Douglas A. Bernstein
University of South Florida
Note: This article is based on a chapter to appear in R. J. Sternberg & W. Niu (eds.), A Multidisciplinary Approach to Critical Thinking. New York: Palgrave.

Anyone who has been teaching psychology for more than a few weeks knows that most of our students are nice, reasonable people who are anticipating an interesting course and hoping to do well in it. There are always a few exceptions, though, so we sometimes have students who challenge us in various ways. In the distant past, as when I started teaching in 1966, you could deal with these students without too much drama. That was because teachers had the power to establish and enforce policies about attendance, grading standards, make-up exams, deadlines, and the like and students were expected to accept those decisions, even if they weren’t happy about them. If they didn’t like you or your course, the worst they could do was give you lousy course evaluations. And unless most of the class did so every semester, those lousy evaluations were unlikely to have significant consequences for your pay raises or your prospects for tenure, promotion, retention, or teaching awards. This uneven distribution of power was comforting for teachers, though some of them tended to abuse it. For example, in 1975 a colleague at Western Washington State College (now University) proudly declared that “the tenured full professor represents the last bastion of absolute power in the world.”

I doubt that this was ever true, but since then, and especially over the last 10 or 15 years, the balance of power has been shifting in the opposite direction as administrators in higher education in North America have become ever more sensitive to student complaints about faculty as communicated through course evaluations, petitions, social media campaigns, and other channels. On some campuses, faculty have faced formal complaints, as well as organized protests and demands for disciplinary action or dismissal in response to something they said or did in class that even one student interpreted as oppressive or insensitive or harmful or hurtful or violent or racist. Even enforcing deadlines and setting high grading standards may be interpreted by some students as offensive signs of elitism, privilege, or worse. One observer described teaching in higher education today as “an exercise in avoiding tripwires” (Pettit, 2023). A database maintained by the Foundation for Individual Rights and Expression (FIRE) shows that in the last two years alone there were 63 student-initiated attempts to punish professors for what they said or did in the classroom (in 2000, there was one). More than two-thirds of these cases resulted in sanctions, up to and including suspension or dismissal, mainly against untenured faculty (Honeycutt, 2024).

Of course, some professors do behave in ways that deserve reporting, and those people should face the consequences of their bad behavior, but the cases in the FIRE survey involve situations in which faculty were attacked unreasonably (e.g. Cascone, 2024; Jones, 2022). And even though, as a percentage of all the students and professors taking and teaching courses in the United States every year, 63 student-initiated punishment attempts is a miniscule number, cases in which professors are unfairly targeted can—like the rare shark attacks and plane crashes that create fear of beaches and flying—create widespread fear among faculty.

It is no wonder, then, that according to a recent survey by the Chronicle of Higher Education, many college and university professors at all levels of seniority worry about doing things that might make students feel distressed, angry, or vengeful (McMurtrie, 2024). For example, about half of them give trigger warnings designed to prepare students for potentially upsetting course material (Kamenetz, 2016). Though there is strong evidence that such warnings are probably unnecessary, not very effective, and potentially counterproductive (e.g., Bridgland et al., 2023; Jones et al., 2020; Kimble et al., 2021, 2022; Sanson et al., 2019), professors still provide them, partly to establish themselves as trustworthy allies (Chew, 2023), but also to forestall students’ complaints, especially on course evaluations. One respondent to the Chronicle survey described the current preoccupation with student complaints as creating a “culture of fear and pandering” in which faculty who might otherwise employ firm but fair teaching methods and high grading standards are now adopting a more permissive approach. Another said, “I don’t discuss alternative values and arguments for positions I know my students hold.”

This last comment should be particularly troubling to psychology teachers because if fear of upsetting students prevents us from challenging their preconceptions, biases, assumptions, and misconceptions, it becomes much more difficult and potentially dangerous to ask them to consider multiple perspectives and alternative interpretations of research on sensitive or controversial topics. For example, based on what they have heard elsewhere, many students are likely to enter our courses believing that intelligence tests are inherently biased against minority groups (see Reynolds et al., 2021), that recovered memories of childhood abuse are common and accurate (see Hyman, 2000), that stereotype threat significantly impairs performance on high stakes academic tests (see Fourgassie et al., 2025; Steele & Aronson, 2000), or that most people (especially white people) harbor unconscious bias against other races that causes them to discriminate in various ways (see Charlesworth & Banaji, 2019; Oswald et al., 2013). Some of these students may not react well if their instructor presents evidence that qualifies, let alone contradicts those beliefs.

