science and critical thinking skills reflection

• MISSION / VISION
• DIVERSITY STATEMENT
• CAREER OPPORTUNITIES
• Kide Science
• STEMscopes Science
• Collaborate Science
• STEMscopes Math
• Math Nation
• STEMscopes Coding
• Mastery Coding
• DIVE-in Engineering
• STEMscopes Streaming
• Tuva Data Literacy
• NATIONAL INSTITUTE FOR STEM EDUCATION
• STEMSCOPES PROFESSIONAL LEARNING
• RESEARCH & EFFICACY STUDIES
• STEM EDUCATION WEBINARS
• LEARNING EQUITY
• DISTANCE LEARNING
• PRODUCT UPDATES
• LMS INTEGRATIONS
• STEMSCOPES BLOG
• FREE RESOURCES
• TESTIMONIALS

Critical Thinking in Science: Fostering Scientific Reasoning Skills in Students

ALI Staff | Published  July 13, 2023

Thinking like a scientist is a central goal of all science curricula.

As students learn facts, methodologies, and methods, what matters most is that all their learning happens through the lens of scientific reasoning what matters most is that it’s all through the lens of scientific reasoning.

That way, when it comes time for them to take on a little science themselves, either in the lab or by theoretically thinking through a solution, they understand how to do it in the right context.

One component of this type of thinking is being critical. Based on facts and evidence, critical thinking in science isn’t exactly the same as critical thinking in other subjects.

Students have to doubt the information they’re given until they can prove it’s right.

They have to truly understand what’s true and what’s hearsay. It’s complex, but with the right tools and plenty of practice, students can get it right.

What is critical thinking?

This particular style of thinking stands out because it requires reflection and analysis. Based on what's logical and rational, thinking critically is all about digging deep and going beyond the surface of a question to establish the quality of the question itself.

It ensures students put their brains to work when confronted with a question rather than taking every piece of information they’re given at face value.

It’s engaged, higher-level thinking that will serve them well in school and throughout their lives.

Why is critical thinking important?

Critical thinking is important when it comes to making good decisions.

It gives us the tools to think through a choice rather than quickly picking an option — and probably guessing wrong. Think of it as the all-important ‘why.’

Why is that true? Why is that right? Why is this the only option?

Finding answers to questions like these requires critical thinking. They require you to really analyze both the question itself and the possible solutions to establish validity.

Will that choice work for me? Does this feel right based on the evidence?

How does critical thinking in science impact students?

Critical thinking is essential in science.

It’s what naturally takes students in the direction of scientific reasoning since evidence is a key component of this style of thought.

It’s not just about whether evidence is available to support a particular answer but how valid that evidence is.

It’s about whether the information the student has fits together to create a strong argument and how to use verifiable facts to get a proper response.

Critical thinking in science helps students:

• Actively evaluate information
• Identify bias
• Separate the logic within arguments
• Analyze evidence

4 Ways to promote critical thinking

Figuring out how to develop critical thinking skills in science means looking at multiple strategies and deciding what will work best at your school and in your class.

Based on your student population, their needs and abilities, not every option will be a home run.

These particular examples are all based on the idea that for students to really learn how to think critically, they have to practice doing it. 

Each focuses on engaging students with science in a way that will motivate them to work independently as they hone their scientific reasoning skills.

Project-Based Learning

Project-based learning centers on critical thinking.

Teachers can shape a project around the thinking style to give students practice with evaluating evidence or other critical thinking skills.

Critical thinking also happens during collaboration, evidence-based thought, and reflection.

For example, setting students up for a research project is not only a great way to get them to think critically, but it also helps motivate them to learn.

Allowing them to pick the topic (that isn’t easy to look up online), develop their own research questions, and establish a process to collect data to find an answer lets students personally connect to science while using critical thinking at each stage of the assignment.

They’ll have to evaluate the quality of the research they find and make evidence-based decisions.

Self-Reflection

Adding a question or two to any lab practicum or activity requiring students to pause and reflect on what they did or learned also helps them practice critical thinking.

At this point in an assignment, they’ll pause and assess independently. 

You can ask students to reflect on the conclusions they came up with for a completed activity, which really makes them think about whether there's any bias in their answer.

Addressing Assumptions

One way critical thinking aligns so perfectly with scientific reasoning is that it encourages students to challenge all assumptions. 

Evidence is king in the science classroom, but even when students work with hard facts, there comes the risk of a little assumptive thinking.

Working with students to identify assumptions in existing research or asking them to address an issue where they suspend their own judgment and simply look at established facts polishes their that critical eye.

They’re getting practice without tossing out opinions, unproven hypotheses, and speculation in exchange for real data and real results, just like a scientist has to do.

Lab Activities With Trial-And-Error

Another component of critical thinking (as well as thinking like a scientist) is figuring out what to do when you get something wrong.

Backtracking can mean you have to rethink a process, redesign an experiment, or reevaluate data because the outcomes don’t make sense, but it’s okay.

The ability to get something wrong and recover is not only a valuable life skill, but it’s where most scientific breakthroughs start. Reminding students of this is always a valuable lesson.

Labs that include comparative activities are one way to increase critical thinking skills, especially when introducing new evidence that might cause students to change their conclusions once the lab has begun.

For example, you provide students with two distinct data sets and ask them to compare them.

With only two choices, there are a finite amount of conclusions to draw, but then what happens when you bring in a third data set? Will it void certain conclusions? Will it allow students to make new conclusions, ones even more deeply rooted in evidence?

Thinking like a scientist

When students get the opportunity to think critically, they’re learning to trust the data over their ‘gut,’ to approach problems systematically and make informed decisions using ‘good’ evidence.

When practiced enough, this ability will engage students in science in a whole new way, providing them with opportunities to dig deeper and learn more.

It can help enrich science and motivate students to approach the subject just like a professional would.

Share this post!

Related articles.

Strategies For Building A Math Community In Your Classroom

At the start of the school year, teachers have the chance to create a math classroom where every student feels valued...

Math Manipulatives: How Can They Improve Student Learning in Math?

Math manipulatives are a great way to make math more accessible for your students, especially if you know they may...

Why Is Storytelling Important in Early Childhood Education?

Storytelling is one of the oldest forms of communication as a way to share experiences, understand others, and...

STAY INFORMED ON THE LATEST IN STEM. SUBSCRIBE TODAY!

Which stem subjects are of interest to you.

STEMscopes Tech Specifications      STEMscopes Security Information & Compliance      Privacy Policy      Terms and Conditions

© 2024 Accelerate Learning  

• Top Courses
• Online Degrees
• Find your New Career
• Join for Free

What Are Critical Thinking Skills and Why Are They Important?

Learn what critical thinking skills are, why they’re important, and how to develop and apply them in your workplace and everyday life.

We often use critical thinking skills without even realizing it. When you make a decision, such as which cereal to eat for breakfast, you're using critical thinking to determine the best option for you that day.

Critical thinking is like a muscle that can be exercised and built over time. It is a skill that can help propel your career to new heights. You'll be able to solve workplace issues, use trial and error to troubleshoot ideas, and more.

We'll take you through what it is and some examples so you can begin your journey in mastering this skill.

What is critical thinking?

Critical thinking is the ability to interpret, evaluate, and analyze facts and information that are available, to form a judgment or decide if something is right or wrong.

More than just being curious about the world around you, critical thinkers make connections between logical ideas to see the bigger picture. Building your critical thinking skills means being able to advocate your ideas and opinions, present them in a logical fashion, and make decisions for improvement.

Build job-ready skills with a Coursera Plus subscription

• Get access to 7,000+ learning programs from world-class universities and companies, including Google, Yale, Salesforce, and more
• Try different courses and find your best fit at no additional cost
• Earn certificates for learning programs you complete
• A subscription price of $59/month, cancel anytime

Why is critical thinking important?

Critical thinking is useful in many areas of your life, including your career. It makes you a well-rounded individual, one who has looked at all of their options and possible solutions before making a choice.

According to the University of the People in California, having critical thinking skills is important because they are [ 1 ]:

Crucial for the economy

Essential for improving language and presentation skills

Very helpful in promoting creativity

Important for self-reflection

The basis of science and democracy 

Critical thinking skills are used every day in a myriad of ways and can be applied to situations such as a CEO approaching a group project or a nurse deciding in which order to treat their patients.

Examples of common critical thinking skills

Critical thinking skills differ from individual to individual and are utilized in various ways. Examples of common critical thinking skills include:

Identification of biases: Identifying biases means knowing there are certain people or things that may have an unfair prejudice or influence on the situation at hand. Pointing out these biases helps to remove them from contention when it comes to solving the problem and allows you to see things from a different perspective.

Research: Researching details and facts allows you to be prepared when presenting your information to people. You’ll know exactly what you’re talking about due to the time you’ve spent with the subject material, and you’ll be well-spoken and know what questions to ask to gain more knowledge. When researching, always use credible sources and factual information.

Open-mindedness: Being open-minded when having a conversation or participating in a group activity is crucial to success. Dismissing someone else’s ideas before you’ve heard them will inhibit you from progressing to a solution, and will often create animosity. If you truly want to solve a problem, you need to be willing to hear everyone’s opinions and ideas if you want them to hear yours.

Analysis: Analyzing your research will lead to you having a better understanding of the things you’ve heard and read. As a true critical thinker, you’ll want to seek out the truth and get to the source of issues. It’s important to avoid taking things at face value and always dig deeper.

Problem-solving: Problem-solving is perhaps the most important skill that critical thinkers can possess. The ability to solve issues and bounce back from conflict is what helps you succeed, be a leader, and effect change. One way to properly solve problems is to first recognize there’s a problem that needs solving. By determining the issue at hand, you can then analyze it and come up with several potential solutions.

How to develop critical thinking skills

You can develop critical thinking skills every day if you approach problems in a logical manner. Here are a few ways you can start your path to improvement:

1. Ask questions.

Be inquisitive about everything. Maintain a neutral perspective and develop a natural curiosity, so you can ask questions that develop your understanding of the situation or task at hand. The more details, facts, and information you have, the better informed you are to make decisions.

2. Practice active listening.

Utilize active listening techniques, which are founded in empathy, to really listen to what the other person is saying. Critical thinking, in part, is the cognitive process of reading the situation: the words coming out of their mouth, their body language, their reactions to your own words. Then, you might paraphrase to clarify what they're saying, so both of you agree you're on the same page.

3. Develop your logic and reasoning.

This is perhaps a more abstract task that requires practice and long-term development. However, think of a schoolteacher assessing the classroom to determine how to energize the lesson. There's options such as playing a game, watching a video, or challenging the students with a reward system. Using logic, you might decide that the reward system will take up too much time and is not an immediate fix. A video is not exactly relevant at this time. So, the teacher decides to play a simple word association game.

Scenarios like this happen every day, so next time, you can be more aware of what will work and what won't. Over time, developing your logic and reasoning will strengthen your critical thinking skills.

Learn tips and tricks on how to become a better critical thinker and problem solver through online courses from notable educational institutions on Coursera. Start with Introduction to Logic and Critical Thinking from Duke University or Mindware: Critical Thinking for the Information Age from the University of Michigan.

Article sources

University of the People, “ Why is Critical Thinking Important?: A Survival Guide , https://www.uopeople.edu/blog/why-is-critical-thinking-important/.” Accessed May 18, 2023.

Keep reading

Coursera staff.

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• CBE Life Sci Educ
• v.17(1); Spring 2018

Understanding the Complex Relationship between Critical Thinking and Science Reasoning among Undergraduate Thesis Writers

Jason e. dowd.

† Department of Biology, Duke University, Durham, NC 27708

Robert J. Thompson, Jr.

‡ Department of Psychology and Neuroscience, Duke University, Durham, NC 27708

Leslie A. Schiff

§ Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455

Julie A. Reynolds

Associated data.

This study empirically examines the relationship between students’ critical-thinking skills and scientific reasoning as reflected in undergraduate thesis writing in biology. Writing offers a unique window into studying this relationship, and the findings raise potential implications for instruction.

Developing critical-thinking and scientific reasoning skills are core learning objectives of science education, but little empirical evidence exists regarding the interrelationships between these constructs. Writing effectively fosters students’ development of these constructs, and it offers a unique window into studying how they relate. In this study of undergraduate thesis writing in biology at two universities, we examine how scientific reasoning exhibited in writing (assessed using the Biology Thesis Assessment Protocol) relates to general and specific critical-thinking skills (assessed using the California Critical Thinking Skills Test), and we consider implications for instruction. We find that scientific reasoning in writing is strongly related to inference , while other aspects of science reasoning that emerge in writing (epistemological considerations, writing conventions, etc.) are not significantly related to critical-thinking skills. Science reasoning in writing is not merely a proxy for critical thinking. In linking features of students’ writing to their critical-thinking skills, this study 1) provides a bridge to prior work suggesting that engagement in science writing enhances critical thinking and 2) serves as a foundational step for subsequently determining whether instruction focused explicitly on developing critical-thinking skills (particularly inference ) can actually improve students’ scientific reasoning in their writing.

INTRODUCTION

Critical-thinking and scientific reasoning skills are core learning objectives of science education for all students, regardless of whether or not they intend to pursue a career in science or engineering. Consistent with the view of learning as construction of understanding and meaning ( National Research Council, 2000 ), the pedagogical practice of writing has been found to be effective not only in fostering the development of students’ conceptual and procedural knowledge ( Gerdeman et al. , 2007 ) and communication skills ( Clase et al. , 2010 ), but also scientific reasoning ( Reynolds et al. , 2012 ) and critical-thinking skills ( Quitadamo and Kurtz, 2007 ).

Critical thinking and scientific reasoning are similar but different constructs that include various types of higher-order cognitive processes, metacognitive strategies, and dispositions involved in making meaning of information. Critical thinking is generally understood as the broader construct ( Holyoak and Morrison, 2005 ), comprising an array of cognitive processes and dispostions that are drawn upon differentially in everyday life and across domains of inquiry such as the natural sciences, social sciences, and humanities. Scientific reasoning, then, may be interpreted as the subset of critical-thinking skills (cognitive and metacognitive processes and dispositions) that 1) are involved in making meaning of information in scientific domains and 2) support the epistemological commitment to scientific methodology and paradigm(s).

Although there has been an enduring focus in higher education on promoting critical thinking and reasoning as general or “transferable” skills, research evidence provides increasing support for the view that reasoning and critical thinking are also situational or domain specific ( Beyer et al. , 2013 ). Some researchers, such as Lawson (2010) , present frameworks in which science reasoning is characterized explicitly in terms of critical-thinking skills. There are, however, limited coherent frameworks and empirical evidence regarding either the general or domain-specific interrelationships of scientific reasoning, as it is most broadly defined, and critical-thinking skills.

The Vision and Change in Undergraduate Biology Education Initiative provides a framework for thinking about these constructs and their interrelationship in the context of the core competencies and disciplinary practice they describe ( American Association for the Advancement of Science, 2011 ). These learning objectives aim for undergraduates to “understand the process of science, the interdisciplinary nature of the new biology and how science is closely integrated within society; be competent in communication and collaboration; have quantitative competency and a basic ability to interpret data; and have some experience with modeling, simulation and computational and systems level approaches as well as with using large databases” ( Woodin et al. , 2010 , pp. 71–72). This framework makes clear that science reasoning and critical-thinking skills play key roles in major learning outcomes; for example, “understanding the process of science” requires students to engage in (and be metacognitive about) scientific reasoning, and having the “ability to interpret data” requires critical-thinking skills. To help students better achieve these core competencies, we must better understand the interrelationships of their composite parts. Thus, the next step is to determine which specific critical-thinking skills are drawn upon when students engage in science reasoning in general and with regard to the particular scientific domain being studied. Such a determination could be applied to improve science education for both majors and nonmajors through pedagogical approaches that foster critical-thinking skills that are most relevant to science reasoning.

Writing affords one of the most effective means for making thinking visible ( Reynolds et al. , 2012 ) and learning how to “think like” and “write like” disciplinary experts ( Meizlish et al. , 2013 ). As a result, student writing affords the opportunities to both foster and examine the interrelationship of scientific reasoning and critical-thinking skills within and across disciplinary contexts. The purpose of this study was to better understand the relationship between students’ critical-thinking skills and scientific reasoning skills as reflected in the genre of undergraduate thesis writing in biology departments at two research universities, the University of Minnesota and Duke University.

In the following subsections, we discuss in greater detail the constructs of scientific reasoning and critical thinking, as well as the assessment of scientific reasoning in students’ thesis writing. In subsequent sections, we discuss our study design, findings, and the implications for enhancing educational practices.

Critical Thinking

The advances in cognitive science in the 21st century have increased our understanding of the mental processes involved in thinking and reasoning, as well as memory, learning, and problem solving. Critical thinking is understood to include both a cognitive dimension and a disposition dimension (e.g., reflective thinking) and is defined as “purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or contextual considera­tions upon which that judgment is based” ( Facione, 1990, p. 3 ). Although various other definitions of critical thinking have been proposed, researchers have generally coalesced on this consensus: expert view ( Blattner and Frazier, 2002 ; Condon and Kelly-Riley, 2004 ; Bissell and Lemons, 2006 ; Quitadamo and Kurtz, 2007 ) and the corresponding measures of critical-­thinking skills ( August, 2016 ; Stephenson and Sadler-McKnight, 2016 ).

Both the cognitive skills and dispositional components of critical thinking have been recognized as important to science education ( Quitadamo and Kurtz, 2007 ). Empirical research demonstrates that specific pedagogical practices in science courses are effective in fostering students’ critical-thinking skills. Quitadamo and Kurtz (2007) found that students who engaged in a laboratory writing component in the context of a general education biology course significantly improved their overall critical-thinking skills (and their analytical and inference skills, in particular), whereas students engaged in a traditional quiz-based laboratory did not improve their critical-thinking skills. In related work, Quitadamo et al. (2008) found that a community-based inquiry experience, involving inquiry, writing, research, and analysis, was associated with improved critical thinking in a biology course for nonmajors, compared with traditionally taught sections. In both studies, students who exhibited stronger presemester critical-thinking skills exhibited stronger gains, suggesting that “students who have not been explicitly taught how to think critically may not reach the same potential as peers who have been taught these skills” ( Quitadamo and Kurtz, 2007 , p. 151).

Recently, Stephenson and Sadler-McKnight (2016) found that first-year general chemistry students who engaged in a science writing heuristic laboratory, which is an inquiry-based, writing-to-learn approach to instruction ( Hand and Keys, 1999 ), had significantly greater gains in total critical-thinking scores than students who received traditional laboratory instruction. Each of the four components—inquiry, writing, collaboration, and reflection—have been linked to critical thinking ( Stephenson and Sadler-McKnight, 2016 ). Like the other studies, this work highlights the value of targeting critical-thinking skills and the effectiveness of an inquiry-based, writing-to-learn approach to enhance critical thinking. Across studies, authors advocate adopting critical thinking as the course framework ( Pukkila, 2004 ) and developing explicit examples of how critical thinking relates to the scientific method ( Miri et al. , 2007 ).

In these examples, the important connection between writing and critical thinking is highlighted by the fact that each intervention involves the incorporation of writing into science, technology, engineering, and mathematics education (either alone or in combination with other pedagogical practices). However, critical-thinking skills are not always the primary learning outcome; in some contexts, scientific reasoning is the primary outcome that is assessed.

Scientific Reasoning

Scientific reasoning is a complex process that is broadly defined as “the skills involved in inquiry, experimentation, evidence evaluation, and inference that are done in the service of conceptual change or scientific understanding” ( Zimmerman, 2007 , p. 172). Scientific reasoning is understood to include both conceptual knowledge and the cognitive processes involved with generation of hypotheses (i.e., inductive processes involved in the generation of hypotheses and the deductive processes used in the testing of hypotheses), experimentation strategies, and evidence evaluation strategies. These dimensions are interrelated, in that “experimentation and inference strategies are selected based on prior conceptual knowledge of the domain” ( Zimmerman, 2000 , p. 139). Furthermore, conceptual and procedural knowledge and cognitive process dimensions can be general and domain specific (or discipline specific).

With regard to conceptual knowledge, attention has been focused on the acquisition of core methodological concepts fundamental to scientists’ causal reasoning and metacognitive distancing (or decontextualized thinking), which is the ability to reason independently of prior knowledge or beliefs ( Greenhoot et al. , 2004 ). The latter involves what Kuhn and Dean (2004) refer to as the coordination of theory and evidence, which requires that one question existing theories (i.e., prior knowledge and beliefs), seek contradictory evidence, eliminate alternative explanations, and revise one’s prior beliefs in the face of contradictory evidence. Kuhn and colleagues (2008) further elaborate that scientific thinking requires “a mature understanding of the epistemological foundations of science, recognizing scientific knowledge as constructed by humans rather than simply discovered in the world,” and “the ability to engage in skilled argumentation in the scientific domain, with an appreciation of argumentation as entailing the coordination of theory and evidence” ( Kuhn et al. , 2008 , p. 435). “This approach to scientific reasoning not only highlights the skills of generating and evaluating evidence-based inferences, but also encompasses epistemological appreciation of the functions of evidence and theory” ( Ding et al. , 2016 , p. 616). Evaluating evidence-based inferences involves epistemic cognition, which Moshman (2015) defines as the subset of metacognition that is concerned with justification, truth, and associated forms of reasoning. Epistemic cognition is both general and domain specific (or discipline specific; Moshman, 2015 ).

