problems/ideas
critically and/or
creatively
Elements, excerpts, and ideas borrowed with permission form Assessing Outcomes and Improving Achievement: Tips and tools for Using Rubrics , edited by Terrel L. Rhodes. Copyright 2010 by the Association of American Colleges and Universities.
Developing strong SLOs involves clearly articulating what students will be able to demonstrate by the end of a course or program. Here are some key elements to consider:
Examples of Fink's Taxonomy in Action:
By following these tips and leveraging Fink's Taxonomy, you can craft SLOs that are clear, measurable, and aligned with your course or program objectives. Let's work together to empower students on their academic journey and prepare them for lifelong success.
Below are several quick tips to keep in mind when designing or revising your SLOs:
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Critical writing.
Students sometimes receive feedback such as "your essay is too descriptive" or "you need to show more critical analysis". While some description may be necessary – for instance if you are providing background information – most university assignments require you to produce work that is analytical and critical in its approach.
Your writing needs to show your interpretation of the evidence and source material, how you have used that information to demonstrate your understanding, and your subsequent position on the topic. Being critical in your writing means engaging in academic debates and research happening in your subject area.
The sources you select, the way you show how they agree or disagree with other pieces of evidence, and the way you structure your argument will all show your thought process and how you have understood the information you have read.
Always keep your reader in mind and try to anticipate the questions they would ask — refer back to the Critical thinking questions (PDF) to help you with this. You can use evidence to help you strengthen your position, answer readers' questions, and "neutralise" opposing points of view.
Remember to keep descriptive statements to a minimum — there is no need to provide large amounts of background or historical information.
Make sure you move from description to analysis and evaluation . Give your interpretation of the facts, and explain the significance, consequences and implications of the statements you have made.
See our advice on structuring a paragraph for more information on how to attach analysis and evaluation to each point you make.
The following examples demonstrate the difference between descriptive writing and critical/analytical writing. They are taken from: Cottrell, S. 2003. The Study Skills Handbook . 2nd ed. London: Palgrave.
To write critically you will need to not only describe what happened, but also identify the significance of what happened.
"The data shows that the incidence (new cases) of asthma rates in children under 15 years old increased rapidly from 1977, peaking in 1993 and then declining, though rates still remain significantly higher than pre-1976 levels."
"The trend, from 1977 until 1993, of a rapid rise in rates of asthma diagnosis in children under 15 years, suggests that one of the causal factors was particularly prevalent during this time, but has since declined in importance or effect."
Descriptive writing will explain what the theory says. To write critically you need to go further and show why that theory is relevant.
"Carl Rogers' theory of a person-centred approach focuses on the freedom of the individual to determine what values should be used to measure successful personal outcomes or benefit, and is particularly relevant for social workers when wanting to take into account the diverse needs of the client group."
"Carl Rogers' theory of a person-centred approach is particularly suitable for social workers wanting to work with a client group with diverse needs because it allows the client to determine what values should be used to measure successful outcomes, rather than those externally determined by, for example, the service, state or dominant culture in society."
Rather than simply noting the method used, which is the descriptive approach, a critical writer will show how appropriate that method was.
"In addition to competency-based questions, the candidates were asked to complete an in-tray exercise, which required them to allocate different priority levels to tasks, as an appropriate method to measure their likely performance in the actual job."
"In addition to competency-based questions, candidates were asked to complete an in-tray task prioritisation exercise. This was because it was considered a more effective way to measure likely performance in the actual role as the majority of the job would involve similar tasks, with little interaction with customers and therefore less requirement for highly developed communication skills."
You can apply our critical thinking model to your own work; use our Judging your own work (PDF) questions to help you decide if your writing is critical. These questions will take you through the description-analysis-evaluation stages. Take a look at further examples of descriptive writing vs. critical/analytical writing (PDF)
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Ian j. quitadamo.
*Department of Biological Sciences, Central Washington University, Ellensburg, WA 98926-7537; and
† Department of Chemistry, Central Washington University, Ellensburg, WA 98926-7539
Increasingly, national stakeholders express concern that U.S. college graduates cannot adequately solve problems and think critically. As a set of cognitive abilities, critical thinking skills provide students with tangible academic, personal, and professional benefits that may ultimately address these concerns. As an instructional method, writing has long been perceived as a way to improve critical thinking. In the current study, the researchers compared critical thinking performance of students who experienced a laboratory writing treatment with those who experienced traditional quiz-based laboratory in a general education biology course. The effects of writing were determined within the context of multiple covariables. Results indicated that the writing group significantly improved critical thinking skills whereas the nonwriting group did not. Specifically, analysis and inference skills increased significantly in the writing group but not the nonwriting group. Writing students also showed greater gains in evaluation skills; however, these were not significant. In addition to writing, prior critical thinking skill and instructor significantly affected critical thinking performance, whereas other covariables such as gender, ethnicity, and age were not significant. With improved critical thinking skill, general education biology students will be better prepared to solve problems as engaged and productive citizens.
A national call to improve critical thinking in science.
In the past several years, an increasing number of national reports indicate a growing concern over the effectiveness of higher education teaching practices and the decreased science (and math) performance of U.S. students relative to other industrialized countries ( Project Kaleidoscope, 2006 ). A variety of national stakeholders, including business and educational leaders, politicians, parents, and public agencies, have called for long-term transformation of the K–20 educational system to produce graduates who are well trained in science, can engage intelligently in global issues that require local action, and in general are better able to solve problems and think critically. Specifically, business leaders are calling for graduates who possess advanced analysis and communication skills, for instructional methods that improve lifelong learning, and ultimately for an educational system that builds a nation of innovative and effective thinkers ( Business-Higher Education Forum and American Council on Education, 2003 ). Education leaders are similarly calling for institutions of higher education to produce graduates who think critically, communicate effectively, and who employ lifelong learning skills to address important scientific and civic issues ( Association of American Colleges and Universities, [AACU] 2005 ).
Many college faculty consider critical thinking to be one of the most important indicators of student learning quality. In its 2005 national report, the AACU indicated that 93% of higher education faculty perceived analytical and critical thinking to be an essential learning outcome (AACU, 2005) whereas 87% of undergraduate students indicated that college experiences contributed to their ability to think analytically and creatively. This same AACU report showed that only 6% of undergraduate seniors demonstrated critical thinking proficiency based on Educational Testing Services standardized assessments from 2003 to 2004. During the same time frame, data from the ACT Collegiate Assessment of Academic Proficiency test showed a similar trend, with undergraduates improving their critical thinking less than 1 SD from freshman to senior year. Thus, it appears a discrepancy exists between faculty expectations of critical thinking and students' ability to perceive and demonstrate critical thinking proficiency using standardized assessments (AACU, 2005).
Teaching that supports the development of critical thinking skills has become a cornerstone of nearly every major educational objective since the Department of Education released its six goals for the nation's schools in 1990. In particular, goal three of the National Goals for Education stated that more students should be able to reason, solve problems, and apply knowledge. Goal six specifically stated that college graduates must be able to think critically ( Office of Educational Research and Improvement, 1991 ). Since 1990, American education has tried—with some success—to make a fundamental shift from traditional teacher-focused instruction to more student-centered constructivist learning that encourages discovery, reflection, and in general is thought to improve student critical thinking skill. National science organizations have supported this trend with recommendations to improve the advanced thinking skills that support scientific literacy ( American Association for Higher Education, 1989 ; National Research Council, 1995 ; National Science Foundation, 1996 ).
More recent reports describe the need for improved biological literacy as well as international competitiveness ( Bybee and Fuchs, 2006 ; Klymkowsky, 2006 ). Despite the collective call for enhanced problem solving and critical thinking, educators, researchers, and policymakers are discovering a lack of evidence in existing literature for methods that measurably improve critical thinking skills ( Tsui, 1998 , 2002 ). As more reports call for improved K–20 student performance, it is essential that research-supported teaching and learning practices be used to better help students develop the cognitive skills that underlie effective science learning ( Malcom et al., 2005 ; Bybee and Fuchs, 2006 ).
Although they are not always transparent to many college students, the academic and personal benefits of critical thinking are well established; students who can think critically tend to get better grades, are often better able to use reasoning in daily decisions ( U.S. Department of Education, 1990 ), and are generally more employable ( Carnevale and American Society for Training and Development, 1990 ; Holmes and Clizbe, 1997 ; National Academy of Sciences, 2005 ). By focusing on instructional efforts that develop critical thinking skills, it may be possible to increase student performance while satisfying national stakeholder calls for educational improvement and increased ability to solve problems as engaged and productive citizens.
Although academics and business professionals consider critical thinking skill to be a crucial outcome of higher education, many would have difficulty defining exactly what critical thinking is. Historically, there has been little agreement on how to conceptualize critical thinking. Of the literally dozens of definitions that exist, one of the most organized efforts to define (and measure) critical thinking emerged from research done by Peter Facione and others in the early 1990s. Their consensus work, referred to as the Delphi report, was accomplished by a group of 46 leading theorists, teachers, and critical thinking assessment specialists from a variety of academic and business disciplines ( Facione and American Philosophical Association, 1990 ). Initial results from the Delphi report were later confirmed in a national survey and replication study ( Jones et al., 1995 ). In short, the Delphi panel expert consensus describes critical thinking as a “process of purposeful self-regulatory judgment that drives problem-solving and decision-making” ( Facione and American Philosophical Association, 1990 ). This definition implies that critical thinking is an intentional, self-regulated process that provides a mechanism for solving problems and making decisions based on reasoning and logic, which is particularly useful when dealing with issues of national and global significance.
The Delphi conceptualization of critical thinking encompasses several cognitive skills that include: 1) analysis (the ability to break a concept or idea into component pieces in order to understand its structure and inherent relationships), 2) inference (the skills used to arrive at a conclusion by reconciling what is known with what is unknown), and 3) evaluation (the ability to weigh and consider evidence and make reasoned judgments within a given context). Other critical thinking skills that are similarly relevant to science include interpretation, explanation, and self-regulation ( Facione and American Philosophical Association, 1990 ). The concept of critical thinking includes behavioral tendencies or dispositions as well as cognitive skills ( Ennis, 1985 ); these include the tendency to seek truth, to be open-minded, to be analytical, to be orderly and systematic, and to be inquisitive ( Facione and American Philosophical Association, 1990 ). These behavioral tendencies also align closely with behaviors considered to be important in science. Thus, an increased focus on teaching critical thinking may directly benefit students who are engaged in science.
Prior research on critical thinking indicates that students' behavioral dispositions do not change in the short term ( Giancarlo and Facione, 2001 ), but cognitive skills can be developed over a relatively short period of time (Quitadamo, Brahler, and Crouch, unpublished results). In their longitudinal study of behavioral disposition toward critical thinking, Giancarlo and Facione (2001) discovered that undergraduate critical thinking disposition changed significantly after two years. Specifically, significant changes in student tendency to seek truth and confidence in thinking critically occurred during the junior and senior years. Also, females tended to be more open-minded and have more mature judgment than males ( Giancarlo and Facione, 2001 ). Although additional studies are necessary to confirm results from the Giancarlo study, existing research seems to indicate that changes in undergraduate critical thinking disposition are measured in years, not weeks.
In contrast to behavioral disposition, prior research indicates that critical thinking skills can be measurably changed in weeks. In their study of undergraduate critical thinking skill in university science and math courses, Quitadamo, Brahler, and Crouch (unpublished results) showed that critical thinking skills changed within 15 wk in response to Peer Led Team Learning (a national best practice for small group learning). This preliminary study provided some evidence that undergraduate critical thinking skills could be measurably improved within an academic semester, but provided no information about whether critical thinking skills could be changed during a shorter academic quarter. It was also unclear whether the development of critical thinking skills was a function of chronological time or whether it was related to instructional time.
Numerous studies provide anecdotal evidence for pedagogies that improve critical thinking, but much of existing research relies on student self-report, which limits the scope of interpretation. From the literature it is clear that, although critical thinking skills are some of the most valued outcomes of a quality education, additional research investigating the effects of instructional factors on critical thinking performance is necessary ( Tsui, 1998 , 2002 ).
Writing has been widely used as a tool for communicating ideas, but less is known about how writing can improve the thinking process itself ( Rivard, 1994 ; Klein, 2004 ). Writing is thought to be a vehicle for improving student learning ( Champagne and Kouba, 1999 ; Kelly and Chen, 1999 ; Keys, 1999 ; Hand and Prain, 2002 ), but too often is used as a means to regurgitate content knowledge and derive prescribed outcomes ( Keys, 1999 ; Keys et al., 1999 ). Historically, writing is thought to contribute to the development of critical thinking skills ( Kurfiss, and Association for the Study of Higher Education, 1988 ). Applebee (1984) suggested that writing improves thinking because it requires an individual to make his or her ideas explicit and to evaluate and choose among tools necessary for effective discourse. Resnick (1987) stressed that writing should provide an opportunity to think through arguments and that, if used in such a way, could serve as a “cultivator and an enabler of higher order thinking.” Marzano (1991) suggested that writing used as a means to restructure knowledge improves higher-order thinking. In this context, writing may provide opportunity for students to think through arguments and use higher-order thinking skills to respond to complex problems ( Marzano, 1991 ).
Writing has also been used as a strategy to improve conceptual learning. Initial work focused on how the recursive and reflective nature of the writing process contributes to student learning ( Applebee, 1984 ; Langer and Applebee, 1985 , 1987 ; Ackerman, 1993 ). However, conclusions from early writing to learn studies were limited by confounding research designs and mismatches between writing activities and measures of student learning ( Ackerman, 1993 ). Subsequent work has focused on how writing within disciplines helps students to learn content and how to think. Specifically, writing within disciplines is thought to require deeper analytical thinking ( Langer and Applebee, 1987 ), which is closely aligned with critical thinking.