Concern over such reactions is not a problem for teachers whose courses don’t cover topics like these, or who play it safe by presenting the conventional wisdom about them that is typically presented in textbooks (e.g, Bartels, 2023). However, if you do address such topics and if you ask students to consider alternative interpretations of research about them, I am sure you have asked yourself how to do so while minimizing the risk of formal complaints, protests, or other undesirable consequences. If it were me, the first step would be to consider whether my teaching style provides a context in which challenging students’ preconceptions and sensitivities is expected and acceptable.

Tripwires and Teaching Styles

The teaching styles that we most often see in the classroom echo the four styles of parenting identified more than 50 years ago by developmental psychologist Diana Baumrind (1971). As you probably know, her classification system crosses two levels of parental involvement/support with two levels of demand for discipline to create permissive-neglectful, authoritarian, permissive-indulgent, and authoritative styles. Let’s consider what these relationship styles look like when applied to teaching (Bassett et al., 2013).

Teachers who personify a permissive-neglectful style do little more than come to class, deliver the same lectures year after year, discourage questions, and escape the classroom with as little student contact as possible. They generate plenty of student complaints, but these usually take the form of bad course evaluations, not protests or petitions because these teachers are not involved enough in their courses to address sensitive or controversial material, let alone promote critical thinking about it. Teachers who fit an authoritarian profile are similarly low on involvement but are preoccupied with enforcing strict discipline. Like authoritarian parents, they offer students little or no opportunity for discussion or argument. (These people are not necessarily bad teachers. Like me, you may have fond memories of tough instructors from whom you learned a lot, even though you might not have had much fun doing it.) Authoritarian professors are likely to march straight through academic minefields, teaching as they always have, and letting the chips fall where they may. Permissive-indulgent teachers tend to be deeply involved with their students and, like “helicopter parents,” perhaps too much so. They worry about the effects of academic stress on students’ mental health and self-esteem, and as a result, their courses may be only moderately demanding. They may believe that students’ efforts to succeed are at least as deserving of reward as the outcome of those efforts, as embodied in test scores and other performance assessments. This teaching style is the safest one on campuses where student activism is prevalent because it combines sensitivity to students’ sensitivities with flexible course requirements and deadlines.

An authoritative teaching style blends high involvement with firm but fair discipline. Authoritative teachers care about their teaching and their students, but they reward outcome, not just effort. They see students as responsible adults, so although they are willing to help, they are careful not to create dependency or to let themselves be exploited or manipulated. They reward student success with praise as well as high grades. They grant requests for special consideration only when justified by confirmed conditions or circumstances, and in accordance with institutional policies. They think carefully about their rules and standards, announce them in advance, explain why they are necessary, and enforce them consistently.

Like all category systems, this classification of teaching styles is not perfect, if for no other reason than that most teachers probably adopt elements of different styles in different situations, but my years of experience lead me to nominate a mainly authoritative teaching style as the best one overall. I say that first because it allows teachers to deal fairly but firmly with students’ special requests, grading complaints, and the like, but also because it has advantages that go beyond handling everyday administrative matters. One of the most important of these is that, because authoritative teachers consider students to be responsible adults, they can ask them to sign classroom contracts that establish agreements about how the course will be run.

The Syllabus as a Contract

Virtually every psychology teacher in North America offers a syllabus, and most teachers (and administrators) consider them to be formal agreements between themselves and their students. Some teachers even ask students to acknowledge having read, understood, and agreed to course policies about grading standards, the use of AI, definitions of plagiarism, and other topics. An outstanding example comes from my colleague Jennifer Coleman at Western New Mexico University (J. Coleman, personal communication, July 6, 2024). She requires her students to read and initial a list of course rules and policies and then sign the following statement:

I have read all policies and informational items, as indicated by my initials above. I understand that these are intended to support my success in the course and, more importantly, my learning and growth as a student. By signing here, I acknowledge that I will follow all policies and utilize the resources, including the schedule of due dates and writing checklist, as well as supplemental resources… and tutoring resources available, as needed.