There is empirical support for the contributions of both prior knowledge and an understanding of the epistemological foundations of science to scientific reasoning. In a study of undergraduate science students, advanced scientific reasoning was most often accompanied by accurate prior knowledge as well as sophisticated epistemological commitments; additionally, for students who had comparable levels of prior knowledge, skillful reasoning was associated with a strong epistemological commitment to the consistency of theory with evidence ( Zeineddin and Abd-El-Khalick, 2010 ). These findings highlight the importance of the need for instructional activities that intentionally help learners develop sophisticated epistemological commitments focused on the nature of knowledge and the role of evidence in supporting knowledge claims ( Zeineddin and Abd-El-Khalick, 2010 ).

Scientific Reasoning in Students’ Thesis Writing

Pedagogical approaches that incorporate writing have also focused on enhancing scientific reasoning. Many rubrics have been developed to assess aspects of scientific reasoning in written artifacts. For example, Timmerman and colleagues (2011) , in the course of describing their own rubric for assessing scientific reasoning, highlight several examples of scientific reasoning assessment criteria ( Haaga, 1993 ; Tariq et al. , 1998 ; Topping et al. , 2000 ; Kelly and Takao, 2002 ; Halonen et al. , 2003 ; Willison and O’Regan, 2007 ).

At both the University of Minnesota and Duke University, we have focused on the genre of the undergraduate honors thesis as the rhetorical context in which to study and improve students’ scientific reasoning and writing. We view the process of writing an undergraduate honors thesis as a form of professional development in the sciences (i.e., a way of engaging students in the practices of a community of discourse). We have found that structured courses designed to scaffold the thesis-­writing process and promote metacognition can improve writing and reasoning skills in biology, chemistry, and economics ( Reynolds and Thompson, 2011 ; Dowd et al. , 2015a , b ). In the context of this prior work, we have defined scientific reasoning in writing as the emergent, underlying construct measured across distinct aspects of students’ written discussion of independent research in their undergraduate theses.

The Biology Thesis Assessment Protocol (BioTAP) was developed at Duke University as a tool for systematically guiding students and faculty through a “draft–feedback–revision” writing process, modeled after professional scientific peer-review processes ( Reynolds et al. , 2009 ). BioTAP includes activities and worksheets that allow students to engage in critical peer review and provides detailed descriptions, presented as rubrics, of the questions (i.e., dimensions, shown in Table 1 ) upon which such review should focus. Nine rubric dimensions focus on communication to the broader scientific community, and four rubric dimensions focus on the accuracy and appropriateness of the research. These rubric dimensions provide criteria by which the thesis is assessed, and therefore allow BioTAP to be used as an assessment tool as well as a teaching resource ( Reynolds et al. , 2009 ). Full details are available at www.science-writing.org/biotap.html .

Theses assessment protocol dimensions

In previous work, we have used BioTAP to quantitatively assess students’ undergraduate honors theses and explore the relationship between thesis-writing courses (or specific interventions within the courses) and the strength of students’ science reasoning in writing across different science disciplines: biology ( Reynolds and Thompson, 2011 ); chemistry ( Dowd et al. , 2015b ); and economics ( Dowd et al. , 2015a ). We have focused exclusively on the nine dimensions related to reasoning and writing (questions 1–9), as the other four dimensions (questions 10–13) require topic-specific expertise and are intended to be used by the student’s thesis supervisor.

Beyond considering individual dimensions, we have investigated whether meaningful constructs underlie students’ thesis scores. We conducted exploratory factor analysis of students’ theses in biology, economics, and chemistry and found one dominant underlying factor in each discipline; we termed the factor “scientific reasoning in writing” ( Dowd et al. , 2015a , b , 2016 ). That is, each of the nine dimensions could be understood as reflecting, in different ways and to different degrees, the construct of scientific reasoning in writing. The findings indicated evidence of both general and discipline-specific components to scientific reasoning in writing that relate to epistemic beliefs and paradigms, in keeping with broader ideas about science reasoning discussed earlier. Specifically, scientific reasoning in writing is more strongly associated with formulating a compelling argument for the significance of the research in the context of current literature in biology, making meaning regarding the implications of the findings in chemistry, and providing an organizational framework for interpreting the thesis in economics. We suggested that instruction, whether occurring in writing studios or in writing courses to facilitate thesis preparation, should attend to both components.

Research Question and Study Design

The genre of thesis writing combines the pedagogies of writing and inquiry found to foster scientific reasoning ( Reynolds et al. , 2012 ) and critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-­McKnight, 2016 ). However, there is no empirical evidence regarding the general or domain-specific interrelationships of scientific reasoning and critical-thinking skills, particularly in the rhetorical context of the undergraduate thesis. The BioTAP studies discussed earlier indicate that the rubric-based assessment produces evidence of scientific reasoning in the undergraduate thesis, but it was not designed to foster or measure critical thinking. The current study was undertaken to address the research question: How are students’ critical-thinking skills related to scientific reasoning as reflected in the genre of undergraduate thesis writing in biology? Determining these interrelationships could guide efforts to enhance students’ scientific reasoning and writing skills through focusing instruction on specific critical-thinking skills as well as disciplinary conventions.

To address this research question, we focused on undergraduate thesis writers in biology courses at two institutions, Duke University and the University of Minnesota, and examined the extent to which students’ scientific reasoning in writing, assessed in the undergraduate thesis using BioTAP, corresponds to students’ critical-thinking skills, assessed using the California Critical Thinking Skills Test (CCTST; August, 2016 ).

Study Sample

The study sample was composed of students enrolled in courses designed to scaffold the thesis-writing process in the Department of Biology at Duke University and the College of Biological Sciences at the University of Minnesota. Both courses complement students’ individual work with research advisors. The course is required for thesis writers at the University of Minnesota and optional for writers at Duke University. Not all students are required to complete a thesis, though it is required for students to graduate with honors; at the University of Minnesota, such students are enrolled in an honors program within the college. In total, 28 students were enrolled in the course at Duke University and 44 students were enrolled in the course at the University of Minnesota. Of those students, two students did not consent to participate in the study; additionally, five students did not validly complete the CCTST (i.e., attempted fewer than 60% of items or completed the test in less than 15 minutes). Thus, our overall rate of valid participation is 90%, with 27 students from Duke University and 38 students from the University of Minnesota. We found no statistically significant differences in thesis assessment between students with valid CCTST scores and invalid CCTST scores. Therefore, we focus on the 65 students who consented to participate and for whom we have complete and valid data in most of this study. Additionally, in asking students for their consent to participate, we allowed them to choose whether to provide or decline access to academic and demographic background data. Of the 65 students who consented to participate, 52 students granted access to such data. Therefore, for additional analyses involving academic and background data, we focus on the 52 students who consented. We note that the 13 students who participated but declined to share additional data performed slightly lower on the CCTST than the 52 others (perhaps suggesting that they differ by other measures, but we cannot determine this with certainty). Among the 52 students, 60% identified as female and 10% identified as being from underrepresented ethnicities.

In both courses, students completed the CCTST online, either in class or on their own, late in the Spring 2016 semester. This is the same assessment that was used in prior studies of critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-McKnight, 2016 ). It is “an objective measure of the core reasoning skills needed for reflective decision making concerning what to believe or what to do” ( Insight Assessment, 2016a ). In the test, students are asked to read and consider information as they answer multiple-choice questions. The questions are intended to be appropriate for all users, so there is no expectation of prior disciplinary knowledge in biology (or any other subject). Although actual test items are protected, sample items are available on the Insight Assessment website ( Insight Assessment, 2016b ). We have included one sample item in the Supplemental Material.

The CCTST is based on a consensus definition of critical thinking, measures cognitive and metacognitive skills associated with critical thinking, and has been evaluated for validity and reliability at the college level ( August, 2016 ; Stephenson and Sadler-McKnight, 2016 ). In addition to providing overall critical-thinking score, the CCTST assesses seven dimensions of critical thinking: analysis, interpretation, inference, evaluation, explanation, induction, and deduction. Scores on each dimension are calculated based on students’ performance on items related to that dimension. Analysis focuses on identifying assumptions, reasons, and claims and examining how they interact to form arguments. Interpretation, related to analysis, focuses on determining the precise meaning and significance of information. Inference focuses on drawing conclusions from reasons and evidence. Evaluation focuses on assessing the credibility of sources of information and claims they make. Explanation, related to evaluation, focuses on describing the evidence, assumptions, or rationale for beliefs and conclusions. Induction focuses on drawing inferences about what is probably true based on evidence. Deduction focuses on drawing conclusions about what must be true when the context completely determines the outcome. These are not independent dimensions; the fact that they are related supports their collective interpretation as critical thinking. Together, the CCTST dimensions provide a basis for evaluating students’ overall strength in using reasoning to form reflective judgments about what to believe or what to do ( August, 2016 ). Each of the seven dimensions and the overall CCTST score are measured on a scale of 0–100, where higher scores indicate superior performance. Scores correspond to superior (86–100), strong (79–85), moderate (70–78), weak (63–69), or not manifested (62 and below) skills.

Scientific Reasoning in Writing

At the end of the semester, students’ final, submitted undergraduate theses were assessed using BioTAP, which consists of nine rubric dimensions that focus on communication to the broader scientific community and four additional dimensions that focus on the exhibition of topic-specific expertise ( Reynolds et al. , 2009 ). These dimensions, framed as questions, are displayed in Table 1 .

Student theses were assessed on questions 1–9 of BioTAP using the same procedures described in previous studies ( Reynolds and Thompson, 2011 ; Dowd et al. , 2015a , b ). In this study, six raters were trained in the valid, reliable use of BioTAP rubrics. Each dimension was rated on a five-point scale: 1 indicates the dimension is missing, incomplete, or below acceptable standards; 3 indicates that the dimension is adequate but not exhibiting mastery; and 5 indicates that the dimension is excellent and exhibits mastery (intermediate ratings of 2 and 4 are appropriate when different parts of the thesis make a single category challenging). After training, two raters independently assessed each thesis and then discussed their independent ratings with one another to form a consensus rating. The consensus score is not an average score, but rather an agreed-upon, discussion-based score. On a five-point scale, raters independently assessed dimensions to be within 1 point of each other 82.4% of the time before discussion and formed consensus ratings 100% of the time after discussion.

In this study, we consider both categorical (mastery/nonmastery, where a score of 5 corresponds to mastery) and numerical treatments of individual BioTAP scores to better relate the manifestation of critical thinking in BioTAP assessment to all of the prior studies. For comprehensive/cumulative measures of BioTAP, we focus on the partial sum of questions 1–5, as these questions relate to higher-order scientific reasoning (whereas questions 6–9 relate to mid- and lower-order writing mechanics [ Reynolds et al. , 2009 ]), and the factor scores (i.e., numerical representations of the extent to which each student exhibits the underlying factor), which are calculated from the factor loadings published by Dowd et al. (2016) . We do not focus on questions 6–9 individually in statistical analyses, because we do not expect critical-thinking skills to relate to mid- and lower-order writing skills.

The final, submitted thesis reflects the student’s writing, the student’s scientific reasoning, the quality of feedback provided to the student by peers and mentors, and the student’s ability to incorporate that feedback into his or her work. Therefore, our assessment is not the same as an assessment of unpolished, unrevised samples of students’ written work. While one might imagine that such an unpolished sample may be more strongly correlated with critical-thinking skills measured by the CCTST, we argue that the complete, submitted thesis, assessed using BioTAP, is ultimately a more appropriate reflection of how students exhibit science reasoning in the scientific community.

Statistical Analyses

We took several steps to analyze the collected data. First, to provide context for subsequent interpretations, we generated descriptive statistics for the CCTST scores of the participants based on the norms for undergraduate CCTST test takers. To determine the strength of relationships among CCTST dimensions (including overall score) and the BioTAP dimensions, partial-sum score (questions 1–5), and factor score, we calculated Pearson’s correlations for each pair of measures. To examine whether falling on one side of the nonmastery/mastery threshold (as opposed to a linear scale of performance) was related to critical thinking, we grouped BioTAP dimensions into categories (mastery/nonmastery) and conducted Student’s t tests to compare the means scores of the two groups on each of the seven dimensions and overall score of the CCTST. Finally, for the strongest relationship that emerged, we included additional academic and background variables as covariates in multiple linear-regression analysis to explore questions about how much observed relationships between critical-thinking skills and science reasoning in writing might be explained by variation in these other factors.

Although BioTAP scores represent discreet, ordinal bins, the five-point scale is intended to capture an underlying continuous construct (from inadequate to exhibiting mastery). It has been argued that five categories is an appropriate cutoff for treating ordinal variables as pseudo-continuous ( Rhemtulla et al. , 2012 )—and therefore using continuous-variable statistical methods (e.g., Pearson’s correlations)—as long as the underlying assumption that ordinal scores are linearly distributed is valid. Although we have no way to statistically test this assumption, we interpret adequate scores to be approximately halfway between inadequate and mastery scores, resulting in a linear scale. In part because this assumption is subject to disagreement, we also consider and interpret a categorical (mastery/nonmastery) treatment of BioTAP variables.

We corrected for multiple comparisons using the Holm-Bonferroni method ( Holm, 1979 ). At the most general level, where we consider the single, comprehensive measures for BioTAP (partial-sum and factor score) and the CCTST (overall score), there is no need to correct for multiple comparisons, because the multiple, individual dimensions are collapsed into single dimensions. When we considered individual CCTST dimensions in relation to comprehensive measures for BioTAP, we accounted for seven comparisons; similarly, when we considered individual dimensions of BioTAP in relation to overall CCTST score, we accounted for five comparisons. When all seven CCTST and five BioTAP dimensions were examined individually and without prior knowledge, we accounted for 35 comparisons; such a rigorous threshold is likely to reject weak and moderate relationships, but it is appropriate if there are no specific pre-existing hypotheses. All p values are presented in tables for complete transparency, and we carefully consider the implications of our interpretation of these data in the Discussion section.

CCTST scores for students in this sample ranged from the 39th to 99th percentile of the general population of undergraduate CCTST test takers (mean percentile = 84.3, median = 85th percentile; Table 2 ); these percentiles reflect overall scores that range from moderate to superior. Scores on individual dimensions and overall scores were sufficiently normal and far enough from the ceiling of the scale to justify subsequent statistical analyses.

Descriptive statistics of CCTST dimensions a

a Scores correspond to superior (86–100), strong (79–85), moderate (70–78), weak (63–69), or not manifested (62 and lower) skills.

The Pearson’s correlations between students’ cumulative scores on BioTAP (the factor score based on loadings published by Dowd et al. , 2016 , and the partial sum of scores on questions 1–5) and students’ overall scores on the CCTST are presented in Table 3 . We found that the partial-sum measure of BioTAP was significantly related to the overall measure of critical thinking ( r = 0.27, p = 0.03), while the BioTAP factor score was marginally related to overall CCTST ( r = 0.24, p = 0.05). When we looked at relationships between comprehensive BioTAP measures and scores for individual dimensions of the CCTST ( Table 3 ), we found significant positive correlations between the both BioTAP partial-sum and factor scores and CCTST inference ( r = 0.45, p < 0.001, and r = 0.41, p < 0.001, respectively). Although some other relationships have p values below 0.05 (e.g., the correlations between BioTAP partial-sum scores and CCTST induction and interpretation scores), they are not significant when we correct for multiple comparisons.

Correlations between dimensions of CCTST and dimensions of BioTAP a

a In each cell, the top number is the correlation, and the bottom, italicized number is the associated p value. Correlations that are statistically significant after correcting for multiple comparisons are shown in bold.

b This is the partial sum of BioTAP scores on questions 1–5.

c This is the factor score calculated from factor loadings published by Dowd et al. (2016) .

When we expanded comparisons to include all 35 potential correlations among individual BioTAP and CCTST dimensions—and, accordingly, corrected for 35 comparisons—we did not find any additional statistically significant relationships. The Pearson’s correlations between students’ scores on each dimension of BioTAP and students’ scores on each dimension of the CCTST range from −0.11 to 0.35 ( Table 3 ); although the relationship between discussion of implications (BioTAP question 5) and inference appears to be relatively large ( r = 0.35), it is not significant ( p = 0.005; the Holm-Bonferroni cutoff is 0.00143). We found no statistically significant relationships between BioTAP questions 6–9 and CCTST dimensions (unpublished data), regardless of whether we correct for multiple comparisons.

The results of Student’s t tests comparing scores on each dimension of the CCTST of students who exhibit mastery with those of students who do not exhibit mastery on each dimension of BioTAP are presented in Table 4 . Focusing first on the overall CCTST scores, we found that the difference between those who exhibit mastery and those who do not in discussing implications of results (BioTAP question 5) is statistically significant ( t = 2.73, p = 0.008, d = 0.71). When we expanded t tests to include all 35 comparisons—and, like above, corrected for 35 comparisons—we found a significant difference in inference scores between students who exhibit mastery on question 5 and students who do not ( t = 3.41, p = 0.0012, d = 0.88), as well as a marginally significant difference in these students’ induction scores ( t = 3.26, p = 0.0018, d = 0.84; the Holm-Bonferroni cutoff is p = 0.00147). Cohen’s d effect sizes, which reveal the strength of the differences for statistically significant relationships, range from 0.71 to 0.88.

The t statistics and effect sizes of differences in ­dimensions of CCTST across dimensions of BioTAP a

a In each cell, the top number is the t statistic for each comparison, and the middle, italicized number is the associated p value. The bottom number is the effect size. Correlations that are statistically significant after correcting for multiple comparisons are shown in bold.

Finally, we more closely examined the strongest relationship that we observed, which was between the CCTST dimension of inference and the BioTAP partial-sum composite score (shown in Table 3 ), using multiple regression analysis ( Table 5 ). Focusing on the 52 students for whom we have background information, we looked at the simple relationship between BioTAP and inference (model 1), a robust background model including multiple covariates that one might expect to explain some part of the variation in BioTAP (model 2), and a combined model including all variables (model 3). As model 3 shows, the covariates explain very little variation in BioTAP scores, and the relationship between inference and BioTAP persists even in the presence of all of the covariates.

Partial sum (questions 1–5) of BioTAP scores ( n = 52)

** p < 0.01.

*** p < 0.001.

The aim of this study was to examine the extent to which the various components of scientific reasoning—manifested in writing in the genre of undergraduate thesis and assessed using BioTAP—draw on general and specific critical-thinking skills (assessed using CCTST) and to consider the implications for educational practices. Although science reasoning involves critical-thinking skills, it also relates to conceptual knowledge and the epistemological foundations of science disciplines ( Kuhn et al. , 2008 ). Moreover, science reasoning in writing , captured in students’ undergraduate theses, reflects habits, conventions, and the incorporation of feedback that may alter evidence of individuals’ critical-thinking skills. Our findings, however, provide empirical evidence that cumulative measures of science reasoning in writing are nonetheless related to students’ overall critical-thinking skills ( Table 3 ). The particularly significant roles of inference skills ( Table 3 ) and the discussion of implications of results (BioTAP question 5; Table 4 ) provide a basis for more specific ideas about how these constructs relate to one another and what educational interventions may have the most success in fostering these skills.

Our results build on previous findings. The genre of thesis writing combines pedagogies of writing and inquiry found to foster scientific reasoning ( Reynolds et al. , 2012 ) and critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-McKnight, 2016 ). Quitadamo and Kurtz (2007) reported that students who engaged in a laboratory writing component in a general education biology course significantly improved their inference and analysis skills, and Quitadamo and colleagues (2008) found that participation in a community-based inquiry biology course (that included a writing component) was associated with significant gains in students’ inference and evaluation skills. The shared focus on inference is noteworthy, because these prior studies actually differ from the current study; the former considered critical-­thinking skills as the primary learning outcome of writing-­focused interventions, whereas the latter focused on emergent links between two learning outcomes (science reasoning in writing and critical thinking). In other words, inference skills are impacted by writing as well as manifested in writing.

Inference focuses on drawing conclusions from argument and evidence. According to the consensus definition of critical thinking, the specific skill of inference includes several processes: querying evidence, conjecturing alternatives, and drawing conclusions. All of these activities are central to the independent research at the core of writing an undergraduate thesis. Indeed, a critical part of what we call “science reasoning in writing” might be characterized as a measure of students’ ability to infer and make meaning of information and findings. Because the cumulative BioTAP measures distill underlying similarities and, to an extent, suppress unique aspects of individual dimensions, we argue that it is appropriate to relate inference to scientific reasoning in writing . Even when we control for other potentially relevant background characteristics, the relationship is strong ( Table 5 ).

In taking the complementary view and focusing on BioTAP, when we compared students who exhibit mastery with those who do not, we found that the specific dimension of “discussing the implications of results” (question 5) differentiates students’ performance on several critical-thinking skills. To achieve mastery on this dimension, students must make connections between their results and other published studies and discuss the future directions of the research; in short, they must demonstrate an understanding of the bigger picture. The specific relationship between question 5 and inference is the strongest observed among all individual comparisons. Altogether, perhaps more than any other BioTAP dimension, this aspect of students’ writing provides a clear view of the role of students’ critical-thinking skills (particularly inference and, marginally, induction) in science reasoning.

While inference and discussion of implications emerge as particularly strongly related dimensions in this work, we note that the strongest contribution to “science reasoning in writing in biology,” as determined through exploratory factor analysis, is “argument for the significance of research” (BioTAP question 2, not question 5; Dowd et al. , 2016 ). Question 2 is not clearly related to critical-thinking skills. These findings are not contradictory, but rather suggest that the epistemological and disciplinary-specific aspects of science reasoning that emerge in writing through BioTAP are not completely aligned with aspects related to critical thinking. In other words, science reasoning in writing is not simply a proxy for those critical-thinking skills that play a role in science reasoning.