The influence of writing on critical thinking is less defined in science. Researchers have repeatedly called for more empirical investigations of writing in science; however, few provide such evidence ( Rivard, 1994 ; Tsui, 1998 ; Daempfle, 2002 ; Klein, 2004 ). In his extensive review of writing research, Rivard (1994) indicated that gaps in writing research limit its inferential scope, particularly within the sciences. Specifically, Rivard and others indicate that, despite the volume of writing students are asked to produce during their education, they are not learning to use writing to improve their awareness of thinking processes ( Resnick, 1987 ; Howard, 1990 ). Existing studies are limited because writing has been used either in isolation or outside authentic classroom contexts. Factors like gender, ethnicity, and academic ability that are not directly associated with writing but may nonetheless influence its effectiveness have also not been sufficiently accounted for in previous work ( Rivard, 1994 ).
A more recent review by Daempfle (2002) similarly indicates the need for additional research to clarify relationships between writing and critical thinking in science. In his review, Daempfle identified nine empirical studies that generally support the hypothesis that students who experience writing (and other nontraditional teaching methods) have higher reasoning skills than students who experience traditional science instruction. Of the relatively few noninstructional variables identified in those studies, gender and major did not affect critical thinking performance; however, the amount of time spent on and the explicitness of instruction to teach reasoning skills did affect overall critical thinking performance. Furthermore, the use of writing and other nontraditional teaching methods did not appear to negatively affect content knowledge acquisition ( Daempfle, 2002 ). Daempfle justified his conclusions by systematically describing the methodological inconsistencies for each study. Specifically, incomplete sample descriptions, the use of instruments with insufficient validity and reliability, the absence of suitable comparison groups, and the lack of statistical covariate analyses limit the scope and generalizability of existing studies of writing and critical thinking ( Daempfle, 2002 ).
The conceptual nature and reliance on the scientific method as a means of understanding make the field of biology a natural place to teach critical thinking through writing. Some work has been done in this area, with literature describing various approaches to writing in the biological sciences that range from linked biology and English courses, writing across the biology curriculum, and directed use of writing to improve reasoning in biology courses ( Ebert-May et al., 1997 ; Holyoak, 1998 ; Taylor and Sobota, 1998 ; Steglich, 2000 ; Lawson, 2001 ; Kokkala and Gessell, 2003 ; Tessier, 2006 ). In their work on integrated biology and English, Taylor and Sobota (1998) discussed several problem areas that affected both biology and English students, including anxiety and frustration associated with writing, difficulty expressing thoughts clearly and succinctly, and a tendency to have strong negative responses to writing critique. Although the authors delineate the usefulness of several composition strategies for writing in biology ( Taylor and Sobota, 1998 ), it was unclear whether student data were used to support their recommendations. Kokkala and Gessell (2003) used English students to evaluate articles written by biology students. Biology students first reflected on initial editorial comments made by English students, and then resubmitted their work for an improved grade. In turn, English students had to justify their editorial comments with written work of their own. Qualitative results generated from a list of reflective questions at the end of the writing experience seemed to indicate that both groups of students improved editorial skills and writing logic. However, no formal measures of student editorial skill were collected before biology-English student collaboration, so no definitive conclusions on the usefulness of this strategy could be made.
Taking a slightly different tack, Steglich (2000) informally assessed student attitudes in nonmajors biology courses, and noted that writing produced positive changes in student attitudes toward biology. However, the author acknowledged that this work was not a research study. Finally, Tessier (2006) showed that students enrolled in a nonmajors ecology course significantly improved writing technical skills and committed fewer errors of fact regarding environmental issues in response to a writing treatment. Attitudes toward environmental issues also improved ( Tessier, 2006 ). Although this study surveyed students at the beginning and the end of the academic term and also tracked student progress during the quarter, instrument validity and reliability were not provided. The generalizability of results was further limited because of an overreliance on student self-reports and small sample size.
Each of the studies described above peripherally supports a relationship between writing and critical thinking. Although not explicitly an investigation of critical thinking, results from a relatively recent study support a stronger connection between writing and reasoning ability ( Daempfle, 2002 ). Ebert-May et al. (1997) used a modified learning cycle instructional method and small group collaboration to increase reasoning ability in general education biology students. A quasi-experimental pretest/posttest control group design was used on a comparatively large sample of students, and considerable thought was given to controlling extraneous variables across the treatment and comparison groups. A multifaceted assessment strategy based on writing, standardized tests, and student interviews was used to quantitatively and qualitatively evaluate student content knowledge and thinking skill. Results indicated that students in the treatment group significantly outperformed control group students on reasoning and process skills as indicated by the National Association of Biology Teachers (NABT) content exam. Coincidentally, student content knowledge did not differ significantly between the treatment and control sections, indicating that development of thinking skill did not occur at the expense of content knowledge ( Ebert-May et al., 1997 ). Interview data indicated that students experiencing the writing and collaboration-based instruction changed how they perceived the construction of biological knowledge and how they applied their reasoning skills. Although the Ebert-May study is one of the more complete investigations of writing and critical thinking to date, several questions remain. Supporting validity and reliability data for the NABT test was not included in the study, making interpretation of results somewhat less certain. In addition, the NABT exam is designed to assess high school biology performance, not college performance ( Daempfle, 2002 ). Perhaps more importantly, the NABT exam does not explicitly measure critical thinking skills.
Collectively, it appears that additional research is necessary to establish a more defined relationship between writing and critical thinking in science ( Rivard, 1994 ; Tsui, 1998 , 2002 ; Daempfle, 2002 ). The current study addresses some of the gaps in previous work by evaluating the effects of writing on critical thinking performance using relatively large numbers of students, suitable comparison groups, valid and reliable instruments, a sizable cadre of covariables, and statistical analyses of covariance. This study uses an experimental design similar to that of the Ebert-May et al. (1997) study but incorporates valid and reliable test measures of critical thinking that can be used both within and across different science disciplines.
Currently there is much national discussion about increasing the numbers of students majoring in various science fields ( National Research Council, 2003 ; National Academy of Sciences, 2005 ). Although this is a necessary and worthwhile goal, attention should also be focused on improving student performance in general education science because these students will far outnumber science majors for the foreseeable future. If college instructors want general education students to think critically about science, they will need to use teaching methods that improve student critical thinking performance. In many traditional general education biology courses, students are not expected to work collaboratively, to think about concepts as much as memorize facts, or to develop and support a written thesis or argument. This presents a large problem when one considers the societal role that general education students will play as voters, community members, and global citizens. By improving their critical thinking skills in science, general education students will be better able to deal with the broad scientific, economic, social, and political issues they will face in the future.
The problem addressed by this study was to discover whether writing could improve student critical thinking performance in general education biology courses. How might writing in general education biology affect the analysis, inference, and evaluation skills that are inherent to critical thinking? What level of critical thinking skill do students bring to nonmajors biology courses? Can their critical thinking skills be measurably improved using writing? What other factors affect development of critical thinking skills? When do student critical thinking skills begin to change, and how much? In this study, the effect of writing on critical thinking performance was investigated using the California Critical Thinking Skills Test (CCTST) at the beginning (pretest) and end (posttest) of 10 sections of general education biology at a regional comprehensive university in the Pacific Northwest. Several research questions framed this investigation:
Does writing in laboratory affect critical thinking performance in general education biology? Does the development of analysis, inference, and evaluation skills differ between students who experience writing versus those who experience traditional laboratory instruction? What measurable effect do factors like gender, ethnicity, and prior thinking skill have on changes in critical thinking in general education biology? If critical thinking skills change during an academic quarter, when does that take place?
Study context.
The study took place at a state-funded regional comprehensive university in the Pacific Northwest. All participants were nonmajor undergraduates who were taking biology to satisfy their general education science requirement. Ten total sections of general education biology offered over three academic quarters (one academic year) were included in the study. Four of the 10 sections implemented a writing component during weekly laboratory meetings (N = 158); six traditional quiz-based laboratory sections served as a nonwriting control group (N = 152). Only scores from students who had completed both the initial (pretest) and end-of-quarter (posttest) critical thinking assessments were included in the data analysis. A breakdown of participant demographics for the writing and nonwriting groups is provided in Table 1 .
Demographics for the writing and nonwriting groups
Sample | Class distribution (%) | Gender distribution (%) | |||||
---|---|---|---|---|---|---|---|
Fr | So | Jr | Sr | 2nd Sr | M | F | |
Writing (158) | 44.9 | 33.5 | 15.2 | 3.8 | 2.5 | 38.6 | 61.4 |
No writing (152) | 53.3 | 28.3 | 7.2 | 9.2 | 2.0 | 38.2 | 61.8 |
Overall (310) | 49.0 | 31.0 | 11.3 | 6.5 | 2.3 | 38.4 | 61.6 |
Sample | Ethnic distribution (%) | ||||||
Caucasian | Hispanic | African American | Native American | Asian | Other | ||
Writing (158) | 84.8 | 1.9 | 2.5 | 0 | 4.4 | 6.3 | |
No writing (152) | 81.6 | 4.6 | 1.3 | 1.3 | 5.9 | 5.3 | |
Overall (310) | 83.2 | 3.2 | 1.9 | 0.6 | 5.2 | 5.8 |
Demographics profile for the study sample. n values in parentheses.
a Other includes the ″choose not to answer″ response.
Each course section included a lecture component offered four times per week for 50 min and a laboratory component that met once a week for 2 h. Course lecture sections were limited to a maximum enrollment of 48 students, with two concurrent lab sections of 24 students. Two different instructors taught five writing sections and five other instructors taught 11 traditional sections over three consecutive quarters. Each course instructor materially participated in teaching laboratory with the help of one graduate assistant per lab section (two graduate students per course section). None of the instructors from treatment sections had implemented writing in the laboratory before the start of this study. Writing instructors were chosen on the basis of personal dissatisfaction with traditional laboratory teaching methods and willingness to try something new.
Strong efforts were made to establish equivalency between writing and nonwriting course sections a priori. Course elements that were highly similar included common lecture rooms, the use of similar (in most cases identical) textbooks, and a lab facility coordinated by a single faculty member. More specifically, three similarly appointed lecture rooms outfitted with contemporary instructional technology including dry erase boards, media cabinets, a networked computer, and digital projection were used to teach the nonmajors biology courses. The same nonmajors biology textbook was used across the writing and most of the nonwriting sections. All laboratory sections used a common lab facility and were taught on the same day of the week. Although the order in which specific labs were taught differed among sections, a common laboratory manual containing prescriptive exercises covering the main themes of biology (scientific method, cellular biology and genetics, natural selection and evolution, kingdoms of life, and a mammalian dissection) was used across all writing and nonwriting lab sections.
Primary course differences included a writing component in the laboratory, and how much time was devoted to laboratory activities. Those sections that experienced the writing treatment completed the prescriptive lab exercises in the first hour and engaged in writing during the second hour of the lab. Nonwriting sections allocated 2 h for the prescriptive lab exercises and included a traditional laboratory quiz rather than a writing assignment. The degree to which the writing and nonwriting sections included small group collaboration in laboratory varied and all course sections differed with regards to individual instructor teaching style. Although all course sections used traditional lecture exams during the quarter to assess content knowledge, the degree to which rote memorization-based exam questions were used to evaluate student learning varied.
On the first day of lecture, students in the writing treatment group were told that their laboratory performance would be evaluated using collaborative essays instead of traditional quizzes. A brief overview of the writing assignments was included in associated course syllabi. During the first laboratory session of the quarter, students were grouped into teams of three or four individuals, and the criteria for completing weekly writing assignments were further explained.
The decision to use collaborative groups to support writing in the laboratory was partly based on existing literature ( Collier, 1980 ; Bruffee, 1984 ; Tobin et al., 1994 ; Jones and Carter, 1998 ; Springer et al., 1999 ) and prior research by Quitadamo, Brahler, and Crouch (unpublished results), who showed that Peer Led Team Learning (one form of collaborative learning) helped to measurably improve undergraduate critical thinking skills. Small group learning was also used in the nonwriting treatment groups to a greater or lesser extent depending on individual instructor preference.
Baseline critical thinking performance was established in the academic quarters preceding the writing experiment to more specifically attribute changes in critical thinking to the writing treatment. Concurrent nonwriting course sections were also used as comparison groups. The historical baseline provided a way to determine what student performance had been before experiencing the writing treatment, whereas the concurrent nonwriting groups allowed for a direct comparison of critical thinking performance during the writing treatment. Pretest scores indicating prior critical thinking skill were also used to further establish comparability between the writing and nonwriting groups.
Laboratory activities were coordinated for all sections by a single faculty member who taught in the nonwriting group. All faculty and graduate assistants met regularly to discuss course progress, laboratory procedure, and coordinate resources. Nonwriting faculty drafted quizzes that addressed laboratory content knowledge. Writing faculty collaboratively crafted a consensus essay, or thought question, designed to elicit student critical thinking and ability to apply content knowledge. Each thought question was designed so that students had to apply lecture concepts and build on their conceptual understanding by integrating actual laboratory experiences (see Supplemental Appendix 1 , available online) for thought question examples). Weekly thought questions became progressively more difficult as the term progressed. Initial planning meetings took place just before the beginning of the academic quarter and included graduate assistant training to help them learn to consistently evaluate student writing using a modified thesis-based essay rubric (see Supplemental Appendix 2 ; Beers et al., 1994 ). A range of sample essays from poor to high quality was used to calibrate graduate assistant scoring and ensure consistency between assistants from different laboratory sections within the writing group. All graduate assistants and course instructors applied the thesis-based rubric to sample essays and worked toward consensus. Initial training ended when all graduate assistants scored within 0.5 points of each other on at least two sample essays.