I think the course syllabus is also a natural place to present the terms and conditions of a classroom contract whose mutual promises and commitments set the stage for critical thinking. For example, it can include statements designed to assure students that their teacher will: (1) be respectful toward them, (2) base grades solely on course performance, (3) present course material in an unbiased manner, (4) teach how to think about psychological science, not what to think about it, (5) encourage the free exchange of ideas, (6) welcome the expression of diverse viewpoints, including unpopular ones, and (7) be open to hearing complaints about the course. It can also convey expectations that students will: (1) recognize that some course content might be distressing, (2) agree to be open-minded when considering that content, (3) be tolerant and respectful of their classmates’ viewpoints, even if they find them offensive, and (4) bring complaints about the course to the instructor before taking them to others.

If you want explicit permission to challenge your students to think critically about sensitive and controversial topics, you can get it by asking them to initial a statement that reads something like this:

I agree to let you challenge me to think critically about the concepts, principles, and phenomena associated with (course title). I understand that you will ask me to consider and evaluate the validity of claims and evidence underlying its theories. I agree to keep an open mind about evidence and points of view that might conflict with what I know, or think I know. I understand that you will not be trying to prove that I am wrong, but to prompt me to ask myself if and why I am right. I acknowledge that the process of critical thinking might at times be distressing, but I recognize that experiencing a certain amount of discomfort is a vital part of my education.

Of course, even when students agree to be challenged and to think critically about those challenges, they may not always do so. Still, I would argue that when they initial that statement and remain enrolled in the course, it provides a framework that justifies, legitimizes—and may head off complaints about—your efforts to promote critical thinking about even the most sensitive and controversial course material.

Suppose, for example, that you plan to use a critical thinking framework that prompts students to ask themselves five questions about whatever course topic is under discussion: (1) What am I being asked to believe? (2) What evidence is available to support the assertion? (3) Are there alternative ways of interpreting that evidence? (4) What additional evidence would help to evaluate those alternative interpretations? and (5) What conclusions are most reasonable given the evidence available? (Bernstein, 2020). If that topic is, say, the claim that intelligence tests are unfairly biased against racial minorities, the most potentially contentious comments and inflammatory reactions are likely to come in response to the third question, because it is in relation to that question that you might be presenting evidence that challenges students’ existing assumptions and beliefs.

This is when a course contract can help. If there is pushback against your efforts to provoke critical thinking, be ready to display the slide you stashed in every PowerPoint deck that summarizes the contract terms and conditions that your students initialed. Doing so can provide them with a useful reminder of their agreement to entertain potentially distressing material and perspectives, while reinforcing your status as an authoritative teacher who can deal with any classroom situation in a firm, fair, and respectful manner.

 

References

Bartels, J. M. (2023). Indoctrination in introduction to psychology. Psychology Learning & Teaching, 22(3), 226-236.https://doi.org/10.1177/14757257231195450

Bassett, J. F., Snyder, T. L., Rogers, D. T., & Collins, C. L. (2013). Permissive, authoritarian, and authoritative instructors: Applying the concept of parenting styles to the college classroom. Individual Differences Research, 11, 1–11.

Baumrind, D. (1971). Current patterns of parental authority. Developmental Psychology Monographs, 4 (1, part 2).

Bernstein, D.A. (2020). Promoting critical thinking by teaching, or taking, psychology courses. In Sternberg, R.J. & Halpern, D.F. (Eds.), Critical thinking in psychology (2nd Ed.). New York: Cambridge University Press.

Bitzan, J. (2023). 2023 American college student freedom, progress and flourishing survey. Sheila and Robert Challey Institute for Global Innovation and Growth, North Dakota State University.