In a similar vein, the content-related, epistemological aspects of science reasoning, as well as the conventions associated with writing the undergraduate thesis (including feedback from peers and revision), may explain the lack of significant relationships between some science reasoning dimensions and some critical-thinking skills that might otherwise seem counterintuitive (e.g., BioTAP question 2, which relates to making an argument, and the critical-thinking skill of argument). It is possible that an individual’s critical-thinking skills may explain some variation in a particular BioTAP dimension, but other aspects of science reasoning and practice exert much stronger influence. Although these relationships do not emerge in our analyses, the lack of significant correlation does not mean that there is definitively no correlation. Correcting for multiple comparisons suppresses type 1 error at the expense of exacerbating type 2 error, which, combined with the limited sample size, constrains statistical power and makes weak relationships more difficult to detect. Ultimately, though, the relationships that do emerge highlight places where individuals’ distinct critical-thinking skills emerge most coherently in thesis assessment, which is why we are particularly interested in unpacking those relationships.

We recognize that, because only honors students submit theses at these institutions, this study sample is composed of a selective subset of the larger population of biology majors. Although this is an inherent limitation of focusing on thesis writing, links between our findings and results of other studies (with different populations) suggest that observed relationships may occur more broadly. The goal of improved science reasoning and critical thinking is shared among all biology majors, particularly those engaged in capstone research experiences. So while the implications of this work most directly apply to honors thesis writers, we provisionally suggest that all students could benefit from further study of them.

There are several important implications of this study for science education practices. Students’ inference skills relate to the understanding and effective application of scientific content. The fact that we find no statistically significant relationships between BioTAP questions 6–9 and CCTST dimensions suggests that such mid- to lower-order elements of BioTAP ( Reynolds et al. , 2009 ), which tend to be more structural in nature, do not focus on aspects of the finished thesis that draw strongly on critical thinking. In keeping with prior analyses ( Reynolds and Thompson, 2011 ; Dowd et al. , 2016 ), these findings further reinforce the notion that disciplinary instructors, who are most capable of teaching and assessing scientific reasoning and perhaps least interested in the more mechanical aspects of writing, may nonetheless be best suited to effectively model and assess students’ writing.

The goal of the thesis writing course at both Duke University and the University of Minnesota is not merely to improve thesis scores but to move students’ writing into the category of mastery across BioTAP dimensions. Recognizing that students with differing critical-thinking skills (particularly inference) are more or less likely to achieve mastery in the undergraduate thesis (particularly in discussing implications [question 5]) is important for developing and testing targeted pedagogical interventions to improve learning outcomes for all students.

The competencies characterized by the Vision and Change in Undergraduate Biology Education Initiative provide a general framework for recognizing that science reasoning and critical-thinking skills play key roles in major learning outcomes of science education. Our findings highlight places where science reasoning–related competencies (like “understanding the process of science”) connect to critical-thinking skills and places where critical thinking–related competencies might be manifested in scientific products (such as the ability to discuss implications in scientific writing). We encourage broader efforts to build empirical connections between competencies and pedagogical practices to further improve science education.

One specific implication of this work for science education is to focus on providing opportunities for students to develop their critical-thinking skills (particularly inference). Of course, as this correlational study is not designed to test causality, we do not claim that enhancing students’ inference skills will improve science reasoning in writing. However, as prior work shows that science writing activities influence students’ inference skills ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ), there is reason to test such a hypothesis. Nevertheless, the focus must extend beyond inference as an isolated skill; rather, it is important to relate inference to the foundations of the scientific method ( Miri et al. , 2007 ) in terms of the epistemological appreciation of the functions and coordination of evidence ( Kuhn and Dean, 2004 ; Zeineddin and Abd-El-Khalick, 2010 ; Ding et al. , 2016 ) and disciplinary paradigms of truth and justification ( Moshman, 2015 ).

Although this study is limited to the domain of biology at two institutions with a relatively small number of students, the findings represent a foundational step in the direction of achieving success with more integrated learning outcomes. Hopefully, it will spur greater interest in empirically grounding discussions of the constructs of scientific reasoning and critical-thinking skills.

This study contributes to the efforts to improve science education, for both majors and nonmajors, through an empirically driven analysis of the relationships between scientific reasoning reflected in the genre of thesis writing and critical-thinking skills. This work is rooted in the usefulness of BioTAP as a method 1) to facilitate communication and learning and 2) to assess disciplinary-specific and general dimensions of science reasoning. The findings support the important role of the critical-thinking skill of inference in scientific reasoning in writing, while also highlighting ways in which other aspects of science reasoning (epistemological considerations, writing conventions, etc.) are not significantly related to critical thinking. Future research into the impact of interventions focused on specific critical-thinking skills (i.e., inference) for improved science reasoning in writing will build on this work and its implications for science education.

Supplementary Material

Acknowledgments.

We acknowledge the contributions of Kelaine Haas and Alexander Motten to the implementation and collection of data. We also thank Mine Çetinkaya-­Rundel for her insights regarding our statistical analyses. This research was funded by National Science Foundation award DUE-1525602.

• American Association for the Advancement of Science. (2011). Vision and change in undergraduate biology education: A call to action . Washington, DC: Retrieved September 26, 2017, from https://visionandchange.org/files/2013/11/aaas-VISchange-web1113.pdf . [ Google Scholar ]
• August D. (2016). California Critical Thinking Skills Test user manual and resource guide . San Jose: Insight Assessment/California Academic Press. [ Google Scholar ]
• Beyer C. H., Taylor E., Gillmore G. M. (2013). Inside the undergraduate teaching experience: The University of Washington’s growth in faculty teaching study . Albany, NY: SUNY Press. [ Google Scholar ]
• Bissell A. N., Lemons P. P. (2006). A new method for assessing critical thinking in the classroom . BioScience , ( 1 ), 66–72. https://doi.org/10.1641/0006-3568(2006)056[0066:ANMFAC]2.0.CO;2 . [ Google Scholar ]
• Blattner N. H., Frazier C. L. (2002). Developing a performance-based assessment of students’ critical thinking skills . Assessing Writing , ( 1 ), 47–64. [ Google Scholar ]
• Clase K. L., Gundlach E., Pelaez N. J. (2010). Calibrated peer review for computer-assisted learning of biological research competencies . Biochemistry and Molecular Biology Education , ( 5 ), 290–295. [ PubMed ] [ Google Scholar ]
• Condon W., Kelly-Riley D. (2004). Assessing and teaching what we value: The relationship between college-level writing and critical thinking abilities . Assessing Writing , ( 1 ), 56–75. https://doi.org/10.1016/j.asw.2004.01.003 . [ Google Scholar ]
• Ding L., Wei X., Liu X. (2016). Variations in university students’ scientific reasoning skills across majors, years, and types of institutions . Research in Science Education , ( 5 ), 613–632. https://doi.org/10.1007/s11165-015-9473-y . [ Google Scholar ]
• Dowd J. E., Connolly M. P., Thompson R. J., Jr., Reynolds J. A. (2015a). Improved reasoning in undergraduate writing through structured workshops . Journal of Economic Education , ( 1 ), 14–27. https://doi.org/10.1080/00220485.2014.978924 . [ Google Scholar ]
• Dowd J. E., Roy C. P., Thompson R. J., Jr., Reynolds J. A. (2015b). “On course” for supporting expanded participation and improving scientific reasoning in undergraduate thesis writing . Journal of Chemical Education , ( 1 ), 39–45. https://doi.org/10.1021/ed500298r . [ Google Scholar ]
• Dowd J. E., Thompson R. J., Jr., Reynolds J. A. (2016). Quantitative genre analysis of undergraduate theses: Uncovering different ways of writing and thinking in science disciplines . WAC Journal , , 36–51. [ Google Scholar ]
• Facione P. A. (1990). Critical thinking: a statement of expert consensus for purposes of educational assessment and instruction. Research findings and recommendations . Newark, DE: American Philosophical Association; Retrieved September 26, 2017, from https://philpapers.org/archive/FACCTA.pdf . [ Google Scholar ]
• Gerdeman R. D., Russell A. A., Worden K. J., Gerdeman R. D., Russell A. A., Worden K. J. (2007). Web-based student writing and reviewing in a large biology lecture course . Journal of College Science Teaching , ( 5 ), 46–52. [ Google Scholar ]
• Greenhoot A. F., Semb G., Colombo J., Schreiber T. (2004). Prior beliefs and methodological concepts in scientific reasoning . Applied Cognitive Psychology , ( 2 ), 203–221. https://doi.org/10.1002/acp.959 . [ Google Scholar ]
• Haaga D. A. F. (1993). Peer review of term papers in graduate psychology courses . Teaching of Psychology , ( 1 ), 28–32. https://doi.org/10.1207/s15328023top2001_5 . [ Google Scholar ]
• Halonen J. S., Bosack T., Clay S., McCarthy M., Dunn D. S., Hill G. W., Whitlock K. (2003). A rubric for learning, teaching, and assessing scientific inquiry in psychology . Teaching of Psychology , ( 3 ), 196–208. https://doi.org/10.1207/S15328023TOP3003_01 . [ Google Scholar ]
• Hand B., Keys C. W. (1999). Inquiry investigation . Science Teacher , ( 4 ), 27–29. [ Google Scholar ]
• Holm S. (1979). A simple sequentially rejective multiple test procedure . Scandinavian Journal of Statistics , ( 2 ), 65–70. [ Google Scholar ]
• Holyoak K. J., Morrison R. G. (2005). The Cambridge handbook of thinking and reasoning . New York: Cambridge University Press. [ Google Scholar ]
• Insight Assessment. (2016a). California Critical Thinking Skills Test (CCTST) Retrieved September 26, 2017, from www.insightassessment.com/Products/Products-Summary/Critical-Thinking-Skills-Tests/California-Critical-Thinking-Skills-Test-CCTST .
• Insight Assessment. (2016b). Sample thinking skills questions. Retrieved September 26, 2017, from www.insightassessment.com/Resources/Teaching-Training-and-Learning-Tools/node_1487 .
• Kelly G. J., Takao A. (2002). Epistemic levels in argument: An analysis of university oceanography students’ use of evidence in writing . Science Education , ( 3 ), 314–342. https://doi.org/10.1002/sce.10024 . [ Google Scholar ]
• Kuhn D., Dean D., Jr. (2004). Connecting scientific reasoning and causal inference . Journal of Cognition and Development , ( 2 ), 261–288. https://doi.org/10.1207/s15327647jcd0502_5 . [ Google Scholar ]
• Kuhn D., Iordanou K., Pease M., Wirkala C. (2008). Beyond control of variables: What needs to develop to achieve skilled scientific thinking? . Cognitive Development , ( 4 ), 435–451. https://doi.org/10.1016/j.cogdev.2008.09.006 . [ Google Scholar ]
• Lawson A. E. (2010). Basic inferences of scientific reasoning, argumentation, and discovery . Science Education , ( 2 ), 336–364. https://doi.org/­10.1002/sce.20357 . [ Google Scholar ]
• Meizlish D., LaVaque-Manty D., Silver N., Kaplan M. (2013). Think like/write like: Metacognitive strategies to foster students’ development as disciplinary thinkers and writers . In Thompson R. J. (Ed.), Changing the conversation about higher education (pp. 53–73). Lanham, MD: Rowman & Littlefield. [ Google Scholar ]
• Miri B., David B.-C., Uri Z. (2007). Purposely teaching for the promotion of higher-order thinking skills: A case of critical thinking . Research in Science Education , ( 4 ), 353–369. https://doi.org/10.1007/s11165-006-9029-2 . [ Google Scholar ]
• Moshman D. (2015). Epistemic cognition and development: The psychology of justification and truth . New York: Psychology Press. [ Google Scholar ]
• National Research Council. (2000). How people learn: Brain, mind, experience, and school . Expanded ed. Washington, DC: National Academies Press. [ Google Scholar ]
• Pukkila P. J. (2004). Introducing student inquiry in large introductory genetics classes . Genetics , ( 1 ), 11–18. https://doi.org/10.1534/genetics.166.1.11 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Quitadamo I. J., Faiola C. L., Johnson J. E., Kurtz M. J. (2008). Community-based inquiry improves critical thinking in general education biology . CBE—Life Sciences Education , ( 3 ), 327–337. https://doi.org/10.1187/cbe.07-11-0097 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Quitadamo I. J., Kurtz M. J. (2007). Learning to improve: Using writing to increase critical thinking performance in general education biology . CBE—Life Sciences Education , ( 2 ), 140–154. https://doi.org/10.1187/cbe.06-11-0203 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Reynolds J. A., Smith R., Moskovitz C., Sayle A. (2009). BioTAP: A systematic approach to teaching scientific writing and evaluating undergraduate theses . BioScience , ( 10 ), 896–903. https://doi.org/10.1525/bio.2009.59.10.11 . [ Google Scholar ]
• Reynolds J. A., Thaiss C., Katkin W., Thompson R. J. (2012). Writing-to-learn in undergraduate science education: A community-based, conceptually driven approach . CBE—Life Sciences Education , ( 1 ), 17–25. https://doi.org/10.1187/cbe.11-08-0064 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Reynolds J. A., Thompson R. J. (2011). Want to improve undergraduate thesis writing? Engage students and their faculty readers in scientific peer review . CBE—Life Sciences Education , ( 2 ), 209–215. https://doi.org/­10.1187/cbe.10-10-0127 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rhemtulla M., Brosseau-Liard P. E., Savalei V. (2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions . Psychological Methods , ( 3 ), 354–373. https://doi.org/­10.1037/a0029315 . [ PubMed ] [ Google Scholar ]
• Stephenson N. S., Sadler-McKnight N. P. (2016). Developing critical thinking skills using the science writing heuristic in the chemistry laboratory . Chemistry Education Research and Practice , ( 1 ), 72–79. https://doi.org/­10.1039/C5RP00102A . [ Google Scholar ]
• Tariq V. N., Stefani L. A. J., Butcher A. C., Heylings D. J. A. (1998). Developing a new approach to the assessment of project work . Assessment and Evaluation in Higher Education , ( 3 ), 221–240. https://doi.org/­10.1080/0260293980230301 . [ Google Scholar ]
• Timmerman B. E. C., Strickland D. C., Johnson R. L., Payne J. R. (2011). Development of a “universal” rubric for assessing undergraduates’ scientific reasoning skills using scientific writing . Assessment and Evaluation in Higher Education , ( 5 ), 509–547. https://doi.org/10.1080/­02602930903540991 . [ Google Scholar ]
• Topping K. J., Smith E. F., Swanson I., Elliot A. (2000). Formative peer assessment of academic writing between postgraduate students . Assessment and Evaluation in Higher Education , ( 2 ), 149–169. https://doi.org/10.1080/713611428 . [ Google Scholar ]
• Willison J., O’Regan K. (2007). Commonly known, commonly not known, totally unknown: A framework for students becoming researchers . Higher Education Research and Development , ( 4 ), 393–409. https://doi.org/10.1080/07294360701658609 . [ Google Scholar ]
• Woodin T., Carter V. C., Fletcher L. (2010). Vision and Change in Biology Undergraduate Education: A Call for Action—Initial responses . CBE—Life Sciences Education , ( 2 ), 71–73. https://doi.org/10.1187/cbe.10-03-0044 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Zeineddin A., Abd-El-Khalick F. (2010). Scientific reasoning and epistemological commitments: Coordination of theory and evidence among college science students . Journal of Research in Science Teaching , ( 9 ), 1064–1093. https://doi.org/10.1002/tea.20368 . [ Google Scholar ]
• Zimmerman C. (2000). The development of scientific reasoning skills . Developmental Review , ( 1 ), 99–149. https://doi.org/10.1006/drev.1999.0497 . [ Google Scholar ]
• Zimmerman C. (2007). The development of scientific thinking skills in elementary and middle school . Developmental Review , ( 2 ), 172–223. https://doi.org/10.1016/j.dr.2006.12.001 . [ Google Scholar ]

Thinking critically on critical thinking: why scientists’ skills need to spread

Lecturer in Psychology, University of Tasmania

Disclosure statement

Rachel Grieve does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Tasmania provides funding as a member of The Conversation AU.

View all partners

MATHS AND SCIENCE EDUCATION: We’ve asked our authors about the state of maths and science education in Australia and its future direction. Today, Rachel Grieve discusses why we need to spread science-specific skills into the wider curriculum.

When we think of science and maths, stereotypical visions of lab coats, test-tubes, and formulae often spring to mind.

But more important than these stereotypes are the methods that underpin the work scientists do – namely generating and systematically testing hypotheses. A key part of this is critical thinking.

It’s a skill that often feels in short supply these days, but you don’t necessarily need to study science or maths in order gain it. It’s time to take critical thinking out of the realm of maths and science and broaden it into students’ general education.

What is critical thinking?

Critical thinking is a reflective and analytical style of thinking, with its basis in logic, rationality, and synthesis. It means delving deeper and asking questions like: why is that so? Where is the evidence? How good is that evidence? Is this a good argument? Is it biased? Is it verifiable? What are the alternative explanations?

Critical thinking moves us beyond mere description and into the realms of scientific inference and reasoning. This is what enables discoveries to be made and innovations to be fostered.

For many scientists, critical thinking becomes (seemingly) intuitive, but like any skill set, critical thinking needs to be taught and cultivated. Unfortunately, educators are unable to deposit this information directly into their students’ heads. While the theory of critical thinking can be taught, critical thinking itself needs to be experienced first-hand.

So what does this mean for educators trying to incorporate critical thinking within their curricula? We can teach students the theoretical elements of critical thinking. Take for example working through [statistical problems](http://wdeneys.org/data/COGNIT_1695.pdf](http://wdeneys.org/data/COGNIT_1695.pdf) like this one:

In a 1,000-person study, four people said their favourite series was Star Trek and 996 said Days of Our Lives. Jeremy is a randomly chosen participant in this study, is 26, and is doing graduate studies in physics. He stays at home most of the time and likes to play videogames. What is most likely? a. Jeremy’s favourite series is Star Trek b. Jeremy’s favourite series is Days of Our Lives

Some critical thought applied to this problem allows us to know that Jeremy is most likely to prefer Days of Our Lives.

Can you teach it?

It’s well established that statistical training is associated with improved decision-making. But the idea of “teaching” critical thinking is itself an oxymoron: critical thinking can really only be learned through practice. Thus, it is not surprising that student engagement with the critical thinking process itself is what pays the dividends for students.

As such, educators try to connect students with the subject matter outside the lecture theatre or classroom. For example, problem based learning is now widely used in the health sciences, whereby students must figure out the key issues related to a case and direct their own learning to solve that problem. Problem based learning has clear parallels with real life practice for health professionals.

Critical thinking goes beyond what might be on the final exam and life-long learning becomes the key. This is a good thing, as practice helps to improve our ability to think critically over time .

Just for scientists?

For those engaging with science, learning the skills needed to be a critical consumer of information is invaluable. But should these skills remain in the domain of scientists? Clearly not: for those engaging with life, being a critical consumer of information is also invaluable, allowing informed judgement.

Being able to actively consider and evaluate information, identify biases, examine the logic of arguments, and tolerate ambiguity until the evidence is in would allow many people from all backgrounds to make better decisions. While these decisions can be trivial (does that miracle anti-wrinkle cream really do what it claims?), in many cases, reasoning and decision-making can have a substantial impact, with some decisions have life-altering effects. A timely case-in-point is immunisation.

Pushing critical thinking from the realms of science and maths into the broader curriculum may lead to far-reaching outcomes. With increasing access to information on the internet, giving individuals the skills to critically think about that information may have widespread benefit, both personally and socially.

The value of science education might not always be in the facts, but in the thinking.

This is the sixth part of our series Maths and Science Education .

• Maths and science education

Associate Professor, Occupational Therapy

Operations Manager

Senior Lecturer, Occupational Therapy

Lecturer, Occupational Therapy 

Project Offier - Diversity & Inclusion

Change Password

Your password must have 8 characters or more and contain 3 of the following:.

• a lower case character, 
• an upper case character, 
• a special character 

Password Changed Successfully

Your password has been changed

• Sign in / Register

Request Username

Can't sign in? Forgot your username?

Enter your email address below and we will send you your username

If the address matches an existing account you will receive an email with instructions to retrieve your username

Understanding the Complex Relationship between Critical Thinking and Science Reasoning among Undergraduate Thesis Writers

• Jason E. Dowd
• Robert J. Thompson
• Leslie A. Schiff
• Julie A. Reynolds

*Address correspondence to: Jason E. Dowd ( E-mail Address: [email protected] ).

Department of Biology, Duke University, Durham, NC 27708

Search for more papers by this author

Department of Psychology and Neuroscience, Duke University, Durham, NC 27708

Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455

Developing critical-thinking and scientific reasoning skills are core learning objectives of science education, but little empirical evidence exists regarding the interrelationships between these constructs. Writing effectively fosters students’ development of these constructs, and it offers a unique window into studying how they relate. In this study of undergraduate thesis writing in biology at two universities, we examine how scientific reasoning exhibited in writing (assessed using the Biology Thesis Assessment Protocol) relates to general and specific critical-thinking skills (assessed using the California Critical Thinking Skills Test), and we consider implications for instruction. We find that scientific reasoning in writing is strongly related to inference , while other aspects of science reasoning that emerge in writing (epistemological considerations, writing conventions, etc.) are not significantly related to critical-thinking skills. Science reasoning in writing is not merely a proxy for critical thinking. In linking features of students’ writing to their critical-thinking skills, this study 1) provides a bridge to prior work suggesting that engagement in science writing enhances critical thinking and 2) serves as a foundational step for subsequently determining whether instruction focused explicitly on developing critical-thinking skills (particularly inference ) can actually improve students’ scientific reasoning in their writing.