Students were given weekly thought questions before beginning laboratory to help them frame their efforts during laboratory exercises. Students completed the prescriptive lab activities during the first hour, and then each student group relocated to an assigned computer lab in the same building and worked around a common computer terminal to draft a collective response to the weekly thought question. Students were allowed to use any suitable information or materials (laboratory observations, laboratory manuals, lecture notes, textbooks, the Internet, etc.) to help them address their thought question. Internal group discussions allowed students to argue individual viewpoints as they worked toward group agreement on each thought question. Essay responses to thought questions were answered using a standard five-paragraph format. Each essay included an introduction with a group-generated thesis statement, two to three body paragraphs that provided sufficient detail to support the thesis statement, and a summary paragraph that concluded the essay. Students were not allowed to work on essays outside of the laboratory environment.
Initial essay drafts were composed in Microsoft Word and submitted to the graduate assistant by the end of the laboratory period using the campus e-mail system. Graduate assistants evaluated each group's essay (typically six per lab section) and assigned an initial grade based on the thesis-based essay rubric. Graduate assistants made comments and suggestions electronically using Microsoft Word revising and track changes tools. Evaluated essays were e-mailed back to each student group, which addressed comments and suggestions during the subsequent week's laboratory writing time. Each student group submitted a final draft that was re-evaluated and assigned a final grade. During the second week, students both revised their essay from the previous week and then generated an initial draft for the current week's thought question, all within the lab writing hour. This was done to help students become more proficient writers within a short period of time. Overall, students in the writing group completed eight essays that, along with lab book scores, constituted 25% of their overall course grade. An identical percentage was used to calculate traditional quiz and lab book scores in all nonwriting course sections.
At the end of the quarter, each writing group member completed a peer evaluation for all group members, including themselves (see Supplemental Appendix 3 ). This was done to help students reflect on and evaluate their own performance, maximize individual accountability within the group, and make sure students received credit proportional to their contributions. The average peer evaluation score for each student was included as 5% of the final course grade.
Collectively, this approach to writing and evaluation was used to 1) help students reflect on and discuss deficiencies in their collective and written work, 2) provide an opportunity for students to explicitly address deficiencies in thesis development and general writing skill, 3) provide a suitable reward for student efforts to revise their work relative to established performance benchmarks, 4) improve individual accountability within each group, and 5) help students develop more efficient and effective writing skills that collectively might lead to improved critical thinking skill.
Using critical thinking to indicate student learning performance is particularly useful because it can be measured within and across disciplines. Various instruments are available to assess critical thinking ( Watson and Glaser, 1980 ; Ennis and Weir, 1985 ; Facione, 1990b ; Center for Critical Thinking and Moral Critique, 1996 ); however, only the CCTST measures cognitive and meta-cognitive skills associated with critical thinking, is based on a consensus definition of critical thinking, and has been evaluated for validity and reliability for measuring critical thinking at the college level ( Facione, 1990a ; Facione et al., 1992 , 2004 ). The CCTST measures cognitive skills of analysis, inference, evaluation, induction, and deduction, with results expressed as raw scores or national percentile equivalents based on a national norming sample of students from 4-yr colleges and universities. Construct validity for the CCTST is high as indicated by greater than 95% consensus of the Delphi panel experts on the component skills of critical thinking. Test reliability (calculated using the KR–20 internal consistency method) is 0.78–0.84 for the form used in this study, a value considered to be within the recommended range for tests that measure a wide range of critical thinking skills ( Facione, 1991 ). The CCTST norming sample for 4-yr colleges and universities is based on a stratified sample of 2000 students from various disciplines, with approximately 30% of the norming sample comprised of science and math students. Approximately 20,000 college students complete the CCTST each year ( Insight Assessment and Blohm, 2005 ).
The CCTST contains 34 questions and is a 45-min timed assessment of critical thinking. An online version of the CCTST was administered in this study, which allowed the researchers to collect student demographics data including gender, ethnicity, age, and several others at the same time critical thinking skill was measured. Total critical thinking skill as well as analysis, inference, and evaluation component critical thinking skills ( Facione, 1990c ) were determined for each CCTST administration and compared across the writing and nonwriting groups.
A quasi-experimental pretest/posttest control group design was used for this study to determine whether critical thinking performance in the writing group differed significantly from the nonwriting group. This design was chosen in order to compare critical thinking performance between intact groups, and because it was not feasible to randomly assign students from one course section to another within the sample. Frequency distributions of pretest/posttest changes in total critical thinking skill and analysis, inference, and evaluation component critical thinking skills were constructed to provide some indication of sample randomness and to inform assumptions for subsequent statistical analyses of covariance (see Figure 1 , A–D).
(A–D) Frequency distribution of change in critical thinking skills. Distribution of change in critical thinking skill for the experimental sample. Changes are indicated using raw scores from CCTST pre- and posttests for total critical thinking skill (A) as well as analysis (B), inference (C), and evaluation (D) component critical thinking skills.
The pretest/posttest control group design was also used in order to minimize internal validity threats that could potentially compete with the effects of the writing treatment on student critical thinking performance. This design is widely used in educational research, and generally controls for most threats to internal validity ( Campbell and Stanley, 1963 ). Internal threats that remain a concern include history, maturation, pretest sensitization, selection, and statistical regression toward the mean. In the current study, history and maturation threats were minimized to the extent that the CCTST pretest and posttest were administered only 9 wk apart, and class standing and age covariables that indicate maturation were included in the statistical analysis. Pretest sensitization and selection are larger concerns for this design. Pretest sensitization was minimized in several ways: 1) prior critical thinking skill indicated by the CCTST pretest was used as a covariable in statistical analyses, 2) pretest/posttest to posttest only comparison studies conducted by Insight Assessment indicate CCTST pretest sensitization is minimized ( Facione, 1990a ), and 3) neither the students, instructors, nor the test administrators have access to the correct answers on the CCTST, so repeat performance on the posttest is less likely. Selection threats were also reduced by using CCTST pretest scores in the statistical analyses, thereby making it more difficult to detect statistically significant differences in critical thinking performance between the writing and nonwriting groups. Statistical regression toward the mean, which was observed to some extent in this study, was minimized because this study used a valid and reliable instrument to assess critical thinking ( Facione, 1990a ). Regression threats were also minimized to the extent that students with higher initial scores regressed much less than students with lower initial scores.
The generalizability of study results is limited because all data were collected at a single university. Specific threats to external validity include selection-treatment interaction and treatment diffusion. These threats were minimized because writing was mandatory for all treatment group participants, thereby minimizing volunteer effects. Because the writing also took considerable student effort, it is less likely that treatment diffusion occurred. In summary, the pretest/posttest control group design was used to minimize internal and external validity threats and maximize the ability to determine the effects of writing on student critical thinking performance.
Effect of writing on critical thinking performance..
General education biology students were divided into writing and nonwriting groups (independent variable). Changes in CCTST pretest/posttest scores (dependent variable) were determined to discover whether writing influenced student critical thinking performance. Two CCTST outcome measures were used to statistically test for writing effect: 1) raw scores for total critical thinking skill, and 2) raw scores for analysis, inference, and evaluation component skills. Results were reported using raw scores and corresponding national percentile rank so that critical thinking performance outcomes would be more meaningful and intuitive. Conversion of CCTST raw scores to national percentile ranking was done using SPSS (SPSS, Inc., Chicago, IL) statistical software and a linear estimation conversion script based on an equivalency scale from Insight Assessment (Millbrae, CA).
Several covariables were included in the analysis to increase statistical accuracy and precision, and to more specifically isolate the effects of writing on critical thinking performance. CCTST pretest scores were used to indicate initial critical thinking skill. Gender and ethnicity helped to account for male/female or race-specific changes in critical thinking performance and were also used to identify potential sources of performance bias. Academic term and time of day were used to account for critical thinking differences due to the time of year each course was offered and the time of day each student took the course, respectively. Class standing and age were used to indicate maturation related to time in college and chronological age, respectively. Finally, the instructor covariable was used to account for performance differences due to individual teaching styles.
Several statistical analyses were conducted to determine the effects of writing on critical thinking performance in general education biology. An analysis of covariance (ANCOVA) test provided insight regarding differences in overall critical thinking performance between the writing and nonwriting groups. Change in CCTST total raw scores and national percentile ranking was used as composite measures of critical thinking ( Facione, 1990c ) in this initial analysis. Second, changes in particular component critical thinking skills (analysis, inference, and evaluation) were evaluated using a multivariate analysis of covariance (MANCOVA) test because of the three dependent variables. The ANCOVA and MANCOVA tests also provided some insight into the effect the covariables had on critical thinking performance in general education biology. Collectively, these statistical tests allowed for a more accurate and precise analysis because variance associated with the covariables could be more specifically isolated from the writing treatment. Mean, SE, and effect size were also compared between the writing and nonwriting groups. Effect size, represented in standard units, was used to compare the magnitude of writing effect in the study.
Performance on weekly thought questions was analyzed to discover specifically when and how much student critical thinking skills changed during the academic term. This analysis also provided context for CCTST critical thinking performance measures. Specifically, average scores from a representative sample of writing course sections (approximately 100 students) were used to compare initial essay drafts across the weeks of the term to discover when students began to show changes in their first attempt at each essay. Weekly performance on final revised essays was also compared to determine how student final submissions changed over time. Finally, the weekly difference between each initial essay and each final essay was compared to determine how much the revision process changed during the term. These calculations collectively helped to provide a profile of critical thinking performance over time.
Student demographics provided in Table 1 indicated an overall distribution of approximately 49% freshmen, 31% sophomores, 11% juniors, and 9% seniors. Approximately 74% of the writing group students were freshmen and sophomores, whereas 82% of the nonwriting group was underclassmen. Overall, 61% of the sample was female and 39% male, with near identical gender distribution across the writing and nonwriting groups. The predominant ethnicity in the sample was Caucasian (>83%), with Asian American (5%), Latino/Hispanic (3%), African American (2%), and Native American (1%) students comprising the remainder of the sample. About 6% of the sample classified themselves as having some other ethnicity or chose not to identify their ethnic heritage.
Analysis of covariance and multivariate analysis of covariance tests were used to compare critical thinking performance between the writing and nonwriting groups. The evaluated assumptions for the ANCOVA and MANCOVA tests were homogeneity of slopes, homogeneity of covariances, and normality. An analysis evaluating the homogeneity of slopes assumption indicated that the relationship between the covariables and the critical thinking performance dependent variable did not differ significantly by the writing/nonwriting independent variable for the ANCOVA test, F(2, 307) = 1.642, p = 0.195, power = 0.346, partial η 2 = 0.011, or the MANCOVA test, F(6, 610) = 1.685, p = 0.122, power = 0.645, partial η 2 = 0.016. These results confirmed that both analyses of covariance met the homogeneity of slopes assumption. The homogeneity of covariance assumption was tested using Levene's and Box's tests. Levene's test results for the ANCOVA indicated that error variances were not equal across writing and nonwriting groups, F(1,308) = 7.139, p = 0.008. Similarly, Box's test results indicated that covariance was not equal for the writing and nonwriting groups, F(6, 684,530) = 4.628, p = 0.000. These results indicated that the ANCOVA/MANCOVA tests did not meet the homogeneity of covariance assumption. To more fully evaluate this assumption, distributions of total and component critical thinking skill were constructed (see Figure 1 , A–D). Furthermore, the writing and nonwriting groups were highly similar in size and no post hoc tests were conducted. On the basis of these data, it was determined that the ANCOVA and MANCOVA tests were the best statistical measures to answer the research questions. Finally, the normality assumption was evaluated using the previously constructed frequency distributions for total change in critical thinking ( Figure 1 A) as well as change in analysis ( Figure 1 B), inference ( Figure 1 C), and evaluation ( Figure 1 D) critical thinking skills. Frequency distributions of total and component critical thinking dependent variables indicated that each approximated a standard normal curve.
The ANCOVA test of total critical thinking performance showed that writing and nonwriting groups differed significantly, F(1, 300) = 19.357, p < 0.0001, power = 0.992, partial η 2 = 0.061 (see Table 2 ). The strength of the relationship between the writing/nonwriting groups and critical thinking performance was modest but significant, accounting for more than 6% of the variance in critical thinking performance.
ANCOVA results for total critical thinking performance
Treatment | F | df | Power | Effect size | |
---|---|---|---|---|---|
Writing | 19.357 | 300 | 0.000 | 0.992 | 0.061 |
CCTST pretest | 19.713 | 300 | 0.000 | 0.993 | 0.062 |
Instructor | 7.745 | 300 | 0.006 | 0.792 | 0.025 |
Time of day | 6.291 | 300 | 0.013 | 0.705 | 0.021 |
Gender | 0.226 | 300 | 0.635 | 0.076 | 0.001 |
Ethnicity | 2.326 | 300 | 0.128 | 0.330 | 0.008 |
Age | 0.453 | 300 | 0.502 | 0.103 | 0.002 |
Class standing | 0.002 | 300 | 0.962 | 0.050 | 0.000 |
Academic term | 2.387 | 300 | 0.123 | 0.338 | 0.008 |
Analysis of covariance for the writing and nonwriting groups. Tested covariables included gender, ethnicity, class standing, age, prior critical thinking skill (CCTST pre-test), academic term, time of day, and instructor.
a Significance tested at 0.05 level.
Descriptive statistics of total critical thinking performance in the writing and nonwriting groups were also calculated (see Table 3 ). The writing group showed an average CCTST raw score change of 1.18 compared with the nonwriting group, which showed an average raw score change of −0.51. These critical thinking raw scores equated to gains in national percentile rank of 7.47 (45th to 53rd percentile) for the writing group and −2.09 (42nd to 40th percentile) for the nonwriting group. Critical thinking improvement in the writing group was approximately nine times greater than the nonwriting group (see Figure 2 ).
Writing effect on total critical thinking performance: CCTST raw scores
Treatment | Mean raw score | SEM | Raw CT change | ||
---|---|---|---|---|---|
Pre | Post | Pre | Post | ||
Writing (158) | 15.84 | 17.02 | 0.32 | 0.36 | 1.18 |
Nonwriting (152) | 15.46 | 14.95 | 0.34 | 0.43 | −0.51 |
Overall (310) | 15.65 | 16.00 | 0.33 | 0.40 | 0.34 |
Comparison of writing and nonwriting group performance based on CCTST raw scores. CCTST raw score range was 0–34; n values in parentheses.