Bridgland, V. M. E., Jones, P. J., & Bellet, B. W. (2023). A meta-analysis of the efficacy of trigger warnings, content warnings, and content notes. Clinical Psychological Science, 0(0). https://doi.org/10.1177/21677026231186625

Cascone, S. (2024, July 24). Hamline settles with professor sacked over prophet Muhammad artworks. Artnet News. https://news.artnet.com/art-world/hamline-settles-with-sacked-professor-muhammad-censorship-2515768

Charlesworth, T. E. S., & Banaji, M. R. (2019). Patterns of implicit and explicit attitudes: I Long-term change and stability from 2007 to 2016. Psychological Science, 30(2), 174–192. https://doi-org.stetson.idm.oclc.org/10.1177/0956797618813087

Fourgassie, L., Subra, B., & Sanitioso, R. B. (2025). Revisiting the concept of stereotype threat(s): Is it all about the situation? Psychological Review. Advance online publication. https://doi-org.proxy2.library.illinois.edu/10.1037/rev0000555

Honeycutt, N. (2024). Silence in the Classroom: The 2024 FIRE Faculty Survey Report. The Foundation for Individual Rights and Expression. https://www.thefire.org/research-learn/silence-classroom-2024-fire-faculty-survey-report

Hyman, I. E., Jr. (2000). The memory wars. In U. Neisser & I. E. Hyman, Jr. (Eds.), Memory observed (2nd ed., pp. 374–379). New York: Worth.

Jones, P. J., Bellet, B. W., & McNally, R. J. (2020). Helping or harming? The effect of trigger warnings on individuals with trauma histories. Clinical Psychological Science, 8(5), 905–917. https://doi.org/10.1177/2167702620921341

Kamenetz, A. (2016, September 7). Half of professors in NPR Ed survey have used “trigger warnings.” National Public Radio. Retrieved from http://www.npr.org/sections/ed/2016/09/07/492979242/half-of-professors-in-npr-edsurvey-have-used-trigger-warnings

Kimble M, Flack W, Koide J, Bennion K, Brenneman M, Meyersburg C (2021) Student reactions to traumatic material in literature: Implications for trigger warnings. PLoS ONE 16(3):e0247579. https://doi.org/10.1371/journal.pone.0247579

Kimble, M., Koide, J., & Flack, W. F. (2022). Students responses to differing trigger warnings: A replication and extension. Journal of American College Health, 0(0), 1–4. https://doi.org/10.1080/07448481.2022.2098038

Jones, M. (2022, December 8) I was fired from NYU after students complained that the class was too hard. Who’s next? Boston Globe. https://archive.ph/1YWqc

McMurtrie, B. (2024, February 21). ‘A culture of fear and of pandering.’ The Chronicle of Higher Education. https://www.chronicle.com/article/a-culture-of-fear-and-of-pandering-what-readers-told-us-about-teaching-evaluations

Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., & Tetlock, P. E. (2013). Predicting

ethnic and racial discrimination: A meta-analysis of IAT criterion studies. Journal of

Personality and Social Psychology, 105(2), 171–192.

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Pettit, E. (2023). Power shift. The Chronicle of Higher Education, April 5.

Sanson, M., Strange, D., & Garry, M. (2019). Trigger warnings are trivially helpful at reducing negative affect, intrusive thoughts, and avoidance. Clinical Psychological Science, 7(4), 778–793. https://doi.org/10.1177/2167702619827018

Reynolds, C.R., Altmann, R.A., Allen, D.N. (2021). The problem of bias in psychological assessment. In C.R. Reynolds, R.A. Altmann, & D.N. Allen (Eds.), Mastering modern psychological testing (2nd ed., pp. 573-613). Springer, Cham. https://doi.org/10.1007/978-3-030-59455-8_15

Steele, C. M., & Aronson, J. (2000). Stereotype threat and the intellectual test performance of African Americans. In C. Stangor (Ed.), Stereotypes and prejudice: Essential readings (pp. 369–389). Philadelphia: Psychology Press/Taylor & Francis.