INTRODUCTION

Critical-thinking and scientific reasoning skills are core learning objectives of science education for all students, regardless of whether or not they intend to pursue a career in science or engineering. Consistent with the view of learning as construction of understanding and meaning ( National Research Council, 2000 ), the pedagogical practice of writing has been found to be effective not only in fostering the development of students’ conceptual and procedural knowledge ( Gerdeman et al. , 2007 ) and communication skills ( Clase et al. , 2010 ), but also scientific reasoning ( Reynolds et al. , 2012 ) and critical-thinking skills ( Quitadamo and Kurtz, 2007 ).

Critical thinking and scientific reasoning are similar but different constructs that include various types of higher-order cognitive processes, metacognitive strategies, and dispositions involved in making meaning of information. Critical thinking is generally understood as the broader construct ( Holyoak and Morrison, 2005 ), comprising an array of cognitive processes and dispostions that are drawn upon differentially in everyday life and across domains of inquiry such as the natural sciences, social sciences, and humanities. Scientific reasoning, then, may be interpreted as the subset of critical-thinking skills (cognitive and metacognitive processes and dispositions) that 1) are involved in making meaning of information in scientific domains and 2) support the epistemological commitment to scientific methodology and paradigm(s).

Although there has been an enduring focus in higher education on promoting critical thinking and reasoning as general or “transferable” skills, research evidence provides increasing support for the view that reasoning and critical thinking are also situational or domain specific ( Beyer et al. , 2013 ). Some researchers, such as Lawson (2010) , present frameworks in which science reasoning is characterized explicitly in terms of critical-thinking skills. There are, however, limited coherent frameworks and empirical evidence regarding either the general or domain-specific interrelationships of scientific reasoning, as it is most broadly defined, and critical-thinking skills.

The Vision and Change in Undergraduate Biology Education Initiative provides a framework for thinking about these constructs and their interrelationship in the context of the core competencies and disciplinary practice they describe ( American Association for the Advancement of Science, 2011 ). These learning objectives aim for undergraduates to “understand the process of science, the interdisciplinary nature of the new biology and how science is closely integrated within society; be competent in communication and collaboration; have quantitative competency and a basic ability to interpret data; and have some experience with modeling, simulation and computational and systems level approaches as well as with using large databases” ( Woodin et al. , 2010 , pp. 71–72). This framework makes clear that science reasoning and critical-thinking skills play key roles in major learning outcomes; for example, “understanding the process of science” requires students to engage in (and be metacognitive about) scientific reasoning, and having the “ability to interpret data” requires critical-thinking skills. To help students better achieve these core competencies, we must better understand the interrelationships of their composite parts. Thus, the next step is to determine which specific critical-thinking skills are drawn upon when students engage in science reasoning in general and with regard to the particular scientific domain being studied. Such a determination could be applied to improve science education for both majors and nonmajors through pedagogical approaches that foster critical-thinking skills that are most relevant to science reasoning.

Writing affords one of the most effective means for making thinking visible ( Reynolds et al. , 2012 ) and learning how to “think like” and “write like” disciplinary experts ( Meizlish et al. , 2013 ). As a result, student writing affords the opportunities to both foster and examine the interrelationship of scientific reasoning and critical-thinking skills within and across disciplinary contexts. The purpose of this study was to better understand the relationship between students’ critical-thinking skills and scientific reasoning skills as reflected in the genre of undergraduate thesis writing in biology departments at two research universities, the University of Minnesota and Duke University.

In the following subsections, we discuss in greater detail the constructs of scientific reasoning and critical thinking, as well as the assessment of scientific reasoning in students’ thesis writing. In subsequent sections, we discuss our study design, findings, and the implications for enhancing educational practices.

Critical Thinking

The advances in cognitive science in the 21st century have increased our understanding of the mental processes involved in thinking and reasoning, as well as memory, learning, and problem solving. Critical thinking is understood to include both a cognitive dimension and a disposition dimension (e.g., reflective thinking) and is defined as “purposeful, self-regulatory judgment which results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or contextual considera­tions upon which that judgment is based” ( Facione, 1990, p. 3 ). Although various other definitions of critical thinking have been proposed, researchers have generally coalesced on this consensus: expert view ( Blattner and Frazier, 2002 ; Condon and Kelly-Riley, 2004 ; Bissell and Lemons, 2006 ; Quitadamo and Kurtz, 2007 ) and the corresponding measures of critical-­thinking skills ( August, 2016 ; Stephenson and Sadler-McKnight, 2016 ).

Both the cognitive skills and dispositional components of critical thinking have been recognized as important to science education ( Quitadamo and Kurtz, 2007 ). Empirical research demonstrates that specific pedagogical practices in science courses are effective in fostering students’ critical-thinking skills. Quitadamo and Kurtz (2007) found that students who engaged in a laboratory writing component in the context of a general education biology course significantly improved their overall critical-thinking skills (and their analytical and inference skills, in particular), whereas students engaged in a traditional quiz-based laboratory did not improve their critical-thinking skills. In related work, Quitadamo et al. (2008) found that a community-based inquiry experience, involving inquiry, writing, research, and analysis, was associated with improved critical thinking in a biology course for nonmajors, compared with traditionally taught sections. In both studies, students who exhibited stronger presemester critical-thinking skills exhibited stronger gains, suggesting that “students who have not been explicitly taught how to think critically may not reach the same potential as peers who have been taught these skills” ( Quitadamo and Kurtz, 2007 , p. 151).

Recently, Stephenson and Sadler-McKnight (2016) found that first-year general chemistry students who engaged in a science writing heuristic laboratory, which is an inquiry-based, writing-to-learn approach to instruction ( Hand and Keys, 1999 ), had significantly greater gains in total critical-thinking scores than students who received traditional laboratory instruction. Each of the four components—inquiry, writing, collaboration, and reflection—have been linked to critical thinking ( Stephenson and Sadler-McKnight, 2016 ). Like the other studies, this work highlights the value of targeting critical-thinking skills and the effectiveness of an inquiry-based, writing-to-learn approach to enhance critical thinking. Across studies, authors advocate adopting critical thinking as the course framework ( Pukkila, 2004 ) and developing explicit examples of how critical thinking relates to the scientific method ( Miri et al. , 2007 ).

In these examples, the important connection between writing and critical thinking is highlighted by the fact that each intervention involves the incorporation of writing into science, technology, engineering, and mathematics education (either alone or in combination with other pedagogical practices). However, critical-thinking skills are not always the primary learning outcome; in some contexts, scientific reasoning is the primary outcome that is assessed.

Scientific Reasoning

Scientific reasoning is a complex process that is broadly defined as “the skills involved in inquiry, experimentation, evidence evaluation, and inference that are done in the service of conceptual change or scientific understanding” ( Zimmerman, 2007 , p. 172). Scientific reasoning is understood to include both conceptual knowledge and the cognitive processes involved with generation of hypotheses (i.e., inductive processes involved in the generation of hypotheses and the deductive processes used in the testing of hypotheses), experimentation strategies, and evidence evaluation strategies. These dimensions are interrelated, in that “experimentation and inference strategies are selected based on prior conceptual knowledge of the domain” ( Zimmerman, 2000 , p. 139). Furthermore, conceptual and procedural knowledge and cognitive process dimensions can be general and domain specific (or discipline specific).

With regard to conceptual knowledge, attention has been focused on the acquisition of core methodological concepts fundamental to scientists’ causal reasoning and metacognitive distancing (or decontextualized thinking), which is the ability to reason independently of prior knowledge or beliefs ( Greenhoot et al. , 2004 ). The latter involves what Kuhn and Dean (2004) refer to as the coordination of theory and evidence, which requires that one question existing theories (i.e., prior knowledge and beliefs), seek contradictory evidence, eliminate alternative explanations, and revise one’s prior beliefs in the face of contradictory evidence. Kuhn and colleagues (2008) further elaborate that scientific thinking requires “a mature understanding of the epistemological foundations of science, recognizing scientific knowledge as constructed by humans rather than simply discovered in the world,” and “the ability to engage in skilled argumentation in the scientific domain, with an appreciation of argumentation as entailing the coordination of theory and evidence” ( Kuhn et al. , 2008 , p. 435). “This approach to scientific reasoning not only highlights the skills of generating and evaluating evidence-based inferences, but also encompasses epistemological appreciation of the functions of evidence and theory” ( Ding et al. , 2016 , p. 616). Evaluating evidence-based inferences involves epistemic cognition, which Moshman (2015) defines as the subset of metacognition that is concerned with justification, truth, and associated forms of reasoning. Epistemic cognition is both general and domain specific (or discipline specific; Moshman, 2015 ).

There is empirical support for the contributions of both prior knowledge and an understanding of the epistemological foundations of science to scientific reasoning. In a study of undergraduate science students, advanced scientific reasoning was most often accompanied by accurate prior knowledge as well as sophisticated epistemological commitments; additionally, for students who had comparable levels of prior knowledge, skillful reasoning was associated with a strong epistemological commitment to the consistency of theory with evidence ( Zeineddin and Abd-El-Khalick, 2010 ). These findings highlight the importance of the need for instructional activities that intentionally help learners develop sophisticated epistemological commitments focused on the nature of knowledge and the role of evidence in supporting knowledge claims ( Zeineddin and Abd-El-Khalick, 2010 ).

Scientific Reasoning in Students’ Thesis Writing

Pedagogical approaches that incorporate writing have also focused on enhancing scientific reasoning. Many rubrics have been developed to assess aspects of scientific reasoning in written artifacts. For example, Timmerman and colleagues (2011) , in the course of describing their own rubric for assessing scientific reasoning, highlight several examples of scientific reasoning assessment criteria ( Haaga, 1993 ; Tariq et al. , 1998 ; Topping et al. , 2000 ; Kelly and Takao, 2002 ; Halonen et al. , 2003 ; Willison and O’Regan, 2007 ).

At both the University of Minnesota and Duke University, we have focused on the genre of the undergraduate honors thesis as the rhetorical context in which to study and improve students’ scientific reasoning and writing. We view the process of writing an undergraduate honors thesis as a form of professional development in the sciences (i.e., a way of engaging students in the practices of a community of discourse). We have found that structured courses designed to scaffold the thesis-­writing process and promote metacognition can improve writing and reasoning skills in biology, chemistry, and economics ( Reynolds and Thompson, 2011 ; Dowd et al. , 2015a , b ). In the context of this prior work, we have defined scientific reasoning in writing as the emergent, underlying construct measured across distinct aspects of students’ written discussion of independent research in their undergraduate theses.

The Biology Thesis Assessment Protocol (BioTAP) was developed at Duke University as a tool for systematically guiding students and faculty through a “draft–feedback–revision” writing process, modeled after professional scientific peer-review processes ( Reynolds et al. , 2009 ). BioTAP includes activities and worksheets that allow students to engage in critical peer review and provides detailed descriptions, presented as rubrics, of the questions (i.e., dimensions, shown in Table 1 ) upon which such review should focus. Nine rubric dimensions focus on communication to the broader scientific community, and four rubric dimensions focus on the accuracy and appropriateness of the research. These rubric dimensions provide criteria by which the thesis is assessed, and therefore allow BioTAP to be used as an assessment tool as well as a teaching resource ( Reynolds et al. , 2009 ). Full details are available at www.science-writing.org/biotap.html .

In previous work, we have used BioTAP to quantitatively assess students’ undergraduate honors theses and explore the relationship between thesis-writing courses (or specific interventions within the courses) and the strength of students’ science reasoning in writing across different science disciplines: biology ( Reynolds and Thompson, 2011 ); chemistry ( Dowd et al. , 2015b ); and economics ( Dowd et al. , 2015a ). We have focused exclusively on the nine dimensions related to reasoning and writing (questions 1–9), as the other four dimensions (questions 10–13) require topic-specific expertise and are intended to be used by the student’s thesis supervisor.

Beyond considering individual dimensions, we have investigated whether meaningful constructs underlie students’ thesis scores. We conducted exploratory factor analysis of students’ theses in biology, economics, and chemistry and found one dominant underlying factor in each discipline; we termed the factor “scientific reasoning in writing” ( Dowd et al. , 2015a , b , 2016 ). That is, each of the nine dimensions could be understood as reflecting, in different ways and to different degrees, the construct of scientific reasoning in writing. The findings indicated evidence of both general and discipline-specific components to scientific reasoning in writing that relate to epistemic beliefs and paradigms, in keeping with broader ideas about science reasoning discussed earlier. Specifically, scientific reasoning in writing is more strongly associated with formulating a compelling argument for the significance of the research in the context of current literature in biology, making meaning regarding the implications of the findings in chemistry, and providing an organizational framework for interpreting the thesis in economics. We suggested that instruction, whether occurring in writing studios or in writing courses to facilitate thesis preparation, should attend to both components.

Research Question and Study Design

The genre of thesis writing combines the pedagogies of writing and inquiry found to foster scientific reasoning ( Reynolds et al. , 2012 ) and critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-­McKnight, 2016 ). However, there is no empirical evidence regarding the general or domain-specific interrelationships of scientific reasoning and critical-thinking skills, particularly in the rhetorical context of the undergraduate thesis. The BioTAP studies discussed earlier indicate that the rubric-based assessment produces evidence of scientific reasoning in the undergraduate thesis, but it was not designed to foster or measure critical thinking. The current study was undertaken to address the research question: How are students’ critical-thinking skills related to scientific reasoning as reflected in the genre of undergraduate thesis writing in biology? Determining these interrelationships could guide efforts to enhance students’ scientific reasoning and writing skills through focusing instruction on specific critical-thinking skills as well as disciplinary conventions.

To address this research question, we focused on undergraduate thesis writers in biology courses at two institutions, Duke University and the University of Minnesota, and examined the extent to which students’ scientific reasoning in writing, assessed in the undergraduate thesis using BioTAP, corresponds to students’ critical-thinking skills, assessed using the California Critical Thinking Skills Test (CCTST; August, 2016 ).

Study Sample

The study sample was composed of students enrolled in courses designed to scaffold the thesis-writing process in the Department of Biology at Duke University and the College of Biological Sciences at the University of Minnesota. Both courses complement students’ individual work with research advisors. The course is required for thesis writers at the University of Minnesota and optional for writers at Duke University. Not all students are required to complete a thesis, though it is required for students to graduate with honors; at the University of Minnesota, such students are enrolled in an honors program within the college. In total, 28 students were enrolled in the course at Duke University and 44 students were enrolled in the course at the University of Minnesota. Of those students, two students did not consent to participate in the study; additionally, five students did not validly complete the CCTST (i.e., attempted fewer than 60% of items or completed the test in less than 15 minutes). Thus, our overall rate of valid participation is 90%, with 27 students from Duke University and 38 students from the University of Minnesota. We found no statistically significant differences in thesis assessment between students with valid CCTST scores and invalid CCTST scores. Therefore, we focus on the 65 students who consented to participate and for whom we have complete and valid data in most of this study. Additionally, in asking students for their consent to participate, we allowed them to choose whether to provide or decline access to academic and demographic background data. Of the 65 students who consented to participate, 52 students granted access to such data. Therefore, for additional analyses involving academic and background data, we focus on the 52 students who consented. We note that the 13 students who participated but declined to share additional data performed slightly lower on the CCTST than the 52 others (perhaps suggesting that they differ by other measures, but we cannot determine this with certainty). Among the 52 students, 60% identified as female and 10% identified as being from underrepresented ethnicities.

In both courses, students completed the CCTST online, either in class or on their own, late in the Spring 2016 semester. This is the same assessment that was used in prior studies of critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-McKnight, 2016 ). It is “an objective measure of the core reasoning skills needed for reflective decision making concerning what to believe or what to do” ( Insight Assessment, 2016a ). In the test, students are asked to read and consider information as they answer multiple-choice questions. The questions are intended to be appropriate for all users, so there is no expectation of prior disciplinary knowledge in biology (or any other subject). Although actual test items are protected, sample items are available on the Insight Assessment website ( Insight Assessment, 2016b ). We have included one sample item in the Supplemental Material.

The CCTST is based on a consensus definition of critical thinking, measures cognitive and metacognitive skills associated with critical thinking, and has been evaluated for validity and reliability at the college level ( August, 2016 ; Stephenson and Sadler-McKnight, 2016 ). In addition to providing overall critical-thinking score, the CCTST assesses seven dimensions of critical thinking: analysis, interpretation, inference, evaluation, explanation, induction, and deduction. Scores on each dimension are calculated based on students’ performance on items related to that dimension. Analysis focuses on identifying assumptions, reasons, and claims and examining how they interact to form arguments. Interpretation, related to analysis, focuses on determining the precise meaning and significance of information. Inference focuses on drawing conclusions from reasons and evidence. Evaluation focuses on assessing the credibility of sources of information and claims they make. Explanation, related to evaluation, focuses on describing the evidence, assumptions, or rationale for beliefs and conclusions. Induction focuses on drawing inferences about what is probably true based on evidence. Deduction focuses on drawing conclusions about what must be true when the context completely determines the outcome. These are not independent dimensions; the fact that they are related supports their collective interpretation as critical thinking. Together, the CCTST dimensions provide a basis for evaluating students’ overall strength in using reasoning to form reflective judgments about what to believe or what to do ( August, 2016 ). Each of the seven dimensions and the overall CCTST score are measured on a scale of 0–100, where higher scores indicate superior performance. Scores correspond to superior (86–100), strong (79–85), moderate (70–78), weak (63–69), or not manifested (62 and below) skills.

Scientific Reasoning in Writing

At the end of the semester, students’ final, submitted undergraduate theses were assessed using BioTAP, which consists of nine rubric dimensions that focus on communication to the broader scientific community and four additional dimensions that focus on the exhibition of topic-specific expertise ( Reynolds et al. , 2009 ). These dimensions, framed as questions, are displayed in Table 1 .

Student theses were assessed on questions 1–9 of BioTAP using the same procedures described in previous studies ( Reynolds and Thompson, 2011 ; Dowd et al. , 2015a , b ). In this study, six raters were trained in the valid, reliable use of BioTAP rubrics. Each dimension was rated on a five-point scale: 1 indicates the dimension is missing, incomplete, or below acceptable standards; 3 indicates that the dimension is adequate but not exhibiting mastery; and 5 indicates that the dimension is excellent and exhibits mastery (intermediate ratings of 2 and 4 are appropriate when different parts of the thesis make a single category challenging). After training, two raters independently assessed each thesis and then discussed their independent ratings with one another to form a consensus rating. The consensus score is not an average score, but rather an agreed-upon, discussion-based score. On a five-point scale, raters independently assessed dimensions to be within 1 point of each other 82.4% of the time before discussion and formed consensus ratings 100% of the time after discussion.

In this study, we consider both categorical (mastery/nonmastery, where a score of 5 corresponds to mastery) and numerical treatments of individual BioTAP scores to better relate the manifestation of critical thinking in BioTAP assessment to all of the prior studies. For comprehensive/cumulative measures of BioTAP, we focus on the partial sum of questions 1–5, as these questions relate to higher-order scientific reasoning (whereas questions 6–9 relate to mid- and lower-order writing mechanics [ Reynolds et al. , 2009 ]), and the factor scores (i.e., numerical representations of the extent to which each student exhibits the underlying factor), which are calculated from the factor loadings published by Dowd et al. (2016) . We do not focus on questions 6–9 individually in statistical analyses, because we do not expect critical-thinking skills to relate to mid- and lower-order writing skills.

The final, submitted thesis reflects the student’s writing, the student’s scientific reasoning, the quality of feedback provided to the student by peers and mentors, and the student’s ability to incorporate that feedback into his or her work. Therefore, our assessment is not the same as an assessment of unpolished, unrevised samples of students’ written work. While one might imagine that such an unpolished sample may be more strongly correlated with critical-thinking skills measured by the CCTST, we argue that the complete, submitted thesis, assessed using BioTAP, is ultimately a more appropriate reflection of how students exhibit science reasoning in the scientific community.

Statistical Analyses

We took several steps to analyze the collected data. First, to provide context for subsequent interpretations, we generated descriptive statistics for the CCTST scores of the participants based on the norms for undergraduate CCTST test takers. To determine the strength of relationships among CCTST dimensions (including overall score) and the BioTAP dimensions, partial-sum score (questions 1–5), and factor score, we calculated Pearson’s correlations for each pair of measures. To examine whether falling on one side of the nonmastery/mastery threshold (as opposed to a linear scale of performance) was related to critical thinking, we grouped BioTAP dimensions into categories (mastery/nonmastery) and conducted Student’s t tests to compare the means scores of the two groups on each of the seven dimensions and overall score of the CCTST. Finally, for the strongest relationship that emerged, we included additional academic and background variables as covariates in multiple linear-regression analysis to explore questions about how much observed relationships between critical-thinking skills and science reasoning in writing might be explained by variation in these other factors.

Although BioTAP scores represent discreet, ordinal bins, the five-point scale is intended to capture an underlying continuous construct (from inadequate to exhibiting mastery). It has been argued that five categories is an appropriate cutoff for treating ordinal variables as pseudo-continuous ( Rhemtulla et al. , 2012 )—and therefore using continuous-variable statistical methods (e.g., Pearson’s correlations)—as long as the underlying assumption that ordinal scores are linearly distributed is valid. Although we have no way to statistically test this assumption, we interpret adequate scores to be approximately halfway between inadequate and mastery scores, resulting in a linear scale. In part because this assumption is subject to disagreement, we also consider and interpret a categorical (mastery/nonmastery) treatment of BioTAP variables.