Effect of writing on total critical thinking national percentile rank. Comparison of total critical thinking national percentile gains between writing and nonwriting groups. Percentile ranking was computed using CCTST raw scores, an equivalency scale from Insight Assessment, and a linear conversion script in SPSS.
The ANCOVA test of total critical thinking skill indicated that gender, ethnicity, age, class standing, and academic term did not significantly affect critical thinking performance (see Table 2 ). Covariables that significantly affected total critical thinking performance included 1) CCTST pretest score, F(1, 300) = 19.713, p < 0.0001, power = 0.993, partial η 2 = 0.062, 2) instructor, F(1, 300) = 7.745, p < 0.006, power = 0.792, partial η 2 = 0.025, and 3) time of day, F(1300) = 6.291, p < 0.013, power = 0.705, partial η 2 = 0.021. The effect of prior critical thinking skill (CCTST pretest) was moderately strong, accounting for more than 6% of the variance in total critical thinking performance. The effect of instructor and time of day were smaller, accounting for 2.5 and 2%, respectively, of total critical thinking performance variance. Critical thinking improvement associated with CCTST pretest score was approximately 2.5 times greater than for instructor and nearly three times greater than for time of day.
The MANCOVA test indicated that analysis, inference, and evaluation critical thinking skills differed significantly between the writing and nonwriting groups, Wilks λ = 0.919, F(3, 296) = 8.746, p < 0.0001, power = 0.995, partial η 2 = 0.081 (see Table 4 ). The strength of the relationship between writing and component critical thinking performance was modest but significant, accounting for more than 8% of the variance in critical thinking performance.
MANCOVA results for component critical thinking performance
Treatment | Wilks λ | F | df | Power | Effect size | |
---|---|---|---|---|---|---|
Writing | 0.919 | 9.746 | 296 | 0.000 | 0.995 | 0.081 |
Analysis pretest | 0.623 | 59.737 | 296 | 0.000 | 1.000 | 0.377 |
Inference pretest | 0.681 | 46.222 | 296 | 0.000 | 1.000 | 0.319 |
Evaluation pretest | 0.613 | 62.398 | 296 | 0.000 | 1.000 | 0.387 |
Gender | 0.984 | 1.602 | 296 | 0.189 | 0.420 | 0.016 |
Ethnicity | 0.983 | 1.756 | 296 | 0.156 | 0.456 | 0.017 |
Age | 0.988 | 1.153 | 296 | 0.328 | 0.456 | 0.012 |
Class standing | 0.978 | 2.186 | 296 | 0.090 | 0.553 | 0.022 |
Instructor | 0.956 | 4.508 | 296 | 0.004 | 0.880 | 0.044 |
Quarter | 0.991 | 0.899 | 296 | 0.442 | 0.246 | 0.009 |
Time of day | 0.980 | 2.022 | 296 | 0.111 | 0.517 | 0.020 |
Multivariate analysis of covariance for the writing and nonwriting groups. Tested covariables included gender, ethnicity, class standing, age, prior critical thinking skill (CCTST pretest), academic term, time of day, and instructor.
Specifically, significant gains in analysis and inference skills were observed in the writing group but not the nonwriting group. No statistically significant gains in evaluation skill were observed in either group (see Table 5 ). National percentile rank equivalents for CCTST component raw scores indicated the writing group gained 10.51 percentile in analysis skill (42nd to 52nd percentile), 6.05 percentile in inference skill (45th to 52nd percentile), and 5.16 percentile in evaluation skill (46th to 52nd percentile). The nonwriting group showed a national percentile rank change of −4.43 percentile in analysis skill (47th to 42nd percentile), −2.23 percentile in inference skill (42nd to 40th percentile), and 1.37 percentile in evaluation (44th to 45th percentile; see Figure 3 ). Critical thinking performance for the writing group was 15 times greater for analysis and 8 times greater for inference skills than for the nonwriting group. Although neither the writing nor the nonwriting group showed significant gains in evaluation skill, the writing group showed more than 3 times greater improvement than did the nonwriting group.
Effect of writing on component critical thinking performance
Component skill | Mean raw score and change | |||
---|---|---|---|---|
Writing (n = 158) | Nonwriting (n = 152) | |||
Raw score | SEM | Raw score | SEM | |
Analysis (pre) | 4.22 | 0.11 | 4.35 | 0.11 |
Analysis (post) | 4.54 | 0.10 | 3.99 | 0.13 |
Analysis (change) | 0.33 | 0.11 | −0.36 | 0.14 |
Inference (pre) | 7.42 | 0.18 | 7.07 | 0.20 |
Inference (post) | 7.91 | 0.20 | 6.83 | 0.23 |
Inference (change) | 0.48 | 0.16 | −0.24 | 0.21 |
Evaluation (pre) | 4.20 | 0.14 | 4.04 | 0.15 |
Evaluation (post) | 4.57 | 0.15 | 4.13 | 0.17 |
Evaluation (change) | 0.37 | 0.15 | 0.09 | 0.17 |
Comparison of writing and nonwriting group performance based on critical thinking component skill raw scores (CCTST subscales). Score range was 0–7 (analysis), 0–16 (inference), and 0–11 (evaluation).
Effect of writing on component critical thinking national percentile rank. Comparison of component critical thinking national percentile gains between writing and nonwriting groups. Percentile ranking was computed using CCTST raw scores, an equivalency scale from Insight Assessment, and a linear conversion script in SPSS.
The MANCOVA test of analysis, inference, and evaluation skills indicated that gender, ethnicity, age, class standing, academic term, and time of day did not significantly affect critical thinking performance. Critical thinking performance was affected by prior analysis, inference, and evaluation skill (CCTST component pretest scores) and instructor (see Table 4 ). Specifically, component pretest scores had a large effect on critical thinking, accounting for 38% (analysis), 32% (inference), and 39% (evaluation) of critical thinking performance variance. The effect of instructor was smaller, accounting for 4.4% of variation in critical thinking skill. The effect of prior component critical thinking skill was approximately 4.5 times greater than the effect of writing, and nearly 9 times greater than the effect of instructor.
Critical thinking performance on student essays was evaluated by applying a thesis-based essay rubric (see Supplemental Appendix 2 ) on initial submissions and final revised essays. Average weekly performance during the academic term is shown in Figure 4 . A comparison of initial essays indicated that students improved 53.3% from week 1 (average score of 27.9%) to week 7 (average score of 81.2%). A similar comparison of final essays showed that students improved 32.5% from week 1 (average score of 54.1%) to week 7 (average score of 86.6%). The largest changes between initial and final essays occurred in week 1 (change of 26.2%), and decreased each week thereafter (24.8, 23.9, 18.8, 8, 7.8, and 5.4% for weeks 2 through 7, respectively). These results showed that students produced little evidence of critical thinking skill in their writing early in the term, but improved dramatically on both initial and revised essay submissions by the end of the term.
Profile of change in critical thinking performance in writing group. Comparison of student writing performance on weekly initial and revised essays. Essay scores were derived using a thesis-based critical thinking rubric (see Supplemental Appendix 2 ). Average essay scores were computed across writing sections.
The purpose of this study was to discover whether writing could measurably influence critical thinking performance in general education biology. Results indicated that students from the writing group significantly outperformed their nonwriting peers in both total critical thinking skill and the component critical thinking skills of analysis and inference. The writing and nonwriting groups were highly similar initially and began the academic term with comparable critical thinking ability (45th and 42nd national percentile for writing and nonwriting, respectively). By the end of the term, writing students had improved their critical thinking skill to above the 52nd percentile whereas nonwriting students decreased to below the 40th percentile. In addition to writing, prior critical thinking skill and course instructor significantly affected critical thinking performance, with prior critical thinking skill having the largest effect on critical thinking gains of any variable tested. Further analysis of the writing group showed that the largest gains in critical thinking occurred during the first few weeks of the term, with graduated improvement during the remainder of the term. A comparison of average critical thinking performance on initial essays and revised essays showed that thinking skills improvement was greater on initial essays (53%) than on final essays (33%). Collectively, the results of this study indicated that students who experienced writing in general education biology significantly improved their critical thinking skills.
The covariance analysis that was conducted provided a partial means to separate out the effects of writing, prior critical thinking skill, instructor, and multiple covariables from total and component critical thinking gains. The analysis of total critical thinking skill indicated that writing students changed their critical thinking skill from below the national average to above the national average within an academic quarter, whereas nonwriting students remained below the national average. This observation is important because it shows that students can develop critical thinking skills within a fairly short 9-wk period of time, and that writing can play a role in that process. A similar study showed critical thinking skills improve over 15 wk (Quitadamo, Brahler, and Crouch, unpublished results); however, this study provided no insight into whether critical thinking skills could be changed over a shorter period of time, in a different academic setting, or in response to instructional variables such as writing.
Although critical thinking gains were influenced by writing, they did not appear to be affected by gender, ethnicity, class standing, or age. In fact, statistical results indicated that these variables collectively had a very small effect on critical thinking performance. Gender distribution was nearly identical across the writing and nonwriting groups, and was predominantly female (nearly 62%). Ethnic distribution was also highly similar across the writing and nonwriting groups, but the sampling was largely Caucasian (>84%). Class standing varied a little more across the writing and nonwriting groups, with the sample largely comprised of underclassmen (70%). Although nearly three-quarters of the sample was between 18 and 21 years of age, nearly 10% was over 21, with a fair number of older nontraditional students represented. It is possible that a more diverse sample would have produced different results, or it may be that the individuals participating in this study responded particularly well to writing. Although further investigation of these variables is necessary and important, it was beyond the scope of the current study.
The analysis of component skills provided greater insight into the particular critical thinking skills that students changed in response to writing. Specifically, writing students significantly improved their analysis and inference skills whereas nonwriting students did not. Writing students also improved their evaluation skills much more than nonwriting students, although not significantly. These results indicate that the process of writing helps students develop improved analytical and inference skills. Prior research indicates that the writing to learn strategy is effective because students must conceptually organize and structure their thoughts as well as their awareness of thinking processes ( Langer and Applebee, 1987 ; Ackerman, 1993 ; Holliday, 1994 ; Rivard, 1994 ). More specifically, as students begin to shape their thoughts at the point of construction and continually analyze, review, and clarify meaning through the processes of drafting and revision, they necessarily engage and apply analysis and inference skills ( Klein, 1999 ; Hand and Prain, 2002 ). In this study, the process of writing appears to have influenced critical thinking gains. It also seems likely that writing students experienced a greater cognitive demand than nonwriting students simply because the writing act required them to hypothesize, debate, and persuade ( Rivard, 1994 ; Hand and Prain, 2002 ) rather than memorize as was the case in nonwriting control courses.
Conversely, the lack of any significant change in analysis, inference, or evaluation skills in the nonwriting group indicated that the traditional lab instruction used in the general education biology control courses did not help students develop critical thinking skills. Based on the results of this study, it could be argued that traditional lab instruction actually prevents the development of critical thinking skills, which presents a rather large problem when one considers how frequently these traditional methods are used in general education biology courses. One also has to consider that the critical thinking gains seen in the writing group might also have resulted from the relative absence of traditional lab instruction rather than writing alone. Additional research will be necessary to gain further insight into this question. Either way, changes to the traditional model of lab instruction will be necessary if the goal is to enhance the critical thinking abilities of general education biology students.
The variable that had the largest impact on critical thinking performance gains was prior critical thinking skill. This phenomenon was previously observed by Quitadamo, Brahler, and Crouch (unpublished results) in a related study that investigated the effect of Peer Led Team Learning on critical thinking performance. That study focused on science and math major undergraduate critical thinking performance at a major research university, and found that, in addition to Peer Led Team Learning, prior critical thinking skill significantly influenced critical thinking performance (Quitadamo, Brahler, and Crouch, unpublished results). Specifically, students with the highest prior critical thinking skill showed the largest performance gains, whereas students with low initial skill were at a comparative disadvantage. The fact that prior critical thinking skill also had a large effect on critical thinking performance in this study increases the generalizability of the observation and underscores its importance. Simply put, 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, not because they lack the cognitive hard-wiring to perform but because they lack the tools to build their knowledge. Is it reasonable or just to expect otherwise comparable students to perform at similar levels when only some of them have the keys for success? If we hope to improve the perception of science in this country, we need to educate people on how to think about important scientific issues, and not simply argue a position based on one school of thought. By helping general education students to develop critical thinking skills, it is hoped that they will be better able to think rationally about science.
The observation that students who come to general education biology with greater critical thinking skills leave with the largest skill gains has important implications for the K–12 school system as well. If a high proportion of students are coming to institutions of higher education lacking critical thinking skills, why are these skills not being explicitly taught in the K–12 system? Ideally, students would learn the foundational tenets of critical thinking at an earlier age, and be able to refine and hone these skills as they progress through the K–20 education system. The results of this study reinforce the idea that students should be explicitly taught critical thinking skills and be expected to practice them as early and often as possible.
Although its effect was smaller than writing or prior critical thinking skill, the instructor variable also played a significant role in student critical thinking performance, accounting for 2.5% of the total variance in critical thinking gains. Determining the particular qualities of each instructor that contributed to student critical thinking success and further separating instructor and writing effects will require additional research. Previous research indicates that teaching style positively influences certain aspects of student learning ( Grasha, 1994 ; Hativa et al., 2001 ; Bain, 2004 ), but the qualities that specifically influence student critical thinking gains have not been sufficiently investigated. Additional research in this area is necessary.
