-being of other workers since their workload will be lessened

Disadvantages

• Increase in operating expense in the form of wages to the new workers
• Managing more employees and monitoring their performance can be challenging
• New workers might find it challenging to adapt essential skills required in the operation of the business

ACA #2: Increase the prices of Xenon pastries’ products to increase revenues . This option can maximize Xenon Pastries’ profit even if not all customers’ orders are accommodated. 

• Cost-effective
• Easy to implement since it only requires changing the price tags of the products
• If customers’ desire to buy the products does not change, the price increase will certainly increase the business’ revenue
• Some customers might be discouraged from buying because of an increase in prices
• There’s a possibility that the increase in the price of the products will make it more expensive relative to competitors’ products

Case Study Problem: Delta Motors has been manufacturing motorcycles for ten years. Recently, the business suffered a gradual shrink in its quarterly revenues due to the increasing popularity of traditional and newly-developed electric bikes. Delta Motors seeks a long-term strategy to attract potential customers to bounce back sales.  

ACA #1: Develop a “regular installment payment” scheme to attract customers who wish to purchase motorcycles but have insufficient lump-sum money to acquire one.  This payment scheme allows customers to pay an initial deposit and the remaining amount through smaller monthly payments.

• Enticing for middle to low-income individuals who comprise a large chunk of the population
• Requires low initial capital to implement 
• Provides a new source of monthly income streams that can benefit the financial standing of the company
• Risk of default or delays in installment payments
• Requires additional human resources to manage and collect installment payments
• The payment scheme requires time to gain returns due to the periodic flow of funds
• Requires a careful creation of guidelines and terms and conditions to ensure smooth facilitation of the installment payment scheme

ACA #2: Introduce new motorcycle models that can entice different types of customers. These models will feature popular designs and more efficient engines.

• This may capture the public’s interest in Delta Motors, which can lead to an increase in the number of potential customers and earning opportunities
• Enables the business to keep up with the intense market competition by providing something “fresh” to the public
• Provides more alternatives for those who already support Delta Motors, strengthening their loyalty to the brand
• Conceptualization of a new model takes a lot of brainstorming to test its feasibility and effectiveness
• Requires sufficient funds to sustain the investment for the development of a new model
• It requires effective marketing strategies to promote the new model to the public

Tips and Warnings

• Do not include in this portion your case study’s conclusion . Think of ACA as a list of possible ways to address the problem. In other words, you suggest the possible alternatives to be selected here. The “ Recommendation ” portion of your case study is where you pick the most appropriate way to solve the problem.
• Use statistical data to support the advantages and disadvantages of each ACA. Although this is optional, presenting numerical data makes your analysis more concrete and factual than just stating them descriptively. 
• Do not fall into the “meat sandwich” trap. This happens when you intently make some of the alternatives less desirable so that your preferred choice stands out. This can be done by refusing to elaborate on their benefits or excessively concentrating on their disadvantages. Make sure that each ACA has potential and can be implemented realistically.

Frequently Asked Questions

1. how many alternative courses of action (aca) can a case study have.

Sometimes your instructor or teacher will tell you the required number of ACA that must be included in your case study . However, there’s no “standard” limit to how many ACA you can indicate.

2. What is the difference between Alternative Courses of Action (ACA) and Recommendations?

As mentioned earlier, the case study’s ACA aims to enumerate all possible solutions to the problem. It is not the stage where you state the “final” action you deem most appropriate to address the issue. The case study portion where you explicitly mention your “best” alternative is called the “Recommendation.” 

To help you understand the point above, let’s return to our Delta Motors example. In our previous section, we have provided two ACA that can solve the problem, namely (1) developing a regular installment payment plan and (2) introducing a new motorcycle model. 

Suppose that upon careful analysis and evaluation of these ACA, you came up with ACA #2 as the more fitting solution to the problem. When you write your case study’s recommendation, you must indicate the ACA you chose and your reasons for selecting it. 

Here’s an example of the Recommendation of the case study:

Recommendation

Introducing new motorcycle models that feature popular designs and more efficient engines to entice different types of customers is the most promising alternative course of action that Delta Motors can implement to bounce back its quarterly revenues and keep up with the competitive market. This creates a strong impression on the public of the company’s dedication to promoting high-quality motorcycles that can withstand changes in consumer preferences and market trends. Furthermore, this action proves that the company is continuously evolving to offer a variety of alternative models to suit everyone’s tastes. With proper promotion, these models can rekindle the company’s popularity in the automotive and motorcycle industry.

• How to Analyze a Case Study. Retrieved 23 May 2022, from https://wps.prenhall.com/bp_laudon_essbus_7/48/12303/3149605.cw/content/index.html
• Develop a Digital Marketing Plan. Retrieved 23 May 2022, from https://www.nibusinessinfo.co.uk/content/advantages-and-disadvantages-digital-marketing

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Last Updated July 8, 2023 08:29 PM

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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