We corrected for multiple comparisons using the Holm-Bonferroni method ( Holm, 1979 ). At the most general level, where we consider the single, comprehensive measures for BioTAP (partial-sum and factor score) and the CCTST (overall score), there is no need to correct for multiple comparisons, because the multiple, individual dimensions are collapsed into single dimensions. When we considered individual CCTST dimensions in relation to comprehensive measures for BioTAP, we accounted for seven comparisons; similarly, when we considered individual dimensions of BioTAP in relation to overall CCTST score, we accounted for five comparisons. When all seven CCTST and five BioTAP dimensions were examined individually and without prior knowledge, we accounted for 35 comparisons; such a rigorous threshold is likely to reject weak and moderate relationships, but it is appropriate if there are no specific pre-existing hypotheses. All p values are presented in tables for complete transparency, and we carefully consider the implications of our interpretation of these data in the Discussion section.

CCTST scores for students in this sample ranged from the 39th to 99th percentile of the general population of undergraduate CCTST test takers (mean percentile = 84.3, median = 85th percentile; Table 2 ); these percentiles reflect overall scores that range from moderate to superior. Scores on individual dimensions and overall scores were sufficiently normal and far enough from the ceiling of the scale to justify subsequent statistical analyses.

a Scores correspond to superior (86–100), strong (79–85), moderate (70–78), weak (63–69), or not manifested (62 and lower) skills.

The Pearson’s correlations between students’ cumulative scores on BioTAP (the factor score based on loadings published by Dowd et al. , 2016 , and the partial sum of scores on questions 1–5) and students’ overall scores on the CCTST are presented in Table 3 . We found that the partial-sum measure of BioTAP was significantly related to the overall measure of critical thinking ( r = 0.27, p = 0.03), while the BioTAP factor score was marginally related to overall CCTST ( r = 0.24, p = 0.05). When we looked at relationships between comprehensive BioTAP measures and scores for individual dimensions of the CCTST ( Table 3 ), we found significant positive correlations between the both BioTAP partial-sum and factor scores and CCTST inference ( r = 0.45, p < 0.001, and r = 0.41, p < 0.001, respectively). Although some other relationships have p values below 0.05 (e.g., the correlations between BioTAP partial-sum scores and CCTST induction and interpretation scores), they are not significant when we correct for multiple comparisons.

a In each cell, the top number is the correlation, and the bottom, italicized number is the associated p value. Correlations that are statistically significant after correcting for multiple comparisons are shown in bold.

b This is the partial sum of BioTAP scores on questions 1–5.

c This is the factor score calculated from factor loadings published by Dowd et al. (2016) .

When we expanded comparisons to include all 35 potential correlations among individual BioTAP and CCTST dimensions—and, accordingly, corrected for 35 comparisons—we did not find any additional statistically significant relationships. The Pearson’s correlations between students’ scores on each dimension of BioTAP and students’ scores on each dimension of the CCTST range from −0.11 to 0.35 ( Table 3 ); although the relationship between discussion of implications (BioTAP question 5) and inference appears to be relatively large ( r = 0.35), it is not significant ( p = 0.005; the Holm-Bonferroni cutoff is 0.00143). We found no statistically significant relationships between BioTAP questions 6–9 and CCTST dimensions (unpublished data), regardless of whether we correct for multiple comparisons.

The results of Student’s t tests comparing scores on each dimension of the CCTST of students who exhibit mastery with those of students who do not exhibit mastery on each dimension of BioTAP are presented in Table 4 . Focusing first on the overall CCTST scores, we found that the difference between those who exhibit mastery and those who do not in discussing implications of results (BioTAP question 5) is statistically significant ( t = 2.73, p = 0.008, d = 0.71). When we expanded t tests to include all 35 comparisons—and, like above, corrected for 35 comparisons—we found a significant difference in inference scores between students who exhibit mastery on question 5 and students who do not ( t = 3.41, p = 0.0012, d = 0.88), as well as a marginally significant difference in these students’ induction scores ( t = 3.26, p = 0.0018, d = 0.84; the Holm-Bonferroni cutoff is p = 0.00147). Cohen’s d effect sizes, which reveal the strength of the differences for statistically significant relationships, range from 0.71 to 0.88.

a In each cell, the top number is the t statistic for each comparison, and the middle, italicized number is the associated p value. The bottom number is the effect size. Correlations that are statistically significant after correcting for multiple comparisons are shown in bold.

Finally, we more closely examined the strongest relationship that we observed, which was between the CCTST dimension of inference and the BioTAP partial-sum composite score (shown in Table 3 ), using multiple regression analysis ( Table 5 ). Focusing on the 52 students for whom we have background information, we looked at the simple relationship between BioTAP and inference (model 1), a robust background model including multiple covariates that one might expect to explain some part of the variation in BioTAP (model 2), and a combined model including all variables (model 3). As model 3 shows, the covariates explain very little variation in BioTAP scores, and the relationship between inference and BioTAP persists even in the presence of all of the covariates.

** p < 0.01.

*** p < 0.001.

The aim of this study was to examine the extent to which the various components of scientific reasoning—manifested in writing in the genre of undergraduate thesis and assessed using BioTAP—draw on general and specific critical-thinking skills (assessed using CCTST) and to consider the implications for educational practices. Although science reasoning involves critical-thinking skills, it also relates to conceptual knowledge and the epistemological foundations of science disciplines ( Kuhn et al. , 2008 ). Moreover, science reasoning in writing , captured in students’ undergraduate theses, reflects habits, conventions, and the incorporation of feedback that may alter evidence of individuals’ critical-thinking skills. Our findings, however, provide empirical evidence that cumulative measures of science reasoning in writing are nonetheless related to students’ overall critical-thinking skills ( Table 3 ). The particularly significant roles of inference skills ( Table 3 ) and the discussion of implications of results (BioTAP question 5; Table 4 ) provide a basis for more specific ideas about how these constructs relate to one another and what educational interventions may have the most success in fostering these skills.

Our results build on previous findings. The genre of thesis writing combines pedagogies of writing and inquiry found to foster scientific reasoning ( Reynolds et al. , 2012 ) and critical thinking ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ; Stephenson and Sadler-McKnight, 2016 ). Quitadamo and Kurtz (2007) reported that students who engaged in a laboratory writing component in a general education biology course significantly improved their inference and analysis skills, and Quitadamo and colleagues (2008) found that participation in a community-based inquiry biology course (that included a writing component) was associated with significant gains in students’ inference and evaluation skills. The shared focus on inference is noteworthy, because these prior studies actually differ from the current study; the former considered critical-­thinking skills as the primary learning outcome of writing-­focused interventions, whereas the latter focused on emergent links between two learning outcomes (science reasoning in writing and critical thinking). In other words, inference skills are impacted by writing as well as manifested in writing.

Inference focuses on drawing conclusions from argument and evidence. According to the consensus definition of critical thinking, the specific skill of inference includes several processes: querying evidence, conjecturing alternatives, and drawing conclusions. All of these activities are central to the independent research at the core of writing an undergraduate thesis. Indeed, a critical part of what we call “science reasoning in writing” might be characterized as a measure of students’ ability to infer and make meaning of information and findings. Because the cumulative BioTAP measures distill underlying similarities and, to an extent, suppress unique aspects of individual dimensions, we argue that it is appropriate to relate inference to scientific reasoning in writing . Even when we control for other potentially relevant background characteristics, the relationship is strong ( Table 5 ).

In taking the complementary view and focusing on BioTAP, when we compared students who exhibit mastery with those who do not, we found that the specific dimension of “discussing the implications of results” (question 5) differentiates students’ performance on several critical-thinking skills. To achieve mastery on this dimension, students must make connections between their results and other published studies and discuss the future directions of the research; in short, they must demonstrate an understanding of the bigger picture. The specific relationship between question 5 and inference is the strongest observed among all individual comparisons. Altogether, perhaps more than any other BioTAP dimension, this aspect of students’ writing provides a clear view of the role of students’ critical-thinking skills (particularly inference and, marginally, induction) in science reasoning.

While inference and discussion of implications emerge as particularly strongly related dimensions in this work, we note that the strongest contribution to “science reasoning in writing in biology,” as determined through exploratory factor analysis, is “argument for the significance of research” (BioTAP question 2, not question 5; Dowd et al. , 2016 ). Question 2 is not clearly related to critical-thinking skills. These findings are not contradictory, but rather suggest that the epistemological and disciplinary-specific aspects of science reasoning that emerge in writing through BioTAP are not completely aligned with aspects related to critical thinking. In other words, science reasoning in writing is not simply a proxy for those critical-thinking skills that play a role in science reasoning.

In a similar vein, the content-related, epistemological aspects of science reasoning, as well as the conventions associated with writing the undergraduate thesis (including feedback from peers and revision), may explain the lack of significant relationships between some science reasoning dimensions and some critical-thinking skills that might otherwise seem counterintuitive (e.g., BioTAP question 2, which relates to making an argument, and the critical-thinking skill of argument). It is possible that an individual’s critical-thinking skills may explain some variation in a particular BioTAP dimension, but other aspects of science reasoning and practice exert much stronger influence. Although these relationships do not emerge in our analyses, the lack of significant correlation does not mean that there is definitively no correlation. Correcting for multiple comparisons suppresses type 1 error at the expense of exacerbating type 2 error, which, combined with the limited sample size, constrains statistical power and makes weak relationships more difficult to detect. Ultimately, though, the relationships that do emerge highlight places where individuals’ distinct critical-thinking skills emerge most coherently in thesis assessment, which is why we are particularly interested in unpacking those relationships.

We recognize that, because only honors students submit theses at these institutions, this study sample is composed of a selective subset of the larger population of biology majors. Although this is an inherent limitation of focusing on thesis writing, links between our findings and results of other studies (with different populations) suggest that observed relationships may occur more broadly. The goal of improved science reasoning and critical thinking is shared among all biology majors, particularly those engaged in capstone research experiences. So while the implications of this work most directly apply to honors thesis writers, we provisionally suggest that all students could benefit from further study of them.

There are several important implications of this study for science education practices. Students’ inference skills relate to the understanding and effective application of scientific content. The fact that we find no statistically significant relationships between BioTAP questions 6–9 and CCTST dimensions suggests that such mid- to lower-order elements of BioTAP ( Reynolds et al. , 2009 ), which tend to be more structural in nature, do not focus on aspects of the finished thesis that draw strongly on critical thinking. In keeping with prior analyses ( Reynolds and Thompson, 2011 ; Dowd et al. , 2016 ), these findings further reinforce the notion that disciplinary instructors, who are most capable of teaching and assessing scientific reasoning and perhaps least interested in the more mechanical aspects of writing, may nonetheless be best suited to effectively model and assess students’ writing.

The goal of the thesis writing course at both Duke University and the University of Minnesota is not merely to improve thesis scores but to move students’ writing into the category of mastery across BioTAP dimensions. Recognizing that students with differing critical-thinking skills (particularly inference) are more or less likely to achieve mastery in the undergraduate thesis (particularly in discussing implications [question 5]) is important for developing and testing targeted pedagogical interventions to improve learning outcomes for all students.

The competencies characterized by the Vision and Change in Undergraduate Biology Education Initiative provide a general framework for recognizing that science reasoning and critical-thinking skills play key roles in major learning outcomes of science education. Our findings highlight places where science reasoning–related competencies (like “understanding the process of science”) connect to critical-thinking skills and places where critical thinking–related competencies might be manifested in scientific products (such as the ability to discuss implications in scientific writing). We encourage broader efforts to build empirical connections between competencies and pedagogical practices to further improve science education.

One specific implication of this work for science education is to focus on providing opportunities for students to develop their critical-thinking skills (particularly inference). Of course, as this correlational study is not designed to test causality, we do not claim that enhancing students’ inference skills will improve science reasoning in writing. However, as prior work shows that science writing activities influence students’ inference skills ( Quitadamo and Kurtz, 2007 ; Quitadamo et al. , 2008 ), there is reason to test such a hypothesis. Nevertheless, the focus must extend beyond inference as an isolated skill; rather, it is important to relate inference to the foundations of the scientific method ( Miri et al. , 2007 ) in terms of the epistemological appreciation of the functions and coordination of evidence ( Kuhn and Dean, 2004 ; Zeineddin and Abd-El-Khalick, 2010 ; Ding et al. , 2016 ) and disciplinary paradigms of truth and justification ( Moshman, 2015 ).

Although this study is limited to the domain of biology at two institutions with a relatively small number of students, the findings represent a foundational step in the direction of achieving success with more integrated learning outcomes. Hopefully, it will spur greater interest in empirically grounding discussions of the constructs of scientific reasoning and critical-thinking skills.

This study contributes to the efforts to improve science education, for both majors and nonmajors, through an empirically driven analysis of the relationships between scientific reasoning reflected in the genre of thesis writing and critical-thinking skills. This work is rooted in the usefulness of BioTAP as a method 1) to facilitate communication and learning and 2) to assess disciplinary-specific and general dimensions of science reasoning. The findings support the important role of the critical-thinking skill of inference in scientific reasoning in writing, while also highlighting ways in which other aspects of science reasoning (epistemological considerations, writing conventions, etc.) are not significantly related to critical thinking. Future research into the impact of interventions focused on specific critical-thinking skills (i.e., inference) for improved science reasoning in writing will build on this work and its implications for science education.

ACKNOWLEDGMENTS

We acknowledge the contributions of Kelaine Haas and Alexander Motten to the implementation and collection of data. We also thank Mine Çetinkaya-­Rundel for her insights regarding our statistical analyses. This research was funded by National Science Foundation award DUE-1525602.

• American Association for the Advancement of Science . ( 2011 ). Vision and change in undergraduate biology education: A call to action . Washington, DC Retrieved September 26, 2017, from https://visionandchange.org/files/2013/11/aaas-VISchange-web1113.pdf . Google Scholar
• August, D. ( 2016 ). California Critical Thinking Skills Test user manual and resource guide . San Jose: Insight Assessment/California Academic Press. Google Scholar
• Beyer, C. H., Taylor, E., & Gillmore, G. M. ( 2013 ). Inside the undergraduate teaching experience: The University of Washington’s growth in faculty teaching study . Albany, NY: SUNY Press. Google Scholar
• Bissell, A. N., & Lemons, P. P. ( 2006 ). A new method for assessing critical thinking in the classroom . BioScience , 56 (1), 66–72. https://doi.org/10.1641/0006-3568(2006)056[0066:ANMFAC]2.0.CO;2 . Google Scholar
• Blattner, N. H., & Frazier, C. L. ( 2002 ). Developing a performance-based assessment of students’ critical thinking skills . Assessing Writing , 8 (1), 47–64. Google Scholar
• Clase, K. L., Gundlach, E., & Pelaez, N. J. ( 2010 ). Calibrated peer review for computer-assisted learning of biological research competencies . Biochemistry and Molecular Biology Education , 38 (5), 290–295. Medline ,  Google Scholar
• Condon, W., & Kelly-Riley, D. ( 2004 ). Assessing and teaching what we value: The relationship between college-level writing and critical thinking abilities . Assessing Writing , 9 (1), 56–75. https://doi.org/10.1016/j.asw.2004.01.003 . Google Scholar
• Ding, L., Wei, X., & Liu, X. ( 2016 ). Variations in university students’ scientific reasoning skills across majors, years, and types of institutions . Research in Science Education , 46 (5), 613–632. https://doi.org/10.1007/s11165-015-9473-y . Google Scholar
• Dowd, J. E., Connolly, M. P., Thompson, R. J.Jr., & Reynolds, J. A. ( 2015a ). Improved reasoning in undergraduate writing through structured workshops . Journal of Economic Education , 46 (1), 14–27. https://doi.org/10.1080/00220485.2014.978924 . Google Scholar
• Dowd, J. E., Roy, C. P., Thompson, R. J.Jr., & Reynolds, J. A. ( 2015b ). “On course” for supporting expanded participation and improving scientific reasoning in undergraduate thesis writing . Journal of Chemical Education , 92 (1), 39–45. https://doi.org/10.1021/ed500298r . Google Scholar
• Dowd, J. E., Thompson, R. J.Jr., & Reynolds, J. A. ( 2016 ). Quantitative genre analysis of undergraduate theses: Uncovering different ways of writing and thinking in science disciplines . WAC Journal , 27 , 36–51. Google Scholar
• Facione, P. A. ( 1990 ). Critical thinking: a statement of expert consensus for purposes of educational assessment and instruction. Research findings and recommendations . Newark, DE: American Philosophical Association. Retrieved September 26, 2017, from https://philpapers.org/archive/FACCTA.pdf . Google Scholar
• Gerdeman, R. D., Russell, A. A., Worden, K. J., Gerdeman, R. D., Russell, A. A., & Worden, K. J. ( 2007 ). Web-based student writing and reviewing in a large biology lecture course . Journal of College Science Teaching , 36 (5), 46–52. Google Scholar
• Greenhoot, A. F., Semb, G., Colombo, J., & Schreiber, T. ( 2004 ). Prior beliefs and methodological concepts in scientific reasoning . Applied Cognitive Psychology , 18 (2), 203–221. https://doi.org/10.1002/acp.959 . Google Scholar
• Haaga, D. A. F. ( 1993 ). Peer review of term papers in graduate psychology courses . Teaching of Psychology , 20 (1), 28–32. https://doi.org/10.1207/s15328023top2001_5 . Google Scholar
• Halonen, J. S., Bosack, T., Clay, S., McCarthy, M., Dunn, D. S., Hill, G. W., … Whitlock, K. ( 2003 ). A rubric for learning, teaching, and assessing scientific inquiry in psychology . Teaching of Psychology , 30 (3), 196–208. https://doi.org/10.1207/S15328023TOP3003_01 . Google Scholar
• Hand, B., & Keys, C. W. ( 1999 ). Inquiry investigation . Science Teacher , 66 (4), 27–29. Google Scholar
• Holm, S. ( 1979 ). A simple sequentially rejective multiple test procedure . Scandinavian Journal of Statistics , 6 (2), 65–70. Google Scholar
• Holyoak, K. J., & Morrison, R. G. ( 2005 ). The Cambridge handbook of thinking and reasoning . New York: Cambridge University Press. Google Scholar
• Insight Assessment . ( 2016a ). California Critical Thinking Skills Test (CCTST) Retrieved September 26, 2017, from www.insightassessment.com/Products/Products-Summary/Critical-Thinking-Skills-Tests/California-Critical-Thinking-Skills-Test-CCTST . Google Scholar
• Insight Assessment . ( 2016b ). Sample thinking skills questions. Retrieved September 26, 2017, from www.insightassessment.com/Resources/Teaching-Training-and-Learning-Tools/node_1487 . Google Scholar
• Kelly, G. J., & Takao, A. ( 2002 ). Epistemic levels in argument: An analysis of university oceanography students’ use of evidence in writing . Science Education , 86 (3), 314–342. https://doi.org/10.1002/sce.10024 . Google Scholar
• Kuhn, D., & Dean, D.Jr. ( 2004 ). Connecting scientific reasoning and causal inference . Journal of Cognition and Development , 5 (2), 261–288. https://doi.org/10.1207/s15327647jcd0502_5 . Google Scholar
• Kuhn, D., Iordanou, K., Pease, M., & Wirkala, C. ( 2008 ). Beyond control of variables: What needs to develop to achieve skilled scientific thinking? . Cognitive Development , 23 (4), 435–451. https://doi.org/10.1016/j.cogdev.2008.09.006 . Google Scholar
• Lawson, A. E. ( 2010 ). Basic inferences of scientific reasoning, argumentation, and discovery . Science Education , 94 (2), 336–364. https://doi.org/­10.1002/sce.20357 . Google Scholar
• Meizlish, D., LaVaque-Manty, D., Silver, N., & Kaplan, M. ( 2013 ). Think like/write like: Metacognitive strategies to foster students’ development as disciplinary thinkers and writers . In Thompson, R. J. (Ed.), Changing the conversation about higher education (pp. 53–73). Lanham, MD: Rowman & Littlefield. Google Scholar
• Miri, B., David, B.-C., & Uri, Z. ( 2007 ). Purposely teaching for the promotion of higher-order thinking skills: A case of critical thinking . Research in Science Education , 37 (4), 353–369. https://doi.org/10.1007/s11165-006-9029-2 . Google Scholar
• Moshman, D. ( 2015 ). Epistemic cognition and development: The psychology of justification and truth . New York: Psychology Press. Google Scholar
• National Research Council . ( 2000 ). How people learn: Brain, mind, experience, and school . Expanded ed.. Washington, DC: National Academies Press. Google Scholar
• Pukkila, P. J. ( 2004 ). Introducing student inquiry in large introductory genetics classes . Genetics , 166 (1), 11–18. https://doi.org/10.1534/genetics.166.1.11 . Medline ,  Google Scholar
• Quitadamo, I. J., Faiola, C. L., Johnson, J. E., & Kurtz, M. J. ( 2008 ). Community-based inquiry improves critical thinking in general education biology . CBE—Life Sciences Education , 7 (3), 327–337. https://doi.org/10.1187/cbe.07-11-0097 . Link ,  Google Scholar
• Quitadamo, I. J., & Kurtz, M. J. ( 2007 ). Learning to improve: Using writing to increase critical thinking performance in general education biology . CBE—Life Sciences Education , 6 (2), 140–154. https://doi.org/10.1187/cbe.06-11-0203 . Link ,  Google Scholar
• Reynolds, J. A., Smith, R., Moskovitz, C., & Sayle, A. ( 2009 ). BioTAP: A systematic approach to teaching scientific writing and evaluating undergraduate theses . BioScience , 59 (10), 896–903. https://doi.org/10.1525/bio.2009.59.10.11 . Google Scholar
• Reynolds, J. A., Thaiss, C., Katkin, W., & Thompson, R. J. ( 2012 ). Writing-to-learn in undergraduate science education: A community-based, conceptually driven approach . CBE—Life Sciences Education , 11 (1), 17–25. https://doi.org/10.1187/cbe.11-08-0064 . Link ,  Google Scholar
• Reynolds, J. A., & Thompson, R. J. ( 2011 ). Want to improve undergraduate thesis writing? Engage students and their faculty readers in scientific peer review . CBE—Life Sciences Education , 10 (2), 209–215. https://doi.org/­10.1187/cbe.10-10-0127 . Link ,  Google Scholar
• Rhemtulla, M., Brosseau-Liard, P. E., & Savalei, V. ( 2012 ). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions . Psychological Methods , 17 (3), 354–373. https://doi.org/­10.1037/a0029315 . Medline ,  Google Scholar
• Stephenson, N. S., & Sadler-McKnight, N. P. ( 2016 ). Developing critical thinking skills using the science writing heuristic in the chemistry laboratory . Chemistry Education Research and Practice , 17 (1), 72–79. https://doi.org/­10.1039/C5RP00102A . Google Scholar
• Tariq, V. N., Stefani, L. A. J., Butcher, A. C., & Heylings, D. J. A. ( 1998 ). Developing a new approach to the assessment of project work . Assessment and Evaluation in Higher Education , 23 (3), 221–240. https://doi.org/­10.1080/0260293980230301 . Google Scholar
• Timmerman, B. E. C., Strickland, D. C., Johnson, R. L., & Payne, J. R. ( 2011 ). Development of a “universal” rubric for assessing undergraduates’ scientific reasoning skills using scientific writing . Assessment and Evaluation in Higher Education , 36 (5), 509–547. https://doi.org/10.1080/­02602930903540991 . Google Scholar
• Topping, K. J., Smith, E. F., Swanson, I., & Elliot, A. ( 2000 ). Formative peer assessment of academic writing between postgraduate students . Assessment and Evaluation in Higher Education , 25 (2), 149–169. https://doi.org/10.1080/713611428 . Google Scholar
• Willison, J., & O’Regan, K. ( 2007 ). Commonly known, commonly not known, totally unknown: A framework for students becoming researchers . Higher Education Research and Development , 26 (4), 393–409. https://doi.org/10.1080/07294360701658609 . Google Scholar
• Woodin, T., Carter, V. C., & Fletcher, L. ( 2010 ). Vision and Change in Biology Undergraduate Education: A Call for Action—Initial responses . CBE—Life Sciences Education , 9 (2), 71–73. https://doi.org/10.1187/cbe.10-03-0044 . Link ,  Google Scholar
• Zeineddin, A., & Abd-El-Khalick, F. ( 2010 ). Scientific reasoning and epistemological commitments: Coordination of theory and evidence among college science students . Journal of Research in Science Teaching , 47 (9), 1064–1093. https://doi.org/10.1002/tea.20368 . Google Scholar
• Zimmerman, C. ( 2000 ). The development of scientific reasoning skills . Developmental Review , 20 (1), 99–149. https://doi.org/10.1006/drev.1999.0497 . Google Scholar
• Zimmerman, C. ( 2007 ). The development of scientific thinking skills in elementary and middle school . Developmental Review , 27 (2), 172–223. https://doi.org/10.1016/j.dr.2006.12.001 . Google Scholar
• Gender, Equity, and Science Writing: Examining Differences in Undergraduate Life Science Majors’ Attitudes toward Writing Lab Reports 6 March 2024 | Education Sciences, Vol. 14, No. 3
• Designing a framework to improve critical reflection writing in teacher education using action research 24 February 2022 | Educational Action Research, Vol. 32, No. 1
• Scientific Thinking and Critical Thinking in Science Education  5 September 2023 | Science & Education, Vol. 11
• Students Need More than Content Knowledge To Counter Vaccine Hesitancy Journal of Microbiology & Biology Education, Vol. 24, No. 2
• Critical thinking during science investigations: what do practicing teachers value and observe? 16 March 2023 | Teachers and Teaching, Vol. 29, No. 6
• Effect of Web-Based Collaborative Learning Method with Scratch on Critical Thinking Skills of 5th Grade Students 30 March 2023 | Participatory Educational Research, Vol. 10, No. 2
• Are We on the Way to Successfully Educating Future Citizens?—A Spotlight on Critical Thinking Skills and Beliefs about the Nature of Science among Pre-Service Biology Teachers in Germany 22 March 2023 | Behavioral Sciences, Vol. 13, No. 3
• A Systematic Review on Inquiry-Based Writing Instruction in Tertiary Settings 30 November 2022 | Written Communication, Vol. 40, No. 1
• An empirical analysis of the relationship between nature of science and critical thinking through science definitions and thinking skills 8 December 2022 | SN Social Sciences, Vol. 2, No. 12
• TEACHING OF CRITICAL THINKING SKILLS BY SCIENCE TEACHERS IN JAPANESE PRIMARY SCHOOLS 25 October 2022 | Journal of Baltic Science Education, Vol. 21, No. 5
• A Team-Based Activity to Support Knowledge Transfer and Experimental Design Skills of Undergraduate Science Students 4 May 2022 | Journal of Microbiology & Biology Education, Vol. 21
• Curriculum Design of College Students’ English Critical Ability in the Internet Age Wireless Communications and Mobile Computing, Vol. 2022
• Exploring the structure of students’ scientific higher order thinking in science education Thinking Skills and Creativity, Vol. 43
• The Asia-Pacific Education Researcher, Vol. 31, No. 4
• Conspiratorial Beliefs and Cognitive Styles: An Integrated Look on Analytic Thinking, Critical Thinking, and Scientific Reasoning in Relation to (Dis)trust in Conspiracy Theories 12 October 2021 | Frontiers in Psychology, Vol. 12
• Professional Knowledge and Self-Efficacy Expectations of Pre-Service Teachers Regarding Scientific Reasoning and Diagnostics 11 October 2021 | Education Sciences, Vol. 11, No. 10
• Developing textbook based on scientific approach, critical thinking, and science process skills Journal of Physics: Conference Series, Vol. 1839, No. 1
• Using Models of Cognitive Development to Design College Learning Experiences
• Thinking Skills and Creativity, Vol. 42
• Assessing students’ prior knowledge on critical thinking skills in the biology classroom: Has it already been good?
• Critical Thinking Level among Medical Sciences Students in Iran Education Research International, Vol. 2020
• Teaching during a pandemic: Using high‐impact writing assignments to balance rigor, engagement, flexibility, and workload 12 October 2020 | Ecology and Evolution, Vol. 10, No. 22
• Mini-Review - Teaching Writing in the Undergraduate Neuroscience Curriculum: Its Importance and Best Practices Neuroscience Letters, Vol. 737
• Developing critical thinking skills assessment for pre-service elementary school teacher about the basic concept of science: validity and reliability Journal of Physics: Conference Series, Vol. 1567, No. 2
• Challenging endocrinology students with a critical-thinking workbook Advances in Physiology Education, Vol. 44, No. 1
• Jason E. Dowd ,
• Robert J. Thompson ,
• Leslie Schiff ,
• Kelaine Haas ,
• Christine Hohmann ,
• Chris Roy ,
• Warren Meck ,
• John Bruno , and
• Rebecca Price, Monitoring Editor
• Kari L. Nelson ,
• Claudia M. Rauter , and
• Christine E. Cutucache
• Elisabeth Schussler, Monitoring Editor