Faculty considering whether to use writing in the laboratory may wonder about how much time and energy it takes to implement, if efforts to change will translate into improved student learning, and how these changes affect disciplinary content. From a practical perspective, implementing writing did not take more time and effort per se; rather, it required faculty to reconceptualize how they spent their instructional time. Instead of individually developing course materials, writing faculty collaborated to a greater extent than nonwriting faculty on course design and assessments that required students to demonstrate their critical thinking skill. Interviews of faculty from the writing and nonwriting groups indicated that writing faculty felt the course was less work because they collaborated with colleagues and because students demonstrated improved thinking skill. Writing faculty generally became more comfortable with the new model after ∼2–3 wk when students began to show observable changes in writing proficiency and critical thinking. Together, collaboration with colleagues and observed gains in critical thinking tended to create a positive feedback loop that helped to sustain writing faculty efforts. In contrast, nonwriting faculty similarly wanted their students to think better but were convinced that traditional methods would be more effective, and so remained closed to change. There were some logistical challenges with writing, like scheduling computer labs where students could draft and revise their weekly essay responses under instructor and teaching assistant supervision. Teaching assistants (and faculty) also needed to be trained on how to evaluate writing using a rubric. Finally, with regards to content coverage, no lecture or laboratory content was killed in order to implement writing because writing and nonwriting students both performed the same lab activities. Collectively, the benefits of using writing in laboratory should encourage faculty who want their students to learn to think critically to give it a try.
This study showed that writing affects student critical thinking skill in a nonmajors biology course, but the results have generated more questions than have been answered. How does writing specifically produce gains in critical thinking performance? What factors influence student prior critical thinking skill? How do instructors specifically influence student gains in critical thinking? Future studies that analyze student essays in more detail would provide greater insight into how writing influences critical thinking skill. Using writing in other nonmajor science courses such as chemistry, geology, or physics could also be done to determine the transferability of this method. Additional studies that investigate student prior critical thinking skill and instructor variables are also necessary. These future studies would further contribute to the knowledge base in this area, and also address some of its identified limitations ( Ebert-May et al., 1997 ; Daempfle, 2002 ). Results from these studies would also increase the generalizability of the results from this study.
Building on existing research and on the basis of several lines of evidence presented in this study, we conclude that writing positively influences critical thinking performance for general education biology students. Those students with prior critical thinking skill may have a comparative advantage over other general education biology students who have not developed these same skills. To rectify that inequity critical thinking skills should be explicitly taught early and used often during the K–20 academic process. As it appears that particular instructors improve student critical thinking skills more than others, students should be discerning in their choice of instructors if they want to improve their critical thinking skills. Whether writing as a method to improve critical thinking skills will prove useful in other general education science courses will likely depend on a host of factors, but it has potential. Further study of writing in general education science will be necessary to verify these results and discover the breadth and depth of how writing affects critical thinking skill.
We thank Drs. Holly Pinkart, Roberta Soltz, Phil Mattocks, and James Johnson and undergraduate researchers Matthew Brewer, Dayrk Flaugh, Adam Wallace, Colette Watson, Kelly Vincent, and Christine Weller for their valuable contributions to this study. The authors also acknowledge the generous financial support provided by the Central Washington University Office of the Provost and the Office of the Associate Vice President for Undergraduate Studies.
Why memory is the missing piece in teaching critical thinking..
Updated July 17, 2024 | Reviewed by Monica Vilhauer
I have a couple of questions for my regular (or semi-regular) readers, touching on a topic I’ve discussed many times on this blog. When it comes to power, persuasion , and influence, why is critical thinking so crucial? Alternatively, what are some common traps and pitfalls for those who prioritize critical thinking? It's not necessary that you go in to great detail—just any vague or general information that comes to mind will do.
Great! Regardless of whether you recalled anything specific, the key is you made the effort to remember something. Like many questions I pose here, the real purpose is to illustrate a point. If you aim to be influential and persuasive—i.e., successful—in both work and life, you must be proficient in critical thinking. To achieve this proficiency, you need to cultivate and exercise your memory , a skill that is increasingly at risk in a technology-saturated age.
Learning and remembering something are often discussed as if they are two separate processes, but they are inextricably linked . Consider this: Everything you know now is something you once had to learn, from basic facts to complex knowledge and skills. Retaining this information as actual knowledge, rather than fleeting stimuli, depends entirely on memory. Without memory, there is no knowledge. Consequently, there can be no critical thinking, as it relies on prior knowledge, which in turn relies on memory.
Students sometimes tell me that they want to learn how to be good critical thinkers but complain about having to “memorize stuff.” On these occasions I will often say, in a playfully teasing manner, “What I hear you saying is that you're bothered by having to remember stuff.” This usually helps them see how silly and unreasonable it is to complain about memorizing information, as there isn’t a single course in existence that doesn’t require remembering something . The ability to remember is at the core of critical thinking, and I often use the simple visual demonstration that follows to illustrate this point.
Benjamin Bloom, an educational psychologist, developed a model known as the “Taxonomy of Learning.” Originally intended for educational psychology, this model also highlights why memory is the foundation of critical thinking—or any kind of thinking at all.
Humans are creatures of interpretation, constantly processing the information we perceive. This ability has made us the scientists, inventors, and artists that we are today. To interpret information, however, we must first remember it—not all information, obviously, as that’s impossible. Thanks to technology (which we’ll get to momentarily) we have vast amounts of information potentially at our fingertips. But how do you know what information to look up in a given situation? To know where to start and avoid endlessly searching irrelevant data, you need to remember enough of the right kind of information.
Think of a crime movie where an investigator, while reviewing evidence, suddenly has an epiphany and rushes off to confirm their hunch. These scenes illustrate that while the investigator needs more information, they remember enough to know what to search for.
Here’s a visual demonstration I use in class to help my students understand. Imagine you have pieces of information represented as five dots:
Now let’s say that any coherent shape or picture you can draw using these dots is an interpretation of the information. When examined together, what might these five dots mean? Here’s one way to connect the dots.
What does this shape represent? Many people will quickly say it’s a house, a common and reasonable interpretation. But not everyone sees it as a house. Some might say it’s the home plate used in baseball. Even when people connect the dots (i.e., interpret a cluster of information) the same way using the same lines, they don’t necessarily interpret the picture the same way. The situation becomes more complex when people connect the dots differently, creating a completely different shape or picture.
Now, having connected the dots differently, instead of a house, we have a star. Or at least some would consider it a star; others might say it’s an occult or magic symbol—these are all very different interpretations. This shows that with the same pieces of information, people can “connect the dots” differently, and even when they connect them the same way, they see different things.
Now what happens when additional information is added or an alleged “missing dot” is perceived by others?
With just one additional dot, what could have previously been interpreted as a 5-pointed star can now be reasonably interpreted as the Star of David.
Finally, sometimes the additional information can lead to a completely different shape or image, resulting in a “eureka” moment of insight. What previously appeared as different types of stars now looks like a circle.
I use this classroom demonstration to illustrate how people can interpret the same objective information in highly subjective ways, creating different narratives for themselves and others. This is a crucial point to remember when aiming to influence or persuade others—i.e., the need to see things from their perspective. Additionally, this activity powerfully underscores the importance of “collecting dots”—that is, the importance of remembering crucial bits of information. Without enough such dots, you lack the basic information needed to form meaningful ideas. Without meaningful ideas, you can’t think critically, influence, or persuade. It’s as straightforward as that.
Why is it so crucial to recognize that memory is foundational to critical thinking, power, influence, and persuasion? Partly because this fact isn’t widely acknowledged—and it needs to be. Additionally, we live in an era where memory is under unprecedented assault. While technology allows us to achieve remarkable feats unimaginable to previous generations, it comes at a cost. One such cost is “digital-induced amnesia,” where our memory capabilities atrophy due to information overload and technology taking over many of the cognitive tasks we used to perform ourselves.
Memory doesn’t exist in isolation. It’s closely tied to traits like the ability to focus and pay attention . If you’re not paying attention, you can’t absorb the information that you want or need to remember. Unfortunately, technology also impacts our ability to focus , and this doesn’t even touch on the dramatic ways AI ’s explosive development might undermine our thinking skills .
This article won’t delve into specifics on improving focus and memory in an age of tech ubiquity. Fortunately, resources from Psychology Today can help with that. My goal here is to convince you why memory is so vital for anyone who wishes to be a critical thinker and a persuasive, influential person. Now you know. Whether you’ll remember or not...only time will tell.
Craig Barkacs, MBA, JD, is a professor of business law at the University of San Diego School of Business and a trial lawyer with three decades of experience as an attorney in high-profile cases.
Sticking up for yourself is no easy task. But there are concrete skills you can use to hone your assertiveness and advocate for yourself.
Analysis of the contribution of critical thinking and psychological well-being to academic performance.
This study examines the influence of critical thinking and psychological well-being on the academic performance of first-year college students. It emphasizes the importance of a model of psychological well-being focused on self-acceptance, environmental mastery and purpose in life, along with a critical thinking approach oriented to problem solving and decision making. A total of 128 first-year psychology students from a Spanish public university participated, assessed by means of Ryff’s psychological well-being scale (PWBS) and the PENCRISAL critical thinking test, complemented with grades obtained in a critical thinking course. The results show positive correlations between psychological well-being, critical thinking and academic performance, with a stronger relationship between critical thinking and academic performance. However, psychological well-being also plays a significant role in academic performance. The findings highlight the need for holistic pedagogical approaches that combine cognitive skills and personal development to enhance first-year students’ learning.
In the context of the increasing demands of contemporary societies, in this study we address how critical thinking (CT) and psychological well-being (PWB) influence academic performance within the university setting. Upon entering university, first-year students are faced with the challenge of adapting to new academic dynamics and demands, which they must balance with the pursuit of personal satisfaction ( Acee et al., 2012 ; Casanova et al., 2018 ). The adaptation process, which involves the achievement of academic goals and the projection of long-term life objectives, is fundamental to academic performance, considered a key indicator of successful adaptation and a reflection of the competencies required in the professional environment ( Alonso-Borrego and Romero-Medina, 2016 ; Frick and Maihaus, 2016 ).
The goal of this research is to show the link between CT, which is characterized by analyzing and evaluating information, making evidence-based inferences, and reflecting on one’s own thought process for decision making and problem solving ( Bailin et al., 1999 ; Ennis, 2015 ; Jahn and Kenner, 2018 ; Saiz, 2020 ; Halpern and Dunn, 2023 ), and the PWB, which focuses on personal development ( Ryff, 1989 , 2013 ; Ryff and Keyes, 1995 ); and analyze how both contribute to academic performance. Despite the complexity of the factors that can influence academic performance, in this study we want to combine cognitive and socio-affective variables to better understand these dynamics. Based on The Ryff Psychological Well-Being Scale (PWBS), we examine how well-being, especially through self-acceptance, environmental mastery, and purpose in life impacts academic performance. As a starting point we recognize that CT may have an even greater effect on academic performance. This holistic approach seeks to contribute to the debate on the competencies needed for the 21st century through the relevance of CT and PWB in university education and their role in the formation of individuals capable of coping with contemporary demands.
In the university context, academic performance is influenced by a series of factors ranging from pedagogical practices and student satisfaction with them to more personal and intrinsic elements. These include the student’s motivation and emotional state, academic background, IQ, personality traits and level of psychological maturity. This multi-layered approach focuses the complexity underlying academic performance and emphasizes the interaction between the educational environment and the individual qualities of each student.
A study by Oliván Blázquez et al. (2019) highlights the flipped classroom (FC) method in comparison to traditional lecture-based learning (LB) and shows that FC not only improves students’ grades, but also maintains their satisfaction with learning without increasing their perceived workload. Although FC was initially perceived as more difficult, this did not have a negative impact on satisfaction or long-term learning, underscoring the importance of student perceptions and involvement in the learning process. These results support the introduction of FC in higher education and point to the need for continuous adjustments based on student feedback to maximize academic performance and develop critical and practical skills.
Beyond educational practices, Gilar-Corbi et al. (2020) investigated how motivational and emotional factors and prior academic performance influence college students’ success. The study used the Motivated Strategies Learning Questionnaire (MSLQ) and the Trait Meta-Mood Scale (TMMS) to measure motivational learning strategies and emotional intelligence. The findings show that scores obtained in the diagnostic tests have a strong influence on academic performance, while emotional attention has a minor influence. The study points out that prior performance, together with self-efficacy and appropriate emotional regulation, plays a crucial role in predicting academic success. Thus, the authors suggest that interventions focused on improving self-efficacy and emotional intelligence may be key to optimizing students’ academic outcomes.
In the same context, this time with more variables, Morales-Vives et al. (2020) investigate the influence of intelligence, psychological maturity and personality traits on the academic performance of adolescents, and find that these factors combined explain about 30% of their variability. Intelligence, especially in reasoning and numerical aptitude, emerges as the most significant predictor, while psychological maturity, reflected in work orientation, and traits such as conscientiousness and openness to experience, have an indirect influence. These findings show that, although intelligence plays a decisive role, maturity and personality are in a lesser proportion.
These conclusions and the recommendations derived from them resemble recent advances in academic research. One example is the work of Mammadov (2022) , which draws attention to cognitive ability as the main predictor of academic performance, but also points to the relevance of conscientiousness, a personality trait associated with self-discipline and organization, which explains a significant part of the variability in academic performance. Mammadov also suggests that the influence of personality on performance varies by educational level, showing the dynamics between a student’s personality and his or her educational context. These findings demonstrate the need for educational strategies that promote both cognitive development and the reinforcement of positive personality traits.
Recent research on academic performance shows two consensuses. First, there is a growing understanding of the influence of the interaction between intrinsic and extrinsic factors, including pedagogical methods and motivational, emotional and cognitive elements, in improving the performance and satisfaction of students in higher education. The studies reviewed highlight the relevance of cognitive ability and personality traits such as consciousness, and promote a holistic educational approach that integrates the development of cognitive and personality dimensions. Second, academic achievement is recognized as a multidimensional construct, objectively assessed through quantitative indicators such as grade point average (GPA) and standardized assessment scores. These reflect the attainment of educational objectives and the accumulation of knowledge and skills over time.