(Alannah) Shelby Rivers
Texas Woman's University

I recently attended Danny Oppenheimer’s excellent NITOP session “Choosing to learn: The importance of student autonomy in post-secondary education,” which discussed the benefits of offering student choices in assignments and course structure (e.g., allowing students to choose if attendance is part of their grade or not, or whether to complete a more challenging assignment compared to an easier alternative). After the talk, a new friend (another reason to love conferences!) turned to me and asked what I thought. I replied that that I already implemented several student choices in my courses, so I was very relieved to see that there was research being done to back up those “gut feelings.” I was half-joking, but it did make me realize how important my “gut feelings” about student autonomy and assignment choices are to my teaching practice more broadly. I had often thought about these as individual ideas and practices, but I realized I wanted to be more intentional about viewing student choice as a broader framework. It can be easy to say that I value giving my students choices, but what kinds of choices am I giving them?

Dabrowski and Marshall (2018) identified three key types of student choice in assignments. First, there is choice in content – for example, offering a choice in readings with similar themes or impact. Second, there is choice in product – allowing students to submit assignments in different mediums (podcast vs. website) or structures (application vs. critique). Finally, there is choice in process, such as choosing whether to collaborate and with whom, or what steps to complete and when. These types of choices are often combined (e.g., choosing both a modality and partners for a final project), but it was helpful for me to consider how I decide which choices to offer students, and I hope it is helpful for you as well.

I often offer content choices, especially in my lower-division courses such as Developmental Psychology (first-year level, 60-80 students). During many class sessions, we have what I call “Choose Your Own Adventure” activities, where students select a brief reading from a curated list representing a diversity of experiences related to the topic that may be unfamiliar. For example, when we cover middle childhood and the school transition, they may choose to read about experiences in Montessori schools, special education, homeschooling, or gifted & talented programs; when we cover birth, topics include planned c-sections, epidurals, doulas, and labor experiences from a variety of perspectives (e.g., Black women, trans men). Then, students share about the different perspectives they read (either in small groups, or using online responses), including why they chose that particular reading, and we come together in an open discussion to try to find common themes as well as areas of divergence across the perspectives.

Students have responded well to these choices and often ask for more of these activities. These content choices seem like the most intuitively easy form of choice to introduce, and that is borne out in the literature; a recent study (Harrington, 2024) that reviewed syllabi posted to STP’s website found that over half of the syllabi included content choices, compared to just 25% giving choices in product and 6% in process. Still, there may be circumstances where this form of choice is not appropriate for the pedagogical goals of the course. For example, in my graduate-level discussion seminar Advanced Developmental Psychology (10-20 students), I require everyone to read the same articles, both to ensure all students become familiar with some of the major theories and most recent research, and because this allows for deeper and more meaningful discussion during the three-hour class sessions.

I have also offered product choices in both lower- and upper-division courses, often in concert with content choices. For example, multiple courses include a “creative final project,” where students propose a method of sharing or implementing course content with a unique audience and appropriately creative way of reaching that audience (e.g., Instagram page for college students, picture book for young children, short video for busy medical professionals). This has been highly effective in my upper-level courses, but some first-year students have struggled with the scope of choices they have to make. For example, students may repeatedly ask for ideas from previous classes and may not consider content we will cover later in the class or ways to present the material outside of a paper or PowerPoint. As a result, I have begun implementing more scaffolding in these courses; in Developmental Psychology (60-80 students), I usually dedicate a full class day where I ask students to submit three project ideas to anonymously share with the full class, and I provide feedback (also to the full class). In smaller classes (e.g., Health Psychology, 30-40 students), I have sometimes formed small groups based on the themes of the project ideas so students can discuss their ideas with others who have similar interests. I also have three check-in dates throughout the semester that give students a chance to revisit their product selection.

More complex, and more uncommon in psychology syllabi (Harrington, 2024), are “cafeteria-style” assignments, where students can mix and match different assignment options in order to meet required credit. I have tried this in several of my classes by moving my lower-stakes assignments into a catch-all category of “Applications.” Each type of option has a set point value (e.g., 1 point for watching a documentary, 2 for reading an academic article, 3 for hands-on activities), and students earn points based on the combinations of assignments they have chosen up to the total amount of points available for the assignment category (usually 10). Some students will earn all of their credit in one category, such as by reading and annotating several articles, whereas others will pull a little from each category to have a variety of activities. This system can promote better performance and student satisfaction, but it can lead to greater burden on instructors who have to create more assignments to choose from (Arendt et al., 2016). To offload some of this work, I allow students to suggest their own Applications, vetted by me and with a cut-off date somewhat earlier in the semester. In most semesters, I add at least a few assignment options this way – for example, in my upper-level Addiction course (30-50 students), a student suggested a 3-point assignment where they reach out to a local treatment center to learn more about their therapeutic approach. I also find the system can be confusing (also reported in Arendt et al., 2016), so dedicating significant time to explaining and answering questions can be required.