Submitted: 17 March 2017 Revised: 19 October 2017 Accepted: 20 October 2017

© 2018 J. E. Dowd et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Advertisement

Developing Students’ Critical Thinking Skills and Argumentation Abilities Through Augmented Reality–Based Argumentation Activities in Science Classes

• Published: 22 August 2022
• Volume 32 , pages 1165–1195, ( 2023 )

Cite this article

• Tuba Demircioglu   ORCID: orcid.org/0000-0003-3567-1739 1 ,
• Memet Karakus   ORCID: orcid.org/0000-0002-6099-5420 2 &
• Sedat Ucar   ORCID: orcid.org/0000-0002-4158-1038 1  

6767 Accesses

5 Citations

Explore all metrics

Due to the COVID-19 pandemic and adapting the classes urgently to distance learning, directing students’ interest in the course content became challenging. The solution to this challenge emerges through creative pedagogies that integrate the instructional methods with new technologies like augmented reality (AR). Although the use of AR in science education is increasing, the integration of AR into science classes is still naive. The lack of the ability to identify misinformation in the COVID-19 pandemic process has revealed the importance of developing students’ critical thinking skills and argumentation abilities. The purpose of this study was to examine the change in critical thinking skills and argumentation abilities through augmented reality–based argumentation activities in teaching astronomy content. The participants were 79 seventh grade students from a private school. In this case study, the examination of the verbal arguments of students showed that all groups engaged in the argumentation and produced quality arguments. The critical thinking skills of the students developed until the middle of the intervention, and the frequency of using critical thinking skills varied after the middle of the intervention. The findings highlight the role of AR-based argumentation activities in students’ critical thinking skills and argumentation in science education.

Similar content being viewed by others

Integrating augmented reality into inquiry-based learning approach in primary science classrooms

Insights from pre-service teachers using science-based augmented reality.

Augmented Reality Simulation to Visualize Global Warming and Its Consequences

Avoid common mistakes on your manuscript.

1 Introduction

With rapidly developing technology, the number of children using mobile handheld devices has increased drastically (Rideout et al., 2010 ; Squire, 2006 ). Technologies and digital enhancements that use the internet have become a part of the daily life of school-age children (Kennedy et al., 2008 ), and education evolves in line with the changing technology. Rapidly changing innovation technologies have changed the characteristics of learners in the fields of knowledge, skills, and expertise that are valuable for society, and circumstances for teachers and students have changed over time (Yuen et al., 2011 ). Almost every school subject incorporates technological devices into the pedagogy to different extents, but science teachers are the most eager to use technological devices in science classes because of the nature of the content they are expected to teach.

The COVID-19 pandemic has had an important impact on educational systems worldwide. Due to the fast-spreading of that disease, the educators had to adapt their classes urgently to technology and distance learning (Dietrich et al., 2020 ), and schools have had to put more effort into adapting new technologies to teaching. Z generation was born into a time of information technology, but they did not choose distance courses that were not created for them so they are not motivated during the classes (Dietrich et al., 2020 ). Directing students’ interest in the course content is challenging, while their interest has changed by this technological development. The solution to this challenge emerges through creative pedagogies that integrate the instructional methods with new striking technology. Augmented reality has demonstrated high potential as part of many teaching methods.

2 Literature Review

2.1 augmented reality, education, and science education.

AR applications have important potential for many areas where rapid transfer of information is important. This is especially effective for education. Science education is among the disciplines where rapid information transfer is important. Taylor ( 1987 , p. 1) stated that “the transfer of scientific and technological information to children and to the general public is as important as the search for information.” With the rapid change in science and technology and outdating of knowledge, learning needs rapid changes in transfer of information (Ploman, 1987 ). Technology provides new and innovative methods for science education and could be an effective media in promoting students’ learning (Virata & Castro, 2019 ). AR technology could be a promising teaching tool for science teaching in which AR technology is especially applicable (Arici et al., 2019 ).

Research shows that AR has great potential and benefits for learning and teaching (Yuen et al., 2011 ). The AR applications used in teaching and learning present many objects, practices, and experiments that students cannot obtain from the first-hand experience into many different dimensions because of the impossibilities in the real world, and it is an approach that can be applied to many science contents that are unreachable, unobtrusive, and unable to travel (Cai et al., 2013 ; Huang et al., 2019 ; Pellas et al., 2019 ). For example, physically unreachable phenomena such as solar systems, moon phases, and magnetic fields become accessible for learners through AR (Fleck & Simon, 2013 ; Kerawalla et al., 2006 ; Shelton & Hedley, 2002 ; Sin & Zaman, 2010 ; Yen et al., 2013 ). Through AR, learners can obtain instant access to location-specific information provided by a wide range of sources (Yuen et al., 2011 ). Location-based information, when used in particular contextual learning activities, is essential for assisting students’ outdoor learning. This interaction develops comprehension, understanding, imagination, and retention, which are the learning and cognitive skills of learners (Chiang et al., 2014 ). For example, an AR-based mobile learning system was used in the study conducted by Chiang et al. ( 2014 ) on aquatic animals and plants. The location module can identify the students’ GPS location, direct them to discover the target ecological regions, and provide the appropriate learning tasks or additional resources. When students explore various characteristics of learning objects, the camera and image editing modules can take the image from the real environment and make comment on the image of the observed things.

Research reveals that the use of AR technology as part of teaching a subject has the features of being constructivist, problem solving-based, student-centered, authentic, participative, creative, personalized, meaningful, challenging, collaborative, interactive, entertaining, cognitively rich, contextual, and motivational (Dunleavy et al., 2009 ). Despite its advantages and although the use of AR in science education is increasing, the integration of AR into science classes is still naive, and teachers still do not consider themselves as ready for use of AR in their class (Oleksiuk & Oleksiuk, 2020 ; Romano et al., 2020 ) and choose not to use AR technology (Alalwan et al., 2020 ; Garzón et al., 2019 ), because most of them do not have the abilities and motivation to design AR learning practices (Garzón et al., 2019 ; Romano et al., 2020 ). It is thought that the current study will contribute to the use of AR in science lessons and how science teachers will include AR technology in their lessons.

2.2 Argumentation, Critical Thinking, and Augmented Reality

New trends in information technologies have contributed to the development of new skills in which people have to struggle with a range of information and evaluate this information. An important point of these skills is the ability to argue with evidence (Jiménez -Aleixandre & Erduran, 2007 ) in which young people create appropriate results from the information and evidence given to them to criticize the claims of others in the direction of the evidence and to distinguish an idea from evidence-based situations (OECD, 2003 , p. 132).

Learning with technologies could produce information and misinformation simultaneously (Chai et al., 2015 ). Misinformation has spread very quickly in public in COVID-19 pandemic, so the lack of the ability to interpret and evaluate the validity and credibility of them arose again (Saribas & Çetinkaya, 2021 ). This process revealed the importance of developing students’ critical thinking skills and argumentation abilities (Erduran, 2020 ) to make decisions and adequate judgments when they encountered contradicting information (Chai et al., 2015 ).

Thinking about different subjects, evaluating the validity of scientific claims, and interpreting and evaluating evidence are important elements of science courses and play important roles in the construction of scientific knowledge (Driver et al., 2000 ). The use of scientific knowledge in everyday life ensures that critical thinking skills come to the forefront. Ennis ( 2011 , p. 1) defined critical thinking as “Critical thinking is reasonable and reflective thinking focused on deciding what to believe”. Jiménez-Aleixandre and Puig ( 2012 ) found this definition very broad, and they proposed a comprehensive definition of critical thinking that combines the components of social emancipation and evidence evaluation. It contains the competence to form autonomous ideas as well as the ability to participate in and reflect on the world around us. Figure  1 summarizes this comprehensive definition.

Argumentation levels by groups

Critical thinking skills that include the ability to evaluate arguments and counterarguments in a variety of contexts are very important, and effective argumentation is the focal point of criticism and the informed decision (Nussbaum, 2008 ). Argumentation is defined as the process of making claims about a scientific subject, supporting them with data, using warrants, and criticizing, refuting, and evaluating an idea (Toulmin, 1990 ). Argumentation as an instructional method is an important research area in science education and has received enduring interest from science educators for more than a decade (Erduran et al., 2015 ). Researchers concluded that learners mostly made only claims in the argumentation process and had difficulty producing well-justified and high-quality arguments (Demircioglu & Ucar, 2014 ; Demircioglu & Ucar, 2015 ; Cavagnetto et al., 2010 ; Erdogan et al., 2017 ; Erduran et al., 2004 ; Novak & Treagust, 2017 ). To improve the quality of arguments, students should be given supportive elements to produce more consistent arguments during argumentation. One of these supportive elements is the visual representations of the phenomena.

Visual representations could make it easier to see the structure of the arguments of learners (Akpınar et al., 2014 ) and improve students’ awareness. For example, the number of words and comments used by students or meaningful links in conversations increases with visually enriched arguments (Erkens & Janssen, 2006 ). Sandoval & Millwood ( 2005 ) stated that students should be able to evaluate different kinds of evidence such as digital data and graphic photography to defend their claims. Appropriate data can directly support a claim and allow an argument to be accepted or rejected by students (Lin & Mintzes, 2010 ). Enriched visual representations provide students with detailed and meaningful information about the subject (Clark et al., 2007 ). Students collect evidence for argumentation by observing enriched representations (Clark et al., 2007 ), and these representations help to construct higher-quality arguments (Buckingham Shum et al., 1997 ; Jermann & Dillenbourg, 2003 ). Visualization techniques enable students to observe how objects behave and interact and provide an easy-to-understand presentation of scientific facts that are difficult to understand with textual or oral explanations (Cadmus, 1990 ). In short, technological opportunities to create visually enriched representations increase students’ access to rich data to support their arguments.

Among the many technological opportunities to promote argumentation, AR seems to be the most promising application for instructing school subjects. AR applications are concerned with the combination of computer-generated data (virtual reality) and the real world, where computer graphics are projected onto real-time video images (Dias, 2009 ). In addition, augmented reality provides users with the ability to see a real-world environment enriched with 3D images and to interact in real time by combining virtual objects with the real environment in 3D and showing the spatial relations (Kerawalla et al., 2006 ). AR applications are thus important tools for students’ arguments with the help of detailed and meaningful information and enriched representations. Research studies using AR technology revealed that all students in the study engaged in argumentation and produced arguments (Jan, 2009 ; Squire & Jan, 2007 ).

Many studies focusing on using AR in science education have been published in recent decades. Research studies related to AR in science education have focused on the use of game-based AR in science education (Atwood-Blaine & Huffman, 2017 ; Bressler & Bodzin, 2013 ; Dunleavy et al., 2009 ; López-Faican & Jaen, 2020 ; Squire, 2006 ), academic achievement (Hsiao et al., 2016 ; Faridi et al., 2020 ; Hwang et al., 2016 ; Lu et al., 2020 ; Sahin & Yilmaz, 2020 ;, Yildirim & Seckin-Kapucu, 2020 ), understanding science content and its conceptual understanding (Cai et al., 2021 ; Chang et al., 2013 ; Chen & Liu, 2020 ; Ibáñez et al., 2014 ), attitude (Sahin & Yilmaz, 2020 0; Hwang et al., 2016 ), self-efficacy (Cai et al., 2021 ), motivation (Bressler & Bodzin, 2013 ; Chen & Liu, 2020 ; Kirikkaya & Başgül, 2019 ; Lu et al., 2020 ; Zhang et al., 2014 ), and critical thinking skills (Faridi et al., 2020 ; Syawaludin et al., 2019 ). The general trend in these research studies based on the content of “learning/academic achievement,” “understanding science content and its conceptual understanding,” “motivation,” “attitude,” and methodologically quantitative studies was mostly used in articles in science education. Therefore, qualitative and quantitative data to be obtained from studies investigating the use of augmented reality technology in education and focusing on cognitive issues, interaction, and collaborative activities are needed (Arici et al., 2019 ; Cheng & Tsai, 2013 ).

Instructional strategies using AR technology ensure interactions between students and additionally between students and teachers (Hanid et al., 2020 ). Both the technological features of AR and learning strategies should be regarded by the teachers, the curriculum, and AR technology developers to acquire the complete advantage of AR in student learning (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ). Researchers investigated the learning outcomes with AR-integrated learning strategies such as collaborative learning (Baran et al., 2020 ; Chen & Liu, 2020 ; Ke & Carafano, 2016 ), socioscientific reasoning (Chang et al., 2020 ), student-centered hands-on learning activities (Chen & Liu, 2020 ), inquiry-based learning (Radu & Schneider, 2019 ), concept-map learning system (Chen et al., 2019 ), problem-based learning (Fidan & Tuncel, 2019 ), and argumentation (Jan, 2009 ; Squire & Jan, 2007 ) in science learning.

The only two existing studies using both AR and argumentation (Jan, 2009 ; Squire & Jan, 2007 ) focus on environmental education and use location-based augmented reality games through mobile devices to engage students in scientific argumentation. Studies combining AR and argumentation in astronomy education have not been found in the literature. In the current study, AR was integrated with argumentation in teaching astronomy content.

Studies have revealed that many topics in astronomy are very difficult to learn and that students have incorrect and naive concepts (Yu & Sahami, 2007 ). Many topics include three-dimensional (3D) spatial relationships between astronomical objects (Aktamış & Arıcı, 2013 ; Yu & Sahami, 2007 ). However, most of the traditional teaching materials used in astronomy education are two-dimensional (Aktamış & Arıcı, 2013 ). Teaching astronomy through photographs and 2D animations is not sufficient to understand the difficult and complex concepts of astronomy (Chen et al., 2007 ). Static visualization tools such as texts, photographs, and 3D models do not change over time and do not have continuous movement, while dynamic visualization tools such as videos or animations show continuous movement and change over time (Schnotz & Lowe, 2008 ). However, animation is the presentation of images on a computer screen (Rieber & Kini, 1991 ), not in the real world, and the users do not have a chance to manipulate the images (Setozaki et al., 2017 ). As a solution to this shortcoming, using 3D technology in science classes, especially AR technology for abstract concepts, has become a necessity (Sahin & Yilmaz, 2020 ). By facilitating interaction with real and virtual environment and supporting object manipulation, AR is possible to enhance educational benefits (Billinghurst, 2002 ). The students are not passive participants while using AR technology. For example, the animated 3D sun and Earth models are moved on a handheld platform that adjusts its orientation in accordance with the student’s point of view in Shelton’s study ( 2002 ). They found that the ability of students to manage “how” and “when” they are allowed to manipulate virtual 3D objects has a direct impact on learning complex spatial phenomena. Experimental results show that compared with traditional video teaching, AR multimedia video teaching method significantly improves students’ learning (Chen et al., 2022 ).