Halpern (1998 ) argues that intrinsic effort and a willingness to analyze and solve complex problems are key competencies for learning and adapting to a constantly changing environment. According to Halpern (1998) CT transcends the mere acquisition of analytical skills and requires the development of an active predisposition to question assumptions, consider diverse perspectives, and persist in cognitive effort. This disposition is by no means innate, but can be cultivated through a pedagogy that explicitly integrates the teaching of critical skills such as logical analysis, argument evaluation, and information synthesis, and that emphasizes problem structuring to facilitate skill transfer and metacognitive self-regulation. Halpern proposes an educational framework that promotes the acquisition of these skills and encourages reflection on the thinking process so that students are able to apply CT effectively in diverse contexts and continuously improve. This methodical and structured approach characterizes CT as a set of advanced cognitive skills and an exercise of conscious judgment that is essential for informed, evidence-based decision making, which integrates non-cognitive elements ( Halpern and Dunn, 2023 ).
Throughout the development of the discourse on CT, various theories and their empirical foundations have evolved into meaningful educational practices, recognized in diverse academic settings. Meta-analyses, particularly those by Abrami et al. (2008 , 2015) have contributed significantly to the understanding of effective teaching of CT and have emphasized the need for specific and tailored teaching strategies that incorporate clear CT objectives into educational programs. These studies demonstrate that CT, defined as a process of intentional, self-regulated judgment that includes interpretation, analysis, evaluation, and inference, is increasingly recognized as essential in the knowledge era. Abrami et al. (2008) note that critical skills and dispositions are developed through explicit pedagogical interventions, as opposed to spontaneous acquisition, which challenges traditional pedagogical paradigms and fosters a shift towards intentional educational practices, placing students at the center of learning.
In addition, a more detailed analysis by Abrami et al. (2015) identifies that strategies that encourage interactive dialogue, confrontation with real problems, and individual tutorials are particularly effective. This suggests that active and meaningful learning outperforms traditional methods in the development of critical skills. This approach not only enhances students’ analytical and synthesis skills, but also facilitates the transfer of knowledge to new contexts, a key skill for the 21st century. The research reinforces the view that CT is a cross-cutting competency, crucial for navigating the complexity of contemporary challenges, and argues for an education that integrates these skills into all areas of learning.
Despite in-depth analyses of the need for CT, the growing discrepancy between rapid progress, the availability of information and the ability to critically analyze it poses a major challenge. Dwyer et al. (2014) point out that the exponential increase in global information has outpaced the ability of traditional education systems to teach effective CT skills, creating a gap that may inadequately prepare students for the challenges of today’s world. The authors argue that the ability to critically evaluate, synthesize, and apply knowledge is crucial for academic success and survival in the 21st century. This approach highlights how CT, by fostering analytical and reflective skills, transcends academia to positively impact individual and collective well-being, and argues for educational strategies that bridge the gap between information acquisition and critical analytical skills.
Recent research on this topic points to the indisputable relevance of CT as an essential component of academic performance and points to its role as a key predictor of success in educational processes. Rivas et al. (2023) show that CT transcends conventional cognitive skills. This is because CT is characterized as a rigorous practice that fosters in-depth analysis, critical evaluation and synthesis of information oriented to decision making and problem solving, fundamental skills to understand and apply knowledge in complex contexts. Research shows that CT skills not only maintain a positive correlation with academic performance, but can be significantly improved through targeted educational programs. For this reason, the authors advocate their integration into curricula and educational assessment systems to prepare students for the challenges of the 21st century, especially when phenomena such as artificial intelligence acquire greater prominence in social and professional dynamics ( Saiz and Rivas, 2023 ).
The literature on CT identifies two fundamental consensuses: first, it defines it as an intentional and deep process, oriented to problem solving and decision making, based on meticulous analysis that goes beyond logical reasoning to include a critical evaluation of the basis for judgments. In addition, it involves detailed scrutiny and integration of new information in changing contexts, as well as metacognition, i.e., conscious self-regulation of thinking that facilitates adaptation and continuous improvement of cognitive strategies in accordance with the major demands and obstacles of our first half century ( Dwyer, 2023 ). In its practical application, CT enables daily challenges to be met through informed judgments and a willingness to question and adjust perspectives in response to new information. Characterized by curiosity and adaptability, CT is essential for making responsible decisions and achieving successful outcomes, underscoring its practical value in both personal and professional settings.
Second, CT, beyond its theoretical value, can be conceived as a key theory of action for academic performance and PWB ( Saiz, 2020 ; Saiz and Rivas, 2023 ), by enhancing in individuals the ability to face and solve problems in an effective and grounded manner. CT involves crucial skills such as analysis, evaluation and synthesis, indispensable for acquiring and retaining knowledge, and also for applying it in new contexts, which improves academic performance and has, in principle, positive effects on quality of life. Thus, CT emerges as an academic competence and an essential tool for everyday life ( Dumitru and Halpern, 2023 ; Guamanga et al., 2023 ). Therefore, to synthesize theoretical paths with a practical function, we understand that “to think critically is to arrive at the best explanation of a fact, phenomenon or problem in order to know how to solve it effectively” ( Saiz, 2024 , p. 19).
The task of relating concepts that are difficult to operationalize, such as well-being, is a major challenge; but it is necessary to approach it, more within a framework of CT understood as a means to achieve broad objectives than as an end in itself. Thinking critically transcends the mere application of skills or the accumulation of goal-oriented knowledge. In fact, it requires a detailed examination of the effect that such management has on the environment and how the satisfaction derived from reaching certain achievements is related to subjective aspects.
CT by its very deliberative and goal-oriented nature goes beyond the search for how to reach effective solutions and addresses a wider range of human and social consequences resulting from these actions ( Facione, 1990 ; Elder, 1997 ; Jahn, 2019 ). The idea is to involve non-cognitive aspects that occupy a central place in academia, and that are crucial in the interaction between specific knowledge and skills, elements widely explored in the discourse of CT. In this sense, PWB has been selected as the focus of study, recognizing it as a desirable attribute in educational processes. The challenges this poses are not lost sight of, especially when it comes to quantifying transient, subjective and normatively mediated judgments about what states or conditions are considered good, healthy or desirable in the complexity of human experience, as detailed by Flanagan et al. (2023) .
Ryff (1989 , 2013) , Ryff and Keyes (1995) contribution to the conceptual understanding and dissemination of PWB is notorious and highly valued in different fields of knowledge ( Van Dierendonck and Lam, 2023 ). The imprint of his research has been marked by criticism of a reductionist conception of PWB that simplifies well-being to the presence of positive affective states ( Ryff, 1989 ). Consequently, Ryff defends a much more complex multidimensional concept that seeks to attune the attainment of goals with the development of potentialities. Ryff’s thesis is that PWB is a multidimensional construct that transcends happiness or mere life satisfaction ( Ryff and Keyes, 1995 ).
Carol Ryff’s theory of PWB, based on humanistic, clinical and developmental psychology, as well as Aristotelian eudaimonia, focuses on self-actualization, the search for meaning and purpose in life as the core of well-being. As detailed in the text Happiness is everything, or is it? Explorations on the meaning of psychological well-being ( Ryff, 1989 ) the model consists of six dimensions that converge in personal development: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance.
The first dimension, self-acceptance, implies a positive attitude towards oneself and an acceptance of all aspects of one’s identity, including both positive and negative qualities. As for positive relationships with others, Ryff states that these are interpersonal relationships characterized by warmth, trust and genuine concern for the well-being of others; this dimension is dominated by the value of empathy in human well-being. Autonomy is defined by an individual’s capacity to maintain independence and resist social pressures in order to regulate their behavior according to internal personal norms. This dimension emphasizes self-determination as a compass for the pursuit of well-being. On the other hand, environmental mastery emphasizes the ability to effectively manage and control the external environment, which implies a feeling of competence and control over personal and professional life. Finally, purpose in life and personal growth refer to the possession of goals, direction and a sense of development and fulfillment of one’s potential. These dimensions reflect the search for meaning and continuous personal evolution as fundamental components of PWB.
Ryff’s PWBS has established itself as a key instrument in positive psychology. Research after 1989 ( Ryff and Keyes, 1995 ; Ryff, 2013 ) has explored the variability of these dimensions with age and across genders. These studies showed the influence of sociodemographic factors on well-being, so the model has been extended to consider the development of PWB across the lifespan and determined by more contextual factors such as health. The approach enriches the understanding of PWB and denotes the practical relevance of the construct in fields such as mental health and social policy. Ryff’s work has inspired other researchers to discuss and extend its principles ( Van Dierendonck and Lam, 2023 ). For example, Huppert (2009) complements Ryff’s dimensions by emphasizing the management of negative emotions and resilience as key components of sustainable well-being; Huppert aligns this view with the World Health Organization (WHO) definition of health and adds a dynamic dimension on overcoming adversity. This theoretical and practical deepening demonstrates the robustness and adaptability of Ryff’s model. The synthesis of these contributions confirms the value and applicability of Ryff’s PWBS; they reveal how the eudaemonic model not only reinforces an academic discourse, but also guides practices that promote well-being in different contexts and consolidates itself as a vital field in human development.
However, due to the same complexity and extension of the PWB construct, Ryff’s PWBS has different observations that question its theoretical and statistical foundations. On the first aspect, the work of Disabato et al. (2016) , by examining the distinction between hedonic and eudaimonic well-being, problematizes the theoretical basis of this dichotomy. Through an analysis incorporating data from 7,617 individuals from 109 countries, the authors find that there is no clear distinction between hedonic well-being experiences, focused on pleasure, and eudaimonic ones, related to personal fulfillment. The results indicate a high correlation between the two types of well-being ( r = 0.96). This suggests that people do not significantly differentiate between pleasure seeking and self-fulfillment in their perception of well-being. This implies that the hedonic-eudaimonic dichotomy may not hold empirically and, therefore, a unified model of well-being that reflects the current behavioral dynamics should be sought.
From a statistical perspective, Ryff and Keyes (1995) analyses show that the PWBS, composed of 18 items, meets psychometric criteria and shows strong internal and moderate correlations among different scales. Correlations between dimensions range from low to modest (0.13 to 0.46), suggesting that each dimension addresses unique aspects of well-being. From the theoretical model, this diversity underscores that, although interrelated, the dimensions represent unique aspects of psychological well-being. In terms of specific results, studies indicate that with age the dimensions of environmental mastery and autonomy increase, while purpose in life and personal growth tend to decrease, with no significant changes in self-acceptance and positive relationships with others. Women outperform men on positive relationships with others and personal growth, suggesting that changes in these dimensions reflect evolving priorities and perceptions of personal development across the life span ( Ryff and Keyes, 1995 ).
On the number of dimensions of PWBS, Blasco-Belled and Alsinet (2022) note that the six-dimensional theoretical model has generated debate even among experts in the field. Some suggest that a four-dimensional model-environmental mastery, personal growth, purpose in life, and self-acceptance-might represent a second-order PWB factor, indicating a possible conceptual overlap between Ryff’s original dimensions; others exclude positive relationships with others and autonomy from the model. The study of Ryff’s PWBS by network analysis conducted by Blasco-Belled and Alsinet (2022) shows four different dimensions, in one of these, the most important node of the network, self-acceptance, purpose in life and environmental mastery are grouped, with special emphasis on self-acceptance because of its centrality in the network at the item level.
In the Spanish-speaking context, Nogueira et al. (2023) identified three main factors: autonomy, positive relationships with others, and competence. This suggests that PWBS may vary according to cultural and contextual factors. Furthermore, although it is not a study analyzing the dimensions of Ryff’s PWBS, the study by Páez-Gallego et al. (2020) applied the PWBS to Spanish adolescent students and found a strong positive correlation with the use of adaptive decision-making strategies. Specifically, the findings show that the adaptive approach is significantly associated with improvements in self-acceptance, environmental mastery, and purpose in life. In contrast, maladaptive strategies characterized by impulsivity and avoidance are associated with lower PWB. From this we infer that fostering effective decision-making skills is important for well-being and, in particular, we identify from empirical studies the dimensions of PWBS that correlate with post decisional skills.
Taken together, these findings suggest that Ryff’s PWBS, although pioneering and widely used, could benefit from revision to more accurately reflect the structure of PWB and its application in diverse cultural and educational contexts. The convergence of evidence from factorial and network analysis perspectives points to the need for a more integrated and adaptive model capable of capturing the complexity and dynamics of the underlying constructs. This underscores the continuing interest in PWB in research and practice. It is also an indication of the ongoing scholarly debate about its conceptualization and measurement. The recurrence of dimensions such as self-acceptance, environmental mastery, and purpose in life across analyses suggests a common core of PWB. This raises the question of whether these dimensions can be conceptually aligned with academic achievement and CT. In addition, questioning the boundaries between hedonic and eudaimonic raises the issue of whether a broader construct is needed to analyze well-being in educational settings. In this context, we start from the premise that self-acceptance, environmental mastery, and purpose in life are sufficient to explore college students’ PWB. These dimensions reflect students’ ability to recognize their strengths and weaknesses, set goals, and navigate effectively in their educational environment, aspects that could be considered part of the dispositional component necessary for the development of higher-level competencies such as those of the CT.
The research brings to empirical analysis the complex interplay between CT, PWB, and academic performance in the university context. We seek to answer how CT skills and PWB influence college students’ academic performance; and, how CT practices can be aligned with PWB to improve academic performance. We propose that the study variables converge in both a theoretical and an empirical model. The argumentative strategy consists of analyzing the direct impact of CT on academic performance, assessing whether PWB correlates with better academic outcomes, examining in detail the predictive factor of the relationship between CT and PWB on academic performance, and finally, according to the data obtained, proposing some dialogic bridges between cognitive and non-cognitive aspects of CT.
2.1 participants.