Finally, I have been experimenting with process choices pertaining to deadlines, sequencing, and collaboration. Often these choices overlap with content and product choices, leading to the most flexible assignments. For example, in my creative final projects described above, I have been more recently offering the option to complete the project either alone or in a small group (up to three students total), instead of my previous default to group work. Students responded very positively to this decision; I observed less conflict and greater group cohesion among the large percentage of students who ultimately chose to collaborate. However, it is important to consider what might be lost with these choices; as Nichols (2023) notes, allowing extensive student choice in product and processes may lead to areas of weakness (e.g., collaboration) going unaddressed. There may also be practical consequences; in Developmental Psychology (60-80 students), even my usual “three-minute thesis” style project presentations would take more than a week if students worked alone, so I ended up cutting them entirely.

Compared to group work decisions, worries about the consequences of giving students choices related to deadlines and sequencing may be more obvious – what if students wait until the last minute and work is late, incomplete, or missing? In my view, these fears are not unfounded. In the Applications described above, students have almost the entire semester to turn in their selected assignments. Although I encourage students to turn the Applications in as they go, reliably, a small percentage of the class will not begin to work on these assignments until the very end and will come up short against my at-that-point unforgiving late policy. Moreover, as Nichols (2023) found, while most students will turn in the work on time and report an increase in interest, this approach tends to lead to a large amount of concentrated grading for faculty, which can be especially difficult at the end of the semester. Perhaps it is better to compromise; I have found some success with a semi-flexible strategy in Applied Statistics (sophomore-level). A large part of the coursework in this class comprises SPSS labs, and students often need repeated practice and hands-on support (from me or from our statistics tutors) to really master the skills. As such, I allow resubmissions and late assignments until the exam where the material is covered. This neatly breaks up the class into a few digestible chunks and prevents students from waiting until the very end to submit, while still giving choices and opportunities for recovery.

Ultimately, making choices about student choices is not easy, but it is full of exciting possibilities that can lead to more engaging and meaningful experiences. When making these decisions, it can be helpful to keep in mind that some types of choices may be more unfamiliar to your students. More choice is not always perceived as positive, and you may need to budget more time than you expect to help students understand their options and feel prepared to take on new challenges. Therefore, it may be wise to start small. Content choices can be highly impactful and may be more familiar to students and less burdensome to instructors. Consider choices that can be included in just one assignment or in-class activity and expand as needed. Finally, just like with any pedagogical decision, it can be very helpful to explain to students why you are offering these particular choices. For example, while I now use it in other classes, I developed the Applications assignment for my Addiction class because there was such a range of student goals in taking the class. Many students are interested in clinical or counseling careers working with clients who may have substance use disorders, while others come from biology or neuroscience and are more interested in the mechanics of individual substances. Another contingent of students have a more personal interest in the topic, based on their own experiences or those of their loved ones. I wanted to offer all of these students the chance to do further exploration of what mattered most to them. Explaining this to students seemed to help address lingering questions about the assignment and even opened up broader conversations about what choices I do not offer and our course learning goals. Not all choices will be the right fit for every class, but I believe being more intentional about the choices I give students will make my teaching more effective – no matter the course.

References

Arendt, A., Trego, A., & Allred, J. (2016). Students reach beyond expectations with cafeteria style grading. Journal of Applied Research in Higher Education, 8(1), 2–17. https://doi.org/10.1108/JARHE-03-2014-0048

Dabrowski, J., & Marshall, T. R. (2018). Motivation and engagement in student assignments: The role of choice and relevancy. The Education Trust, 1-14. https://edtrust.org/resource/motivation-and-engagement-in-student-assignments/

Harrington, C. (2024). How much assignment choice do students have? A descriptive study of syllabi. Currents in Teaching and Learning, 15(2), 6-12.