This study, which integrates argumentation with new striking technology “AR” in astronomy education, clarifies the relationship between them and examines variables such as critical thinking skills and argumentation abilities that are essential in the era we live, making this research important.

2.3 Research Questions

The purpose of this study was to identify the change in critical thinking skills and argumentation abilities through augmented reality–based argumentation activities in teaching astronomy content. The following research questions guided this study:

RQ1: How do the critical thinking skills of students who participated in both augmented reality and argumentation activities on astronomy change during the study?

RQ2: How do the argumentation abilities of students who participated in both augmented reality and argumentation activities on astronomy change during the study?

In this case study, we investigated the change of critical thinking skills and argumentation abilities of middle school students. Before the main intervention, a pilot study was conducted to observe the effectiveness of the prepared lesson plans in practice and to identify the problems in the implementation process. The pilot study was recorded with a camera. The camera recordings were watched by the researcher, and the difficulties in the implementation process were identified. In the main intervention, preventions were taken to overcome these difficulties. Table 1 illustrates that the problems encountered during the pilot study and the preventions taken to eliminate these problems.

During the main intervention, qualitative data were collected through observations and audio recordings to determine the change in the critical thinking skills and argumentation abilities of students who participated in both augmented reality and argumentation activities on astronomy.

3.1 Context and Participants

The participants consisted of 79 7th middle school students aged between 12 and 13 from a private school in Southern Turkey. The participants were determined as students in a private school where tablet computers are available for each student and the school willing to participate in the study. Twenty-six students, including 17 females and 9 males, participated in the study. The students’ parents signed the consent forms (whether participating or refusing participation in the study). The researcher informed them about the purpose of the study, instructional process, and ethical principles that directed the study. The teachers and school principals were informed that the preliminary and detailed conclusions of the study will be shared with them. The first researcher conducted the lessons in all groups because when the study was conducted, the use of augmented reality technology in education was very new. Also, the science teachers had inadequate knowledge and experience about augmented reality applications. Before the study, the researcher attended the classes with the teacher and made observations to help students become accustomed to the presence of the researcher in the classroom. This prolonged engagement increased the reliability of the implementation of instructions and data collection (Guba & Lincoln, 1989 ).

3.2 Instructional Activities

The 3-week, 19-h intervention process, which was based on the prepared lesson plan, was conducted. The students participated in the learning process that included both augmented reality and argumentation activities about astronomy.

3.2.1 Augmented Reality Activities

Free applications such as Star Chart, Sky View Free, Aurasma, Junaio, Augment, and i Solar System were used with students’ tablet computers in augmented reality instructions. Tablet computers were provided by the school administration from their stock. Videos, simulations, and 3D visuals generated by applications were used as “overlays.” In addition, pictures, photographs, colored areas in the worksheets, and students’ textbooks were used as “trigger images.” Students had the opportunity to interact with and manipulate these videos, simulations, and 3D visuals while using the applications. With applications such as Sky View Free and Star Chart, students were provided with the resources to make sky observations.

A detailed description of the activities used in augmented reality is given in Appendix Table 8 .

3.2.2 Argumentation Activities

Before the instruction, the students were divided into six groups by the teacher, paying attention to heterogeneity in terms of gender and academic achievement. After small group discussions, the students participated in whole-class discussions. Competing theories cartoons, tables of statements, constructing an argument, and argument-driven inquiry (ADI) frameworks were used to support argumentation in the learning process. Argument-driven inquiry consists of eight steps including the following: identification of the task, the generation and analysis of data, the production of a tentative argument, an argumentation session, an investigation report, a double-blind peer review, revision of the report, and explicit and reflective discussion (Sampson & Gleim, 2009 ; Sampson et al., 2011 ).

A detailed description of the activities used in argumentation is given in Appendix Table 9 .

4 Data Collection

The data were collected through unstructured and participant observations (Maykut & Morehouse, 1994 ; Patton, 2002 ). The instructional intervention was recorded with a video camera, and the students’ argumentation processes were also recorded with a voice recorder.

Since all students spoke at the same time during group discussions, the observation records were insufficient to understand the student talks. To determine what each student in the group said during the argumentation process, a voice recorder was placed in the middle of the group table, and a voice recording was taken throughout the lesson. A total of 2653.99 min of voice recordings were taken in the six groups.

4.1 Data Analysis

The analysis of the data was conducted with inductive and deductive approaches. Before coding, the data were arranged. The critical thinking data were organized by day. The argumentation skills were organized by day and also on the basis of the groups. After generating codes during the inductive analysis of the development of critical thinking skills, a deductive approach was adopted (Patton, 2002 ). The critical thinking skills dimensions discussed by Ennis ( 2011 ) and Ennis ( 1991 ) were used to determine the relationship between codes. Ennis ( 2011 ) prepared an outline to distinguish critical thinking dispositions and skills by synthesizing of many years of studies. These critical skills that contain abilities that ideal critical thinkers have were used to generate codes from students’ talks. This skills and abilities were given in Appendix Table 10 . Then “clarification skills, decision making-supporting skills, inference skills, advanced clarification skills, and other/strategy and techniques skills” discussed by Ennis ( 1991 ) and Ennis ( 2011 ) were used to determine the categories. The change in the argumentation abilities of the students was analyzed descriptively based on the Toulmin argument model (Toulmin, 1990 ) using the data obtained from the students’ voice recordings. The argument structures of each group during verbal argumentation were determined by dividing them into components according to the Toulmin model (Toulmin, 1990 ). The first three items (data, claim, and warrant) in the Toulmin model form the basis of an argument, and the other three items (rebuttal, backing, and qualifier) are subsidiary elements of the argument (Toulmin, 1990 ).

Some quotations regarding the analysis of the arguments according to the items are given in Appendix Table 11 .

Arguments from the whole group were put into stages based on the argumentation-level model developed by Erduran et al. ( 2004 ) to examine the changes in each lesson and to make comparisons between the small groups of students. By considering the argument model developed by Toulmin, Erduran et al. ( 2004 ) created a five-level framework for the assessment of the quality of argumentation supposing that the quality of the arguments including rebuttals was high. The framework is given in Table 2 .

4.2 Validity and Reliability

To confirm the accuracy and validity of the analysis, method triangulation, triangulation of data sources, and analyst triangulation were used (Patton, 2002 ).

For analyst triangulation, the qualitative findings were also analyzed independently by a researcher studying in the field of critical thinking and argumentation, and then these evaluations made by the researchers were compared.

Video and audio recordings of intervention and documents from the activities were used for the triangulation of data sources. In addition, the data were described in detail without interpretation. Additionally, within the reliability and validity efforts, direct quotations were given in the findings. In this sense, for students, codes such as S1, S2, and S3 were used, and the source of data, group number, and relevant date of the conversation were included at the end of the quotations.

In addition, experts studying in the field of critical thinking and argumentation were asked to verify all data and findings. After the process of reflection and discussion with experts, the codes, subcategories, and categories were revised.

For reliability, some of the data randomly selected from the written transcripts of the students’ audio recordings were also coded by a second encoder, and the interrater agreement between the two coders, determined by Cohen’s kappa (Cohen, 1960 ), was κ = 0.86, which is considered high reliability.

5.1 Development of Critical Thinking Ability

The development of critical thinking skills was given separately for the trend drastically changed on the day when the first skills were used by the students. All six dimensions of critical thinking skills were included in students’ dialogs or when there was a decrease in the number of categories of critical thinking skills.

The codes, subcategories, and categories of critical thinking skills that occurred on the first day (dated 11.05) are given in Table 3 .

Clarification skills, inference skills, other/strategy and technical skills, advanced clarification skills, and decision-making/supporting skills occurred on the first day. The students mostly used decision-making/supporting skills ( f  = 55). Under the decision-making/supporting skills category, students mostly explained observation data ( f  = 37). S7, S1, and S20 stated the data they presented about their observations with the Star Chart and Sky View applications as follows:

S7: Venus is such a yellowish reddish colour.

S1: What was the colour? Red and big. The moon’s color is white.

S20: Not white here.

S20: It’s not white here. (Audio Recordings (AuR), Group 2 / 11.05).

Additionally, S19 mentioned the observation data with the words “I searched Saturn. It is bright. It does not vibrate. It is yellow and it’s large.” (AuR, Group 2 / 11.05).

Decision-making/supporting skills were followed by inference ( f  = 17), clarification ( f  = 13), advanced clarification ( f  = 5), and skills and other/strategy technical skills ( f  = 1).

In Table 4 , the categories, subcategories, and codes for critical thinking skills that occurred on the fifth day (dated 18.05) are presented.

It was observed for the first time on the fifth day that all six dimensions of critical thinking skills were included in students’ dialogs. These are, according to the frequency of use, inference ( f  = 152), decision-making/support ( f  = 116), clarification ( f  = 43), advanced clarification ( f  = 8), other/strategy and technique ( f  = 3), and suppositional thinking and integrational ( f  = 2) skills.

On this date, judging the credibility of the source from decision-making/supporting skills ( f  = 1) was the skill used for the first time.

Unlike other days, for the first time, a student tried to prove his thoughts with an analogy in advanced clarification skills. An exemplary dialogue to this finding is as follows:

S19: Even the Moon remains constant, we will see different faces of the moon because the Earth revolves around its axis.

S6: I also say that it turns at the same speed. So, for example, when this house turns like this while we return in the same way, we always see the same face. (AuR, 18.05, Group 2).

Here, S6 tried to explain to his friend that they always see the same face of the moon by comparing how they see the same face of the house.

In Table 5 , the categories, subcategories, and codes for critical thinking skills that occurred on the sixth day (dated 21.05) are included.

There is a decrease in the number of categories of critical thinking skills. It was determined that the students used mostly inference skills in three categories ( f  = 38). Additionally, students used decision-making/support ( f  = 34) and clarification ( f  = 9) skills. In inference skills, it is seen that students often make claims ( f  = 33) and rarely infer from the available data ( f  = 4).

Among the decision-making/support skills, students mostly used the skill to give reasons ( f  = 28). S24 accepted herself as Uranus during the activity, and she gave reason to make Saturn as an enemy like that: “No, Saturn would be my enemy too. Its ring is more distinctive, it can be seen from the Earth, its ring is more beautiful than me.” (AuR, 21.05, Group 3/).

The categories, subcategories, and codes for critical thinking skills that occurred on the ninth day (dated 28.05) are presented in Table 6 .

In the course of the day dated 28.05, six categories of critical thinking skills were observed: clarification, inference, other/strategy and technique, advanced clarification, decision-making/support, suppositional thinking and integration skills. Furthermore, the subcategories under these categories are also very diverse.

There are 10 subcategories under clarification skills ( f  = 57), which are the most commonly used skills. The frequency of using these skills is as follows: asking his friend about his opinion ( f  = 15), asking questions to clarify the situation ( f  = 12), explaining his statement ( f  = 10), summarizing the solutions of other groups ( f  = 7), asking for a detailed explanation ( f  = 4), summarizing the idea ( f  = 3), explaining the solution proposal ( f  = 2), asking for a reason ( f  = 2), focusing on the question ( f  = 1), and asking what the tools used in experiment do ( f  = 1) skills. Explaining the solution proposal, asking what the tools used in the experiment do, and focusing on the question are the first skills used by the students.

When the qualitative findings regarding the critical thinking skills of the students were examined as a whole, it was determined that there was an improvement in the students’ critical thinking skills dimensions in the lessons held in the first 5 days (between 11.05 and 18.05). There was a decrease in the number of critical thinking skills dimensions in the middle of the intervention (21.05). However, after this date, there was an increase again in the number of critical thinking skills dimensions; and on the last day of the intervention, all the critical thinking skills dimensions were used by the students. In addition, it was determined that the skills found under these dimensions showed great variety at this date. Only in the middle (18.05) and on the last day (28.05) of the intervention did students use the skills in the six dimensions of critical thinking.

It was determined that students used mostly decision-making/support, inference, and clarification skills. According to the days, it was determined that the students mostly used inference skills (12.05, 15.05, 18.05, and 21.05) among these skills.

5.2 The Argumentation Abilities of the Students

5.2.1 argument structures in students’ verbal argumentation activities.

Instead of the argument structures of all groups, only an example of one group is presented because of including both basic and subsidiary items in the Toulmin argument model. In Table 7 , the argument structures in the verbal argumentation activities of the fourth group of students are presented due to the use of the “rebuttal” item.

When the argument structures in the verbal argumentation process of the six groups were examined, it was found that all groups engaged in the argumentation and produced arguments. In the activities, students mostly made claims. This was followed by data and warrant items. In the “the phases of the moon” activity, it was determined that only the second and fourth groups used rebuttal and the other groups did not.

The number of rebuttals used by the groups is lower in “the planets-table of statements” activity than in other activities. The rebuttals used are also weak. The use of rebuttals differs in the “who is right?” and “urgent solution to space pollution” activities. The number of rebuttal students used in these activities is higher than that in the other activities. The quality rebuttals are also higher.

When the structure of the warrants is examined, there are more unscientific warrants in the “urgent solution to space pollution” and “who is right” activities, while the correct scientific and partially correct scientific warrants were more frequently used in the “the phases of the moon” and “the planets table of statements” activities.

When the models related to the argument structures are examined in general, it was found that there is a decrease in the type of items used and the number of uses in the “the phases of the moon” and “the planets-table of statements” activities rather than the “urgent solution to space pollution” and “who is right” activities.

When the results were analyzed in terms of groups, it was determined that the argument structures of the second and fourth groups showed more variety than those of the other groups.

5.2.2 The Change of Argumentation Levels

The argumentation levels achieved by six groups created in the “who is right,” “ the planets-table of statements,” “phases of the moon,” and “urgent solution to space pollution” activities are shown in Fig.  2 .

A characterization of the components of critical thinking (Jiménez-Aleixandre & Puig, 2012 , p. 6)

In the first verbal argumentation activity, “who is right?,” the arguments achieved by the five of the six groups were at level 5. Additionally, the arguments achieved by one group, which was group 6, were at level 4.

In the second verbal argumentation activity “table of statements,” a decrease was determined at the levels of the argumentation of the other groups except group 1 and group 3. In the “the phases of the moon” activity, there was a decrease at the level of argumentation achieved by the other groups except for group 2 and group 4. In the last argumentation activity, “urgent solution to space pollution,” it was found that the arguments of all groups were at level 5.

6 Conclusions and Discussion

The critical thinking skills of the students developed until the middle of the intervention, and the frequency of using critical thinking skills varied after the middle of the intervention. When the activities in the lessons were examined, on the days when critical thinking skills were frequently used, activities including argumentation methods were performed. Based on this situation, it could be revealed that the frequency of using critical thinking skills by students varies according to the use of the argumentation method.

Argumentation is defined as the process of making claims about a scientific subject, supporting them with data, providing reasons for proof, and criticizing, rebutting, and evaluating an idea (Toulmin, 1990 ). According to the definition of argumentation, these processes are also in the subdimensions of critical thinking skills. The ability to provide reasons for critical thinking skills in decision-making/supporting skills is the equivalent of providing reasons for proof in the argumentation process using warrants in the Toulmin argument model. Different types of claims under inference skills are related to making claims in the argumentation process, and rejecting a judgment is related to rebutting an idea in the argumentation process. In this context, the argumentation method is thought to contribute to the development of critical thinking skills within AR.

Another qualitative finding reached in the study is that the skills most used in the subdimensions differ according to the days. This can be explained by the different types of activities performed in each lesson. For example, on the day when the ability to explain observation data was used the most, students observed the sky, constellations, and galaxies with the Star Chart or Sky View applications or observed the planets with the i-Solar System application, and they presented the data they obtained during these observations.

Regarding the verbal argumentation structure of the groups, the findings imply that all groups engaged in argumentation and produced arguments. This finding presented evidence with qualitative data to further verify Squire & Jan’s ( 2007 ) research conducted with primary, middle, and high school students to investigate the potential of a location-based AR game in environmental science concluding that all groups engaged in argumentation. Similarly, Jan ( 2009 ) investigated the experience of three middle school students and their argumentative discourse on environmental education using a location-based AR game, and it was found that all students participated in argumentation and produced arguments.

Another finding in the current study was that students mostly made claims in the activities. This situation can be interpreted as students being strong in expressing their opinions. Similar findings are found in the literature (Author, 20xxa; Cavagnetto et al., 2010 ; Erduran et al., 2004 ; Novak & Treagust, 2017 ). In addition, it was concluded that the students failed to use warrants and data, they could not support their claims with the data, and they did not use “rebuttal” in these studies. However, in this study in which both augmented reality applications and argumentation methods were used, students mostly made contradictory claims and used data and warrants in their arguments. This situation can be interpreted as students being strong in defending their opinions. Additionally, although it was stated in many of the studies that students’ argumentation levels were generally at level 1 or level 2 (Erdogan et al., 2017 ; Erduran et al., 2004 ; Venville & Dawson, 2010 ; Zohar & Nemet, 2002 ), it was found that most of the students’ arguments were at level 4 and level 5 in the current study. Arguments are considered to be high quality in line with the existence of rebuttals, and discussions involving rebuttals are characterized as having a high level of argumentation (Aufschnaiter et al., 2008 ; Erduran et al., 2004 ). Students used rebuttals in their arguments, and their arguments were at high levels, which indicates that students could produce quality arguments. The reason for these findings to differ from those of other studies may be due to the augmented reality technology used in the current study. Enriched representations make it easier to see the structure of arguments (Akpınar et al., 2014 ), helping students to improve their awareness, increase the number of words they use and comments they make (Erkens & Janssen, 2006 ), and provide important information about the subject (Clark et al., 2007 ). By observing enriched representations, students collect evidence for argumentation (Clark & Sampson, 2008 ) and explore different points of view to support their claim (Oestermeier & Hesse, 2000 ). AR technology, which includes enriched representations, may have increased the accessibility of rich data to support students’ arguments; and using these data has helped them to support their arguments and enabled them to discover different perspectives. For example, S4 explained that the statement in the table is incorrect because she observed Uranus, Jupiter, and Neptune having rings around them in the application “I-solar system” as Uranus. She used the data obtained in the AR application to support her claim.

When the models related to the argument structures are examined in general, it was concluded that the type of items, the number of items, and the rebuttals used in scientific activities were less than those in the activities involving socioscientific issues. The rebuttals used were also weak. There are also findings in the literature that producing arguments on scientific issues is more difficult than producing arguments on socioscientific issues (Osborne et al., 2004 ).

When the structure of the warrants in the students’ arguments was examined, it was seen that there are more nonscientific warrants in socioscientific activities, and the scientific and partially scientific warrants are more in the activities that contain scientific subjects. This shows that students were unable to combine what they have learned in science with socioscientific issues. Albe ( 2008 ) and Kolsto ( 2001 ) stated that scientific knowledge is very low in students’ arguments on socioscientific issues. Similarly, the results of the studies conducted in the related literature support this view (Demircioglu & Ucar, 2014 ; Sadler & Donnelly, 2006 ; Wu & Tsai, 2007 ).

When the argument structures in the activities are analyzed by groups, the argument structures of the two groups vary more than the other groups, and the argumentation levels of these groups are at level 4 and level 5. This might be because some students have different prior knowledge about subjects. Different studies have also indicated that content knowledge plays an important role in the quality of students’ arguments (Acar, 2008 ; Aufschnaiter et al., 2008 ; Clark & Sampson, 2008 ; Cross et al., 2008 ; Sampson & Clark, 2011 ). In many studies, it has been emphasized that the most important thing affecting the choice and process of knowledge is previous information (Stark et al., 2009 ). To better understand how previous information affects argumentation quality in astronomy education, investigating the relationship between middle school students’ content knowledge and argumentation quality could be a direction of future research.

7 Limitations and Future Research

There are some limitations in this study. First, this study was implemented in a private school. Therefore, the results are true for these students. Future research is necessary to be performed with the students in public schools. Second, the researcher conducted the lessons because the science teacher had no ability to design AR learning practices. Teachers and students creating their own AR experiences is an important way to bring the learning outcomes of AR available to a wider audience (Romano et al., 2020 ). Further research can be conducted in which the science teacher of the class is the instructor. Another limitation of the study is that the instruction with AR-based argumentation was time-consuming, and the time allocated for the “Solar System and Beyond” unit in the curriculum was not sufficient for the implementation, because students tried to understand to use AR applications, and they needed time to reflect on the activities despite prior training on AR before the instructional process. This situation may cause cognitive overload (Alalwan et al., 2020 ). The adoption and implementation of educational technologies are more difficult and time-consuming than other methods (Parker & Heywood, 1998 ). A longer period is needed to prepare student-centered and technology-supported activities.

Acar, O. (2008).  Argumentation skills and conceptual knowledge of undergraduate students in a physics by inquiry class . (Doctoral dissertation, The Ohio State University). https://etd.ohiolink.edu/apexprod/rws_etd/send_file/send?accession=osu1228972473&disposition=inline

Akpınar, Y., Ardaç, D., & Er-Amuce, N. (2014). Development and validation of an argumentation based multimedia science learning environment: Preliminary findings. Procedia-Social and Behavioral Sciences, 116 , 3848–3853.

Article   Google Scholar  

Aktamış, H., & Arıcı, V. A. (2013). The effects of using virtual reality software in teaching astronomy subjects on academic achievement and retention. Mersin University Journal of the Faculty of Education, 9 (2), 58–70.