The study involved 128 first-year psychology students from a Spanish public university. The vast majority were women (83.1%), with only 16.9% men, which is usual in social sciences and humanities degrees. Age ranged from 18 to 33 years, with a mean of 19.28 (SD = 1.73). The sample was essentially composed of students who had completed secondary education (75.3% of the students were 19 years old). Between the ages of the students according to sex — females ( M = 19.09, SD = 0.814) and males ( M = 20.20, SD = 3.78) — there were no statistical differences, but the age of the males was not only higher, but also more dispersed.
The instruments applied were Ryff’s PWBS in its Spanish adaptation ( Díaz et al., 2006 ) and the PENCRISAL critical thinking test ( Saiz and Rivas, 2008 ; Rivas and Saiz, 2012 ). For academic performance, the academic records of the students participating in the critical thinking course in the first year of the psychology graduation were collected. The grades have an ascending interval from 1 to 10.
Ryff’s PWBS as mentioned in the previous discussion has different models. This instrument aims to measure psychological well-being, focusing on students’ own evaluations of their situations and perceived success in various aspects of life and personal development. It explores well-being through six main dimensions, self-acceptance (α: 0.83), positive relationships with others (α: 0.81), environmental mastery (α: 0.71), autonomy (α: 0.73), purpose in life (α: 0.83) and personal growth (α: 0.68). The questionnaire consists of 39 items, presented in a Likert scale format ranging from 1 (strongly disagree) to 6 (strongly agree) ( Díaz et al., 2006 ).
Consistent with the complexity of the scale and some data in common with other studies, we have chosen to consider only self-acceptance, environmental mastery and purpose in life. In support of this methodological decision, we have performed with our sample an exploratory factor analysis (principal components method) to see if these three dimensions converge in the same factor. The data confirm this convergence and show that this single factor has an eigenvalue of 2.43 and explains a very high value of the variance of its results (81.1%).
In the case of the PENCRISAL, the full version was applied, and the score was taken for each of the five dimensions and the total score. The PENCRISAL was applied to measure CT skills. This test consists of 35 problem situations that participants answer in an open-response format. The test is organized into five key areas: deductive reasoning, inductive reasoning, practical reasoning, decision making and problem solving.
The deductive and inductive component tests different forms of reasoning, such as propositional, categorical, causal, analogical and hypothetical. Decision-making measures the ability to make probabilistic judgments and to effectively use heuristics to identify potential biases. The problem-solving section poses participants with general and specific problems that require appropriate solution strategies. These sections are intended to encourage the application of strategies necessary for effective problem planning. The open-ended question format encourages participants to justify their answers, which are evaluated using a scoring system that rates the quality of their responses on a scale of 0 to 2. Responses are converted into numerical scores using item-specific criteria. These are used to describe and identify the thinking mechanisms underlying each response. A score of 0 indicates that the answer is incorrect, 1 indicates that the answer is correct but no or inadequate justification is provided, and 2 indicates that the answer is correct and adequate justification is provided. The PENCRISAL yields an overall score of the CT ranging between 0 and 70 and between 0 and 14 for each dimension. Reliability assessments show satisfactory accuracy, with a minimum Cronbach’s Alpha of 0.632 and a test–retest reliability of 0.786 ( Rivas and Saiz, 2012 ). The test is administered online through the SelectSurvey.NET V5 platform.
Students gave their free and informed consent to participate in the study. The PWBS was carried out at the beginning of the semester of the CT course. The PENCRISAL test was taken at the beginning and at the end of the academic period. Only the results of students who completed both instruments are considered. Academic performance is represented by the grade obtained by students at the end of the course. Statistical analyses were performed with IBM/SPSS version 29.0. After performing the descriptive statistics, we proceeded to a correlation analysis and, finally, we evaluated the impact of the PWBS and the CT on the variance of academic performance by performing a regression analysis.
Table 1 presents the descriptive data of the students’ scores on the two instruments applied, and the measure of academic performance. In addition to the minimum and maximum values, the mean, standard deviation and indicators of skewness and kurtosis of the distribution of the results are presented.
Table 1 . Descriptive statistics for the measures used ( n = 128).
Observing the results, we can see a distribution with a slight tendency towards values above the mean (m = 79.80) for the PWBS, which is reflected in a negative skewness (−0.437). With respect to the five dimensions of CT, it can be stated globally that the mean value of DR, IR and PS is moving away from the maximum value observed and towards the minimum value, which represents a positive symmetry. The opposite situation occurs with the RP dimension. Regarding the TCT, the data show a tendency to scores around the mean (m = 37.21), as can be deduced from the residual values of skewness and kurtosis. Regarding the AP, the data suggest a balanced distribution of academic scores around an intermediate value between 3.66 and 9.01 as scores at the lower and upper extremes (m = 6.10), with very low skewness and kurtosis.
In general, the results show good variability or dispersion, since the mean of each variable is located in the center of the data interval, which is desirable in research to adequately represent the population studied. Skewness and kurtosis indices close to zero for academic achievement are especially indicative of a normal or Gaussian distribution of values. The slightly higher kurtosis in the IR dimension of CT (2.248) is still acceptable.
Table 2 shows the correlations between the variables in this study. Since these were interval metric variables, Pearson’s product x moment method was used to calculate the correlations. For statistical significance, the two-tailed test was used and p < 0.05 was set as the limit of significance.
Table 2 . Correlations between study variables.
According to the data, the highest correlation is found between TCT and AP, with the lowest correlation being between CT and PWBS measurement (no correlation). At an intermediate level is the correlation between PWBS and AP. Likewise, all the dimensions of the CT correlate with the AP with values between 0.183 (PS) and 0.337 (PR). As can be seen, there are variations in the correlations among the five dimensions of the CT, but all have high correlations with the total score (between 0.502 and 0.668). In this sense, only the TCT score is used for the regression statistical analysis.
In summary, the data suggest that there is a significant and positive relationship between PWBS and AP, as well as an even stronger and more significant relationship between TCT and AP. There is no evidence of a significant relationship between PWBS and TCT. To further explore the relationships between cognitive and noncognitive variables in AP, we turned to a regression analysis. We opted for a linear regression with PWBS and TCT as predictors and AP as the criterion or dependent variable. Table 3 presents the regression values obtained.
Table 3 . Impact of psychological well-being and critical thinking on academic performance.
The regression model was found to be statistically significant, with an F -value (2, 88) = 18.571, p < 0.001. This indicates that, collectively, PWBS and TCT provide significant prediction of AP. The coefficient of determination (R 2 adj.) is 0.285, which means that approximately 30% of the variability in AP can be explained by the independent variables in the model. As can be seen from the t -values and significance, both variables have a significant impact on AP, although TCT has a greater impact.
In a complementary manner, with the objective of enriching the analysis of the influence of the CT on the PA, we have included additional measures to the grade obtained by the students in the course (NCT), such as the selectivity grade with which they entered the university (NEBAU), the average grade of the transcript (NMEXP), that is, the grades of the other courses that the students must take, and the pretest results obtained with the PENCRISAL (PCT). The data obtained are recorded in Table 4 .
Table 4 . Correlations between study variables and complementary measures.
Table 4 shows that the relationship between PWBS and NMEXP has a Pearson correlation of 0.075, with a p -value of 0.372. This low correlation indicates that the connection is minimal. In contrast, the relationship between TCT and NMEXP shows a stronger correlation of 0.464**, suggesting a moderate positive association. The significance of this correlation, less than 0.001, indicates a statistically significant relationship, which implies that this result is not likely to be a coincidence. A similar case occurs with the relationship between NEBAU and NMEXP.
Given this context, if we perform a multiple linear regression analysis with NMEXP as the dependent variable and PWBS and TCT as independent variables, we would expect TCT to have a more significant impact on NMEXP. This projection is based on the statistically significant correlation of these variables. On the other hand, NEBAU has a slightly lower correlation with NMEXP compared to TCT (0.455 vs. 0.464), but the difference is very small, indicating that both have similar impact capacity for NMEXP in terms of linear correlation.
Confirmation of these hypotheses by appropriate regression analysis will provide a more detailed and accurate understanding of how PWBS and TCT individually contribute to the prediction of NMEXP, considering the influence of interrelated variables. However, in performing this procedure, a reduction in sample size to only 64 cases were observed. This increases the risk of failing to detect significant differences or could lead to unstable effect estimates.
The CT seeks to understand and effectively solve problems, through a correct approach, the generation of solution alternatives filtered by the mechanism of explanation and the selection of a solution, all with the aim of achieving a desired change. The PENCRISAL test is based on this defining framework of the CT ( Saiz and Rivas, 2008 ; Rivas and Saiz, 2012 ). Therefore, if we start from this concept and look at the data, we can conclude that the CT is a good predictor of academic performance.
Table 2 shows a positive and moderate correlation (0.514) between the CT and academic performance, suggesting that an increase in the CT is associated with an improvement in academic performance. Meanwhile, Table 3 shows — with a B coefficient of 0.074 and a Beta of 0.473 — that CT has a stronger relationship with academic performance compared to PWBS. This means that for every unit increase in CT, academic performance increases on average 0.074 units, and this effect is considerably significant in the model. The robust correlation and the impact indicated as a dependent variable highlight that the CT is a determinant competence of academic performance and is suggested as a relevant diagnostic and formative tool in the educational field. Although it is not the only factor that influences academic performance, the CT is presented as a significant predictor and one that can be worked on or trained in the classroom.
Declaratively, the current study coincides with other results obtained and recorded in Rivas et al. (2023) . On that occasion, the authors found that CT is a predictor of academic performance and that the benefits of instruction can be sustained over time. The study showed a correlation between CT and academic performance of 0.32. The main difference between these two studies concerns the objectives. The previous study did not attend to the explicit discussion of how CT could influence well-being, or vice versa. The current work recovers this line and incorporates non-cognitive variables in the analysis framework to account for well-being, under the assumption that this construct should have a significant impact on academic performance.
More generally, if we consider that, although the construct intelligence is not the same as CT, they do have several points of convergence ( Butler et al., 2017 ), then we can establish a dialogue with other studies on the factors that influence academic performance. Intelligence represents the intrinsic capacity to learn, understand, reason, and meet challenges through problem solving to adapt to the environment ( Sternberg, 1985 ). This cognitive potentiality manifests itself in various ways, being the CT one of its most relevant expressions, particularly in situations that demand deep analysis, evaluation, and decisions based on logical reasoning ( Saiz, 2024 ). The CT, therefore, acts as an essential tool that intelligence employs to effectively navigate through complex and challenging real-world situations ( Halpern and Butler, 2018 ).
In this conceptual line, the current results partially coincide with studies that have shown that the best predictors of academic performance are cognitive components, such as measures of general intelligence, analogical reasoning, fluid intelligence, logical, verbal and quantitative reasoning ( Morales-Vives et al., 2020 ; Mammadov, 2022 ); as well as scores on the diagnostic and university entrance test ( Gilar-Corbi et al., 2020 ).
In our study the other factor of analysis was the PWB. Although due to its non-cognitive nature it would be per se at a disadvantage compared to cognitive factors, the data also show that its inclusion in educational research, especially to account for academic performance, is significant. In Table 2 , the analysis of the correlation between PWBS and academic performance reveals a positive relationship with a correlation coefficient of 0.336. Although the correlation is moderate and not as strong as that observed between CT and academic performance, it is still significant and should not be ignored in the pursuit of improving students’ academic performance. Table 3 shows that PWBS has a positive and significant influence on the dependent variable. The standardized coefficient (Beta) of 0.271 indicates that there is a positive relationship between PWBS and academic achievement. The unstandardized coefficient (B) shows that, holding all other variables constant, for each unit increase in PWBS, academic performance increases on average 0.022 units. This relationship, supported by a low standard error of 0.007, points to a moderate but significant contribution of PWBS compared to other variables.
These findings show that the integration of some aspects of PWBS could be an effective strategy to improve academic performance, evidencing a beneficial and significant relationship between both aspects. PWB can influence academic performance through non-cognitive conditions or factors involved in learning, such as motivation, academic satisfaction, effective coping with stress or anxiety, and the acceptance and management of limitations related to the process of appropriation and adaptation to one’s own identity.
However, it is important to emphasize that the PWB is a construct that requires careful theoretical and empirical review in the educational context, as the Ryff scale has open debates and the lack of uniqueness of criteria on the number of dimensions influences these results. To cite just one case, we have used three dimensions out of six, with statistical and literature support, but the data may be different with a different selection approach. This finding highlights the importance of students’ PWB as part of a comprehensive educational strategy, but also shows that the direct impact of PWB on academic performance may be less pronounced than the impact of cognitive skills, and that due to its very multidimensional and complex nature, it is not easy to converge in an instructional design. Despite this, higher education institutions can take care of the institutional and relational climate so that students feel good and take advantage of the formative and educational opportunities of the academic environment. In the case of CT, there are concrete and validated training strategies that make it possible to improve skills such as argumentation, explanation, problem solving and decision making ( Guamanga et al., 2023 ; Saiz, 2024 ). On the PWB side, the same cannot be said due to the lack of empirical support; however, some studies have proposed a path that incorporates socio-emotional competences in the training of CT, a proposal characterized by the cognitive-emotional methodology, with interesting results that still need to be explored and debated ( Hanna, 2013 ).
Table 2 shows low and non-significant correlations between PWBS and the different forms of reasoning (deductive, inductive and practical), as well as with decision making and problem solving. For example, the correlation between PWBS and deductive reasoning is −0.082, which is not only low, but also lacks statistical significance. Additionally, the correlation between PWBS and decision making is −0.132, which is also a low correlation and not significant. Although there is a positive correlation between PWBS and problem solving (0.040), it is very low and not statistically significant, so there is not enough evidence to claim a positive relationship between these variables. This reinforces the idea that there is not a direct and significant relationship between how a student feels psychologically and CT skills or, nuanced is not supported by the data from this sample. It is possible that there are unexamined mediating factors that influence these relationships or that the relationship exists in a different context or with different measures.