Nichols, G. (2023). Assignment choices in an upper level biology course increase engagement and course satisfaction. The American Biology Teacher, 85(6), 351–354. https://doi.org/10.1525/abt.2023.85.6.351

Oppenheimer, D. (2025, January). Choosing to learn: The importance of student autonomy in post-secondary education. Presentation at the annual meeting of the National Institute on the Teaching of Psychology.

Brian Stone
Boise State University

Much has been written in the past couple years about how large language models (LLMs) like ChatGPT, Gemini, and Claude threaten the traditional essay or paper as an assignment. Indeed, at this point LLMs can write in ways that are hard for most instructors to tell apart from human writing (Scarfe et al., 2024). (I invite reflection on the toupee fallacy.) For those instructors who played around with earlier LLMs like ChatGPT 3.5 and haven't kept up with more recent developments and services like ChatGPT Deep Research (powered by the o3 model) or Gemini Deep Research, you may be surprised that the technology has largely moved beyond the point of hallucinated references and vague summarizing. 

While frontier models may be financially out of reach for students right now (ChatGPT Pro is $200/month), other services like DeepSeek are stepping in with freely accessible models that bring more up-to-date performance into reach for cash-strapped students. Meanwhile, countless paper-writing apps layered onto existing LLMs are highlighted to students on TikTok and Instagram through targeted marketing and influencer partnerships. Students are definitely using generative AI, and my recent data found that around 60% of students self-report having used AI to cheat (up from around 40% a year earlier in a nearly-identical sample; Stone, 2025). 

Instructors have adopted a variety of strategies in response to the easy availability of AI-generated papers, some of which have proven less robust than others to recent technical developments. After briefly surveying this, I will share a specific AI-resistant paper alternative I've experimented with in the past two years.

Instructor Strategies Meet Recent AI Developments

AI detection faces signal detection issues like false negatives and false positives, and research on detectors is not promising at this point (Malik & Amjad, 2025; Tufts et al., 2025). Meanwhile, false accusations damage student-instructor relationships. In my recent survey 11% of students reported being falsely accused, and it may be hitting first-gen students at a higher rate than non-first-gen (Stone, 2025). Regardless, most detection methods fail when AI-generated writing is adjusted with further AI paraphrasing (Sadasivan et al., 2024) and "humanizing" apps are advertised widely to students on social media to make AI papers undetectable.

Some instructors argue we should concentrate on the students who genuinely try: put the responsibility onto students to figure out when AI use helps or harms their learning, or maybe we just need to talk to students and convince them of the value of exercising their own mental muscles. Others decry the costs of developing an adversarial relationship with students, creating anxiety through surveillance, inducing worries about false accusations, and over-emphasizing performance and product over process and learning.

Early attempts to make writing assignments AI resistant are falling to recent technical advances. LLMs can generate outlines or draft papers in parts and stages (with deliberate errors and typos) and directly incorporate instructor comments into iterative drafts. Likewise, focusing assignments on events more recent than the model's training cutoff no longer works given that current models can browse the internet, access daily news, view preprint articles, and analyze [the transcript of] a YouTube/TED talk. Referencing specific details and examples from course readings or slides is easy for LLMs that now allow attachments like slides, articles, or even entire books. Meeting-recording tools like Otter.ai may soon allow a student who wasn't in class to reference specifics from that day's discussion into AI writing.

Many instructors are requiring students to compose in Google Docs with shared editing access or in Word with track changes or to use Grammarly's Authorship tool. This allows an instructor to see time-stamped writing and editing history, and browser plugins like Draftback visualize the editing process to spot odd behavior like pasting in large chunks of text. Nothing stops the student from typing in AI text word-by-word (though this behavior looks different from genuine writing). Yet recent developments in agentic AI like OpenAI's Operator appear already capable of creating and writing into a Google Doc through a process that looks superficially similar to real human writing (writing in bursts, removing and retyping, copying and pasting bits around), so we are back at an arms race. 