Google Scholar  

Alalwan, N., Cheng, L., Al-Samarraie, H., Yousef, R., Alzahrani, A. I., & Sarsam, S. M. (2020). Challenges and prospects of virtual reality and augmented reality utilization among primary school teachers: A developing country perspective. Studies in Educational Evaluation, 66 , 100876.

Albe, V. (2008). When scientific knowledge, daily life experience, epistemological and social considerations intersect: Students’ argumentation in group discussions on a socio-scientific issue. Research in Science Education, 38 (1), 67–90.

Arici, F., Yildirim, P., Caliklar, Ş, & Yilmaz, R. M. (2019). Research trends in the use of augmented reality in science education: Content and bibliometric mapping analysis. Computers & Education, 142 , 103647.

Atwood-Blaine, D., & Huffman, D. (2017). Mobile gaming and student interactions in a science center: The future of gaming in science education. International Journal of Science and Mathematics Education, 15 (1), 45–65.

Baran, B., Yecan, E., Kaptan, B., & Paşayiğit, O. (2020). Using augmented reality to teach fifth grade students about electrical circuits. Education and Information Technologies, 25 (2), 1371–1385.

Billinghurst, M. (2002). Augmented reality in education. New Horizons for Learning, 12 (5), 1–5.

Bressler, D. M., & Bodzin, A. M. (2013). A mixed methods assessment of students’ flow experiences during a mobile augmented reality science game. Journal of Computer Assisted Learning, 29 (6), 505–517.

Buckingham Shum, S. J., MacLean, A., Bellotti, V. M., & Hammond, N. V. (1997). Graphical argumentation and design cognition. Human-Computer Interaction, 12 (3), 267–300.

Cadmus, R. R., Jr. (1990). A video technique to facilitate the visualization of physical phenomena. American Journal of Physics, 58 (4), 397–399.

Cai, S., Chiang, F. K., & Wang, X. (2013). Using the augmented reality 3D technique for a convex imaging experiment in a physics course. International Journal of Engineering Education, 29 (4), 856–865.

Chai, C. S., Deng, F., Tsai, P. S., Koh, J. H. L., & Tsai, C. C. (2015). Assessing multidimensional students’ perceptions of twenty-first-century learning practices. Asia Pacific Education Review, 16 (3), 389–398.

Cai, S., Liu, C., Wang, T., Liu, E., & Liang, J. C. (2021). Effects of learning physics using augmented reality on students’ self-efficacy and conceptions of learning. British Journal of Educational Technology, 52 (1), 235–251.

Cavagnetto, A., Hand, B. M., & Norton-Meier, L. (2010). The nature of elementary student science discourse in the context of the science writing heuristic approach. International Journal of Science Education, 32 (4), 427–449.

Chang, H. Y., Wu, H. K., & Hsu, Y. S. (2013). Integrating a mobile augmented reality activity to contextualize student learning of a socioscientific issue. British Journal of Educational Technology, 44 (3), 95–99.

Chang, H. Y., Liang, J. C., & Tsai, C. C. (2020). Students’ context-specific epistemic justifications, prior knowledge, engagement, and socioscientific reasoning in a mobile augmented reality learning environment. Journal of Science Education and Technology, 29 (3), 399–408.

Chen, S. Y., & Liu, S. Y. (2020). Using augmented reality to experiment with elements in a chemistry course. Computers in Human Behavior, 111 (2020), 106418.

Chen, C. H., Yang, J. C., Shen, S., & Jeng, M. C. (2007). A desktop virtual reality earth motion system in astronomy education. Educational Technology & Society, 10 (3), 289–304.

Chen, C. H., Huang, C. Y., & Chou, Y. Y. (2019). Effects of augmented reality-based multidimensional concept maps on students’ learning achievement, motivation and acceptance. Universal Access in the Information Society, 18 (2), 257–268.

Chen, C. C., Chen, H. R., & Wang, T. Y. (2022). Creative situated augmented reality learning for astronomy curricula. Educational Technology & Society, 25 (2), 148–162.

Cheng, K. H., & Tsai, C. C. (2013). Affordances of augmented reality in science learning: Suggestions for future research. Journal of Science Education and Technology, 22 (4), 449–462.

Chiang, T. H. C., Yang, S. J. H., & Hwang, G. J. (2014). An augmented reality-based mobile learning system to improve students’ learning achievements and motivations in natural science inquiry activities. Journal of Educational Technology & Society, 17 (4), 352–365.

Clark, D. B., & Sampson, V. (2008). Assessing dialogic argumentation in online environments to relate structure, grounds, and conceptual quality. Journal of Research in Science Teaching, 45 (3), 293–321.

Clark, D. B., Stegmann, K., Weinberger, A., Menekse, M., & Erkens, G. (2007). Technology-enhanced learning environments to support students’ argumentation. In S. Erduran & M. P. Jimenez-Aleixandre (Eds.), Argumentation in science education: Perspectives from classroom-based research (pp. 217–243). Springer.

Chapter   Google Scholar  

Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20 (1), 37–46.

Cross, D., Taasoobshirazi, G., Hendricks, S., & Hickey, D. T. (2008). Argumentation: A strategy for improving achievement and revealing scientific identities. International Journal of Science Education, 30 (6), 837–861.

Demircioglu, T., & Ucar, S. (2014). Investigation of written arguments about Akkuyu nuclear power plant. Elementary Education Online, 13 (4), 1373–1386.

Demircioglu, T., & Ucar, S. (2015). Investigation the effect of argument-driven inquiry in laboratory instruction. Educational Sciences: Theory and Practice, 15 (1), 267–283.

Dias, A. (2009). Technology enhanced learning and augmented reality: An application on multimedia interactive books. International Business & Economics Review, 1 (1), 69–79.

Dietrich, N., Kentheswaran, K., Ahmadi, A., Teychené, J., Bessière, Y., Alfenore, S., Laborie, S., & Hébrard, G. (2020). Attempts, successes, and failures of distance learning in the time of COVID-19. Journal of Chemical Education, 97 (9), 2448–2457.

Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84 , 287–312.

Dunleavy, M., Dede, C., & Mitchell, R. (2009). Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. Journal of Science Education and Technology, 18 (1), 7–22.

Ennis, R. H. (1991). Goals for a critical thinking curriculum. In A. Costa (Ed.), Developing minds: A resource book for teaching thinking (pp. 68–71). The Association of Supervision and Curriculum Development.

Ennis, R. H. (2011). The nature of critical thinking: An outline of critical thinking dispositions and abilities. Illinois College of Education. https://education.illinois.edu/docs/default-source/faculty-documents/robert-ennis/thenatureofcriticalthinking_51711_000.pdf

Erdogan, I., Ciftci, A., & Topcu, M. S. (2017). Examination of the questions used in science lessons and argumentation levels of students. Journal of Baltic Science Education, 16 (6), 980–993.

Erduran, S. (2020). Science education in the era of a pandemic: How can history, philosophy and sociology of science contribute to education for understanding and solving the Covid-19 crisis? Science & Education, 29 , 233–235.

Erduran, S., Simon, S., & Osborne, J. (2004). TAPping into argumentation: Developments in the application of Toulmin’s argument pattern for studying science discourse. Science Education, 88 (6), 915–933.

Erduran, S., Özdem, Y., & Park, J. Y. (2015). Research trends on argumentation in science education: A journal content analysis from 1998–2014. International Journal of STEM Education, 2 (1), 1–12.

Erkens, G., & Janssen, J. (2006). Automatic coding of communication in collaboration protocols. In S. Barab, K. Hay, & D. Hickey (Eds.), Proceedings of the 7th International Conference on Learning Sciences (ICLS) , (pp. 1063–1064). International Society of the Learning Sciences. https://doi.org/10.5555/1150034

Faridi, H., Tuli, N., Mantri, A., Singh, G., & Gargrish, S. (2020). A framework utilizing augmented reality to improve critical thinking ability and learning gain of the students in Physics. Computer Applications in Engineering Education, 29 , 258–273.

Fidan, M., & Tuncel, M. (2019). Integrating augmented reality into problem based learning: The effects on learning achievement and attitude in physics education. Computers & Education, 142 , 103635.

Fleck, S., & Simon, G. (2013, November). An augmented reality environment for astronomy learning in elementary grades: An exploratory study. In  Proceedings of the 25th Conference on l ’ Interaction Homme-Machine  (pp. 14–22). ACM.

Garzón, J., & Acevedo, J. (2019). Meta-analysis of the impact of augmented reality on students’ learning gains. Educational Research Review, 27 , 244–260.

Garzón, J., Pavón, J., & Baldiris, S. (2019). Systematic review and meta-analysis of augmented reality in educational settings. Virtual Reality , 1–13

Garzón, J., Baldiris, S., Gutiérrez, J., & Pavón, J. (2020). How do pedagogical approaches affect the impact of augmented reality on education? A meta-analysis and research synthesis.  Educational Research Review , 100334.

Guba, E.G. & Lincoln, Y.S. (1989). Fourth generation evaluation . Sage Publications.

Hanid, M. F. A., Said, M. N. H. M., & Yahaya, N. (2020). Learning strategies using augmented reality technology in education: Meta-analysis. Universal Journal of Educational Research, 8 (5A), 51–56.

Hsiao, H. S., Chang, C. S., Lin, C. Y., & Wang, Y. Z. (2016). Weather observers: A manipulative augmented reality system for weather simulations at home, in the classroom, and at a museum. Interactive Learning Environments, 24 (1), 205–223.

Huang, K. T., Ball, C., Francis, J., Ratan, R., Boumis, J., & Fordham, J. (2019). Augmented versus virtual reality in education: An exploratory study examining science knowledge retention when using augmented reality/virtual reality mobile applications. Cyberpsychology, Behavior, and Social Networking, 22 (2), 105–110.

Hwang, G. J., Wu, P. H., Chen, C. C., & Tu, N. T. (2016). Effects of an augmented reality-based educational game on students’ learning achievements and attitudes in real-world observations. Interactive Learning Environments, 24 (8), 1895–1906.

Ibáñez, M. B., Di Serio, Á., Villarán, D., & Kloos, C. D. (2014). Experimenting with electromagnetism using augmented reality: Impact on flow student experience and educational effectiveness. Computers & Education, 71 , 1–13.

Jan, M. (2009). Designing an augmented reality game-based curriculum for argumentation . (Unpublished doctoral dissertation). University of Wisconsin-Madison.

Jermann, P., & Dillenbourg, P. (2003). Elaborating new arguments through a CSCL script. In J. Andriessen, M. Baker, & D. Suthers (Eds.), Arguing to learn: Confronting cognitions in computer-supported collaborative learning environments (pp. 205–226). Springer.

Jiménez –Aleixandre, M. P., & Erduran, S. (2007). Argumentation in science education: An overview. In S. Erduran & M. P. Jimenez-Aleixandre (Eds.), Argumentation in science education: Perspectives from classroom-based research (pp. 3–27). Springer.

Jiménez-Aleixandre, M. P., & Puig, B. (2012). Argumentation, evidence evaluation and critical thinking. In  Second international handbook of science education  (pp. 1001–1015). Springer, Dordrecht.

Ke, F., & Carafano, P. (2016). Collaborative science learning in an immersive flight simulation. Computers & Education, 103 , 114–123.

Kennedy, G., Dalgarno, B., Bennett, S., Judd, T., Gray, K., & Chang, R. (2008). Immigrants and natives: Investigating differences between staff and students’ use of technology. In Hello! Where are you in the landscape of educational technology? . Proceedings Ascilite Melbourne, 2008 , 484–492.

Kerawalla, L., Luckin, R., Seljeflot, S., & Woolard, A. (2006). “Making it real”: Exploring the potential of augmented reality for teaching primary school science. Virtual Reality, 10 (3–4), 163–174.

Kirikkaya, E. B., & Başgül, M. Ş. (2019). The effect of the use of augmented reality applications on the academic success and motivation of 7th grade students. Journal of Baltic Science Education, 18 (3), 362.

Kolsto, S. D. (2001). ‘To trust or not to trust,…’-pupils’ ways of judging information encountered in a socio-scientific issue. International Journal of Science Education, 23 (9), 877–901.

Lin, S. S., & Mintzes, J. J. (2010). Learning argumentation skills through instruction in socioscientific issues: The effect of ability level. International Journal of Science and Mathematics Education, 8 (6), 993–1017.

López-Faican, L., & Jaen, J. (2020). Emofindar: Evaluation of a mobile multiplayer augmented reality game for primary school children. Computers & Education, 149 (2020), 103814.

Lu, S. J., Liu, Y. C., Chen, P. J., & Hsieh, M. R. (2020). Evaluation of AR embedded physical puzzle game on students’ learning achievement and motivation on elementary natural science. Interactive Learning Environments, 28 (4), 451–463.

Maykut, P., & Morehouse, R. (1994). Beginning qualitative research: A philosophic and practical guide. The Falmer Press.

Novak, A. M., & Treagust, D. F. (2017). Adjusting claims as new evidence emerges: Do students incorporate new evidence into their scientific explanations? Journal of Research in Science Teaching, 55 (4), 526–549.

Nussbaum, E. M. (2008). Collaborative discourse, argumentation, and learning: Preface and literature review. Contemporary Educational Psychology, 33 (3), 345–359.

OECD. (2003). Literacy skills for the world of tomorrow: Further results from PISA 2003 . OECD Publishing.

Book   Google Scholar  

Oestermeier, U., & Hesse, F. W. (2000). Verbal and visual causal arguments. Cognition, 75 (1), 65–104.

Oleksiuk, V.P., Oleksiuk, O.R. (2020). Exploring the potential of augmented reality for teaching school computer science. In Burov, O.Yu., Kiv, A.E. (Eds.) Proceedings of the 3rd International Workshop on Augmented Reality in Education (AREdu 2020) (pp. 91–107).

Osborne, J., Erduran, S., & Simon, S. (2004). Enhancing the quality of argument in school science. Journal of Research in Science Teaching, 41 (10), 994–1020.

Parker, J., & Heywood, D. (1998). The earth and beyond: Developing primary teachers’ understanding of basic astronomical events. International Journal of Science Education, 20 , 503–520.

Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Sage.

Pellas, N., Fotaris, P., Kazanidis, I., & Wells, D. (2019). Augmenting the learning experience in primary and secondary school education: A systematic review of recent trends in augmented reality game-based learning. Virtual Reality, 23 (4), 329–346.

Ploman, E. W. (1987), Global learning: A challenge. In C. A., Taylor (Ed.) Science education and information transfer (pp. 75–80). Oxford: Pergamon (for ICSU Press).

Radu, I., & Schneider, B. (2019). What can we learn from augmented reality (AR)? Benefits and drawbacks of AR for inquiry-based learning of physics. In  Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems  (pp. 1–12).

Rideout, V. J., Foehr, U. G., & Roberts, D. F. (2010). Generation M [superscript 2]: Media in the lives of 8-to 18-year-olds . Kaiser Family Foundation.

Rieber, L. P., & Kini, A. S. (1991). Theoretical foundations of instructional applications of computer-generated animated visuals. Journal of Computer-Based Instruction, 18 , 83e88.

Romano, M., Díaz, P., & Aedo, I. (2020). Empowering teachers to create augmented reality experiences: The effects on the educational experience.  Interactive Learning Environments , 1–18.

Sadler, T. D., & Donnelly, L. A. (2006). Socioscientific argumentation: The effects of content knowledge and morality. International Journal of Science Education, 28 (12), 1463–1488.

Sahin, D., & Yilmaz, R. M. (2020). The effect of augmented reality technology on middle school students’ achievements and attitudes towards science education. Computers & Education, 144 (2020), 103710.

Sampson, V., & Clark, D. B. (2011). A comparison of the collaborative scientific argumentation practices of two high and two low performing groups. Research in Science Education, 41 (1), 63–97.

Sampson, V., & Gleim, L. (2009). Argument-driven ınquiry to promote the understanding of important concepts & practices in biology. The American Biology Teacher, 71 (8), 465–472.

Sampson, V., Grooms, J., & Walker, J. P. (2011). Argument-driven ınquiry as a way to help students learn how to participate in scientific argumentation and craft written arguments: An exploratory study. Science Education, 95 (2), 217–257.

Sandoval, W. A., & Millwood, K. A. (2005). The quality of students’ use of evidence in written scientific explanations. Cognition and Instruction, 23 (1), 23–55.

Saribas, D., & Çetinkaya, E. (2021). Pre-service teachers’ analysis of claims about COVID-19 in an online course. Science & Education, 30 (2), 235–266.

Schnotz, W., & Lowe, R. K. (2008). A unified view of learning from animated and static graphics. In R. K. Lowe & W. Schnotz (Eds.), Learning with animation: Research implications for design (pp. 304–357). Cambridge University Press.

Setozaki, N., Suzuki, K., Iwasaki, T., & Morita, Y. (2017). Development and evaluation of the usefulness of collaborative learning on the tangible AR learning equipment for astronomy education. Educational Technology Research, 40 (1), 71–83.

Shelton, B. E. & Hedley, N. R. (2002). Using augmented reality for teaching earth-sun relationships to undergraduate geography students. In Augmented Reality Toolkit, The First IEEE International Workshop (8).

Sin, A. K., & Zaman, H. B. (2010). Live solar system (LSS): Evaluation of an augmented reality book-based educational tool. In Proceedings of 2010 International Symposium on Information Technology, 1 , 1–6.

Squire, K. (2006). From content to context: Videogames as designed experience. Educational Researcher, 35 (8), 19–29.

Squire, K. D., & Jan, M. (2007). Mad City Mystery: Developing scientific argumentation skills with a place-based augmented reality game on handheld computers. Journal of Science Education and Technology, 16 (1), 5–29.

Stark, R., Puhl, T., & Krause, U. M. (2009). Improving scientific argumentation skills by a problem-based learning environment: Effects of an elaboration tool and relevance of student characteristics. Evaluation & Research in Education, 22 (1), 51–68.

Syawaludin, A., Gunarhadi, R., & P. (2019). Development of augmented reality-based interactive multimedia to improve critical thinking skills in science learning. International Journal of Instruction, 12 (4), 331–344.

Taylor, C. A. (1987). Science education and information transfer (pp.1–15). Oxford: Pergamon (for ICSU Press)

Toulmin, S. E. (1990). The uses of argument (10th ed.). Cambridge University Press.

Venville, G. J., & Dawson, V. M. (2010). The impact of a classroom intervention on grade 10 students’ argumentation skills, informal reasoning, and conceptual understanding of science. Journal of Research in Science Teaching, 47 (8), 952–977.

Virata, R. O., & Castro, J. D. L. (2019). Augmented reality in science classroom: Perceived effects in education, visualization and information processing. In  Proceedings of the 10th International Conference on E-Education, E-Business, E-Management and E-Learning  (pp. 85–92).

Von Aufschnaiter, C., Erduran, S., Osborne, J., & Simon, S. (2008). Arguing to learn and learning to argue: Case studies of how students’ argumentation relates to their scientific knowledge. Journal of Research in Science Teaching, 45 (1), 101–131.

Wu, Y. T., & Tsai, C. C. (2007). High school students’ informal reasoning on a socio-scientific issue: Qualitative and quantitative analyses. International Journal of Science Education, 29 (9), 1163–1187.

Yen, J. C., Tsai, C. H., & Wu, M. (2013). Augmented reality in the higher education: Students’ science concept learning and academic achievement in astronomy. Procedia-Social and Behavioral Sciences, 103 , 165–173.

Yildirim, I., & Seckin-Kapucu, M. (2020). The effect of augmented reality applications in science education on academic achievement and retention of 6th grade students. Journal of Education in Science Environment and Health, 7 (1), 56–71.

Yu, K. C., & Sahami, K. (2007). Visuospatial astronomy education in immersive digital planetariums.  Communicating Astronomy with the Public , 242–245.

Yuen, S., Yaoyuneyong, G., & Johnson, E. (2011). Augmented reality: An overview and five directions for AR in education. Journal of Educational Technology Development and Exchange, 4 (1), 119–140.

Zhang, J., Sung, Y.-T., Hou, H.-T., & Chang, K.-E. (2014). The development and evaluation of an augmented reality-based armillary sphere for astronomical observation instruction. Computers & Education, 73 , 178–188.

Zohar, A., & Nemet, F. (2002). Fostering students’ knowledge and argumentation skills through dilemmas in human genetics. Journal of Research in Science Teaching, 39 (1), 35–62.

Download references

This study is a part of Tuba Demircioğlu’s dissertation supported by the Cukurova University Scientific Research Projects (grant number: SDK20153929).

The manuscript is part of first author’s PhD dissertation. The study was reviewed and approved by the PhD committee in the Cukurova University Faculty of Education, as well as by the committee of Ministry of National Education. The parents of students were provided with written informed consent.

Author information

Authors and affiliations.

Faculty of Education, Department of Mathematics and Science Education/Elementary Science Education, Cukurova University, 01330, Saricam-Adana, Turkey

Tuba Demircioglu & Sedat Ucar

Department of Educational Sciences, Cukurova University, Adana, Turkey

Memet Karakus

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Tuba Demircioglu .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Tables 8 , 9 , 10 and 11

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Demircioglu, T., Karakus, M. & Ucar, S. Developing Students’ Critical Thinking Skills and Argumentation Abilities Through Augmented Reality–Based Argumentation Activities in Science Classes. Sci & Educ 32 , 1165–1195 (2023). https://doi.org/10.1007/s11191-022-00369-5

Download citation

Accepted : 15 July 2022

Published : 22 August 2022

Issue Date : August 2023

DOI : https://doi.org/10.1007/s11191-022-00369-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Find a journal
• Publish with us
• Track your research