The results of the present study do not coincide with other research that has shown positive relationships between decision-making and PWBS, especially with self-acceptance, environmental mastery, and purpose in life. The study by Páez-Gallego et al. (2020) addresses this issue by exploring how the PWBS of adolescents in Madrid, Spain, is linked to their decision-making methods. The research concludes that there is a positive correlation between the use of adaptive decision-making strategies and PWBS. Adolescents who opt for a rational and systematic evaluation of available options report higher levels of well-being. Specifically, adaptive decision-making style correlates significantly with overall well-being (0.544) and with aspects such as self-acceptance (0.485), positive relationships with others (0.242), environmental mastery (0.472), autonomy (0.359), purpose in life (0.473), and personal growth (0.346). In contrast, those who resort to maladaptive strategies, marked by impulsivity or avoidance, show reduced PWBS (−0.458).
The discrepancy in results with this study could be due to the difference between the instruments used to assess decision making. While Páez-Gallego et al. (2020) used the Flinders Adolescent Decision Making Questionnaire (FADMQ), which focuses on personal perceptions and experiences of decision making, our study uses the PENCRISAL, which although not limited to decision making, does include this ability as an essential component of the CT. The latter measures the ability to identify, analyze and solve everyday problems through items that simulate real situations, assessing the ability to choose the best solution or action strategy. Because the PENCRISAL responses are open-ended, it allows for a detailed assessment of how participants describe or explain their decisions. Ultimately, the fundamental difference between these two measures is that one is a self-report of perceptions and experiences, while the other is a set of problems to be solved correctly; in other words, one collects impressions of decision making and the other collects realized decision making. Therefore, although both studies applied Ryff’s PWBS, the differences between instruments and approach to decision making explain the variations in the results. This divergence evidences the relevance of considering the context and the specific instrument when interpreting the relationship between the PWBS and decision making.
Despite these findings, the need to further explore these interactions persists, especially given that the three selected dimensions-self-acceptance, environmental mastery, and life purpose-theoretically align with CT approaches focused on explanation and the development of post decisional skills, such as decision making and problem solving ( Guamanga et al., 2023 ). A CT approach that emphasizes the development of these skills must consider effects that transcend immediate or tangible outcomes. Therefore, it is crucial to understand how the concept of PWB, as examined above, relates to CT. Specifically, it must be determined whether some of these dimensions align directly to foster effective CT, or whether they instead lean more towards a conception of well-being in a more general sense, which could include hedonic aspects.
The emphasis on CT oriented to decision making and problem solving through the analysis of explanations and causalities should be evaluated for its pragmatic effects on PWB. At first glance this idea seems to confront parallel concepts paradoxically united by the same diachronic nature. In the case of the CT, this nature explains the high demands placed on it. For example, it is not enough to say that it contributes to tangible improvements in academic performance, but its usefulness is expected to transcend beyond academia and materialize in skills of interest to organizations in all sectors of the economy ( Casner-Lotto and Barrington, 2006 ; Atanasiu, 2021 ). However, their practical impact still presents serious challenges, especially when students, as active subjects of learning, face limitations in anticipating the usefulness and applicability of these critical skills for the future. This is partly explained by the fact that the educational system prioritizes academic performance over the comprehensive development required later in the professional sphere ( Saiz, 2020 ). Which means that the CT can be interpreted as an unfulfilled or partial promise. It is certainly a reading that omits the particular contexts, interests, motivations and concerns of students while they are part of these instructional programs and then the same factors analyzed by a student who knows that he or she must make the transition to the professional field.
A similar case happens with PWB as a diachronic phenomenon. An instant in time is not enough to understand and analyze students’ PWB. It is necessary to focus on how it changes and evolves through different stages, including through feelings of achievement or frustration in the academic process. Thus, it is recognized that PWB is not static and, therefore, evolves through lived experiences, among them, those comprising the applicability of a series of learned skills. This implies that as diachronic phenomena they can evolve and influence each other over time. This approach requires longitudinal studies to follow the evolution of the impact of curricular interventions aimed at strengthening cognitive skills such as those of the CT, in order to understand how these may influence the PWB in the long term.
The limitations of this study, beyond having a small sample that prevents the generalization of the results or having examined only certain dimensions of the PWBS, added to the theoretical impossibility of performing regression analyses with other performance measures, lie in the diachronic nature of the constructs studied. This characteristic makes it difficult, as has been argued, to give a definitive answer on the relationship.
Within the framework of the PWBS triad model we are analyzing, it is possible to theoretically group several key concepts. The development of the CT involves a process of self-acceptance, which is crucial given our inherent tendency for error. This process allows us, through a reflective evaluation of our past and present, to recognize and accept beliefs that we have discarded as erroneous. This self-acceptance facilitates deeper introspection, allowing us to see these errors as essential learning opportunities in our lives. On the other hand, any model that emphasizes post-decisional skills must also consider the non-linear complexity of our reality, and provide solid criteria for problem solving and decision making to master our environment more effectively. This is what allows us to adapt better, both biologically and socially. Finally, this approach to TC inevitably values purpose in life by seeking to ensure that it is in part determined by integrating the best tools of science, philosophy and education for a more effective life orientation, grounded in the principles of rationality. The importance of setting clear goals, recognizing that their achievement requires effort, discipline and determination, is essential to being an effective critical thinker.
Therefore, although each dimension proposed by Ryff’s PWBS possesses a conceptual richness that requires empirical validation, the dimensions selected for this study are aligned with a model of CT focused on problem solving and real-world decision making. Although we aspired to discover stronger links between PWB and CT, and to deepen their interrelationship, the theoretical parallelism analyzed is also reflected in the empirical results. Moreover, PWB as an operational concept, due to its complexity and multidimensionality, is subject to continuous revisions or possible unifications into a broader notion of well-being.
In future research on this topic, it is essential to include a broader set of variables predictive of academic performance. This includes, but is not limited to, students’ selectivity record and cumulative grades in other subjects. In addition, a more solid and theoretically robust concept of well-being must be adopted, one that fits contemporary educational and professional demands. This concept must transcend the simple distinction between eudaemonic and hedonic well-being, and address its diachronic nature. It is important to explore how these dimensions of well-being are interrelated, either as cause or effect; and to examine whether CT fosters a virtuous circle with well-being.
The original contributions presented in the study are included in the article/supplementary material; further inquiries can be directed to the corresponding author.
Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.
MG: Writing – original draft, Conceptualization, Investigation, Methodology, Writing – review & editing. CS: Investigation, Methodology, Project administration, Validation, Writing – original draft. SR: Data curation, Investigation, Supervision, Validation, Writing – review & editing. LA: Formal analysis, Methodology, Validation, Writing – review & editing.
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was funded by the Universidad de Salamanca, Spain.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Keywords: critical thinking, psychological well-being, academic performance, higher education, assessment
Citation: Guamanga MH, Saiz C, Rivas SF and Almeida LS (2024) Analysis of the contribution of critical thinking and psychological well-being to academic performance. Front. Educ . 9:1423441. doi: 10.3389/feduc.2024.1423441
Received: 25 April 2024; Accepted: 28 June 2024; Published: 16 July 2024.
Reviewed by:
Copyright © 2024 Guamanga, Saiz, Rivas and Almeida. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Carlos Saiz, [email protected]
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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Academic Program Learning Outcomes. The following examples of academic program student learning outcomes come from a variety of academic programs across campus, and are organized in four broad areas: 1) contextualization of knowledge; 2) praxis and technique; 3) critical thinking; and, 4) research and communication.
Student learning outcomes also: Should align with the institution's curriculum and co-curriculum outcomes (Maki, 2010) Should be collaboratively authored and collectively accepted (Maki, 2010) Should incorporate or adapt professional organizations outcome statements when they exist (Maki, 2010) Can be quantitatively and/or qualitatively ...
Learning outcomes benefit instructors. Learning outcomes can help instructors in a number of ways by: Providing a framework and rationale for making course design decisions about the sequence of topics and instruction, content selection, and so on. Communicating to students what they must do to make progress in learning in your course.
7. • In writing learning outcomes it is important to keep in mind that we assess what is taught . Find learning outcomes that are a source of objective data for assessment, indicating clearly what learners have to understand, know and/or be able to do . All learning outcomes have to be observable and measurable .
Strive to keep all your learning outcomes measurable, clear and concise. When you are ready to write, it can be helpful to list the level of Bloom's next to the verb you choose in parentheses. For example: Course level outcome 1. (apply) Demonstrate how transportation is a critical link in the supply chain. 1.1.
Written Communication Learning Outcomes ... students' writing skills and their critical thinking capabilities (e.g., National Center for Education Statistics, 1993, 1994, 1995), whereas other research points to the independence ... seniors' attainment of written communication and critical thinking outcomes. The data collected through these ...
Learning Outcomes at UF are organized into three broad categories: Content Knowledge, Critical Thinking, and Communication. In order to demonstrate SACS standard 3.3.1, student learning outcomes should be reviewed periodically and realigned with the evolving outcomes and expectations for students graduating from UF.
Learning Outcome 1. Upon completion of this unit, students will be able to critically assess the factors influencing physical activity and nutrition (environment, community, habits, underlying thinking, lifestyle and time allocation), and analyze how these factors shape their current choices.
The framework aligns intending to improve student learning outcomes by enhancing teachers' ability to design, ... AL is essential to unlocking writing success, and by taking appropriate interventions, students can improve their writing skills, develop critical thinking, and develop problem-solving abilities while also being motivated to achieve ...
The notion of critical thinking and its theoretical complexity are used as a case for an epistemological critique of the model of intended learning outcomes. The conclusion is that three problems of learning outcomes, previously discussed in the literature, become even more challenging when seen in the light of critical thinking.
"Writing is thinking on paper." (Zinsser, 1976, p. vii) Google the term "critical thinking." How many hits are there? On the day this tutorial was completed, Google found about 65,100,000 results in 0.56 seconds. That's an impressive number, and it grows more impressively large every day. That's because the nation's educators, business leaders, and political…
In recent decades, approaches to critical thinking have generally taken a practical turn, pivoting away from more abstract accounts - such as emphasizing the logical relations that hold between statements (Ennis, 1964) - and moving toward an emphasis on belief and action.According to the definition that Robert Ennis (2018) has been advocating for the last few decades, critical thinking is ...
focussed on the learner. It is performance-oriented, typically beginning with an action verb (e.g. 'demonstrate', 'apply'), typically written in the future tense, typically relating the action to the unit content, and typically specifying the des. ed level of performance. A learning outcome should be a clear statement of what the ...
you could write a learning outcome that looks similar to the following: Students participating in the SL206 Service Learning through Music Therapy course will demonstrate an increase in critical thinking skills, as exhibited by an improvement in scores on the Chronicle Critical Thinking pre-test/post-test instrument.
Increase Critical Thinking through Writing tackles the vital role of writing for enhancing literacy as a comprehensive strategy, facilitating improved understanding across various disciplines. This approach advocates for the integration of engaging writing tasks within every lesson, aiming to augment academic performance by prompting students ...
Writing Learning Outcomes. Once the promise of a course is understood and articulated, it is easier to talk about the student learning goals, which are typically written out in the form of learning outcomes. ... Think about not only what knowledge students should gain, but what skills they will be developing (critical thinking skills, creative ...
Increasingly, national stakeholders express concern that U.S. college graduates cannot adequately solve problems and think critically. As a set of cognitive abilities, critical thinking skills provide students with tangible academic, personal, and professional benefits that may ultimately address these concerns. As an instructional method, writing has long been perceived as a way to improve ...
What Are Student Learning Outcomes?Learning outcomes are statements of the knowledge, skills and abilities individual students should possess and can demonstrate upon completion of a learning experience. r sequence of learning experiences. Before preparing a list of learning outcomes consi. er the following recommendations: Learning outcomes.
Introduction. The ability to think critically is the fundamental characteristic of an educated person. It is required for just, civil society and governance, prized by employers, and essential for the growth of wisdom. Critical thinking is what most people name first when asked about the essential components of a college education.
At Avenues World School, critical thinking is one of the Avenues World Elements and is an enduring outcome embedded in students' early experiences through 12th grade. For instance, a ...
Guide to Critical/Creative Thinking. Intended Learning Outcome: Analyze, evaluate, and synthesize information in order to consider problems/ideas and transform them in innovative or imaginative ways (See below for definitions) Assessment may include but is not limited to the following criteria and intended outcomes:
Write learning outcomes that are too narrow: Avoid writing outcomes that are too narrow or focused on specific tasks, as this can limit the scope of learning. Write learning outcomes that are too broad: Learning outcomes that are too broad make it difficult to assess whether students have achieved the intended learnin .
ABSTRACT. The notion of critical thinking and its theoretical complexity are used as a case for an epistemological critique of the model of intended learning outcomes. The conclusion is that three problems of learning outcomes, previously discussed in the literature, become even more challenging when seen in the light of critical thinking.
You can apply our critical thinking model to your own work; use our Judging your own work (PDF) questions to help you decide if your writing is critical. These questions will take you through the description-analysis-evaluation stages. Take a look at further examples of descriptive writing vs. critical/analytical writing (PDF)
Critical Thinking. Although they are not always transparent to many college students, the academic and personal benefits of critical thinking are well established; students who can think critically tend to get better grades, are often better able to use reasoning in daily decisions (U.S. Department of Education, 1990), and are generally more employable (Carnevale and American Society for ...
Key points. Critical thinking requires us to simultaneously analyze and interpret different pieces of information. To effectively interpret information, one must first be able to remember it.
The instruments applied were Ryff's PWBS in its Spanish adaptation (Díaz et al., 2006) and the PENCRISAL critical thinking test (Saiz and Rivas, 2008; Rivas and Saiz, 2012). For academic performance, the academic records of the students participating in the critical thinking course in the first year of the psychology graduation were collected.