Some (including myself) are moving the writing process and/or assessment in-person for non-online courses (blue books are back!). However, this limits class time for other activities, limits the length and scope of writing, and can be complicated due to slow or anxious writers, poor handwriting, and accommodations incompatible with time-limited writing. That said, written communication in general and lengthy structured writing in particular may be their own learning objectives, in which case we may just have to satisfice and accept some amount of cheating, as we always have.

Other instructors may directly integrate AI into their courses, ideally in a way that teaches critical AI literacy and ethical usage. AI may be integral to many future careers and become an important part of psychology education specifically (Koumpan & McOwen, 2024; Lim & Lee, 2024). The skillful psychology student should demonstrate adaptability to new technology, says the APA. Maybe we just need to teach students how to credit their AI usage (Albada & Woods, 2024); indeed, the APA style guide tells us how to cite AI. However, while using and integrating AI may become part of psychology student training (including to train critical thinking; Costello et al, 2024), this may not be a good fit for all courses or would require sacrificing other learning objectives. Furthermore, integrating AI in the wrong way may in some cases actively harm learning (Bastini et al., 2024; Gerlich, 2025; Lee et al., 2025; Spatola, 2024; Stadler et al., 2024).

Finally, many instructors are moving away from essays and papers altogether. For example, some have integrated social annotations like Perusall to encourage critical reading. Others have moved toward podcasts, videos, and infographics as paper alternatives, and while these can be great ways to serve and assess learning objectives, these other mediums are still susceptible to AI usage. Not only can recent AI write an engaging and accurate script for a podcast, free services like Google's Notebook LM can generate an entire podcast on any topic imaginable. Likewise, AI can generate the script for a video or presentation and some apps are starting to generate decent slide decks and infographics. At this stage, the average AI-generated project may still be worse than a good student-generated project, but it won't be surprising if that gap shrinks in the near future.

Live Critical Discussion: My Book Club Case Study

Another alternative to essays and papers that could still serve many of the same learning objectives would be critical discussion by students in groups, and that's what I want to focus on for the rest of this piece. As you'll see, it may not completely solve the AI problem, but for now the in-the-moment nature of synchronous discussion seems harder to fake.

Specifically, I want to share the case study of how I moved from having students in my 100-person upper-division cognitive psychology course write a paper on Kahneman's book Thinking, Fast and Slow to having them record book club-style critical group discussions. In both versions of the assignment, students had to reference specifics from the book to make their points, come up with connections to their own life, and talk about their take-aways from the book. In previous years, they were required to incorporate that into a paper about the book; in recent semesters, they have done so as part of their preparation notes for and live contributions during a group discussion.

Specifically, twice during the semester I have groups of roughly seven students meet synchronously over Zoom for 75-90 minutes each time. In my case, they address half of the book in each meeting, but this could be split up differently or done all in one session. The key is requiring them to use Zoom's "record to cloud" feature (or similar for other platforms) so that they can share the entire recording with me afterward. 

Their preparation before a book club consists of reading and jotting down notes on each of the assigned chapters, but also doing a deep dive and extra preparation on a subset of chapters which they lead some critical discussion on.

There's no doubt a student could feed the book into an LLM and ask for notes on each chapter (just as some students have historically turned to Cliff's Notes rather than the original source), but such students tend to have much lower-quality contributions and reactions during the discussion. Indeed, the times where preparation notes have looked 'off' (likely auto-generated) have been the times where the same student seems to read from their notes verbatim when 'leading' discussion of their chapters and the times where a student does very poorly and superficially at responding to their peers in the moment. More importantly, a large portion of their grade comes from the quality of their emergent discussion and it's pretty clear when someone has done the reading themselves and can pull some examples or make connections on the fly. 

During their synchronous meeting, students are required to contribute actively throughout. They are also encouraged to invite quieter teammates to speak up. After the discussion, they submit the recording link and a post-meeting reflection in which they report on the discussion (e.g., specific examples that changed their mind) and can confidentially name any teammate who went above-and-beyond or seemed entirely unprepared and unengaged. I also have them submit screenshots of their handwritten notes and prep as part of the submission (this can include pictures of annotations in the book).

I watch chunks of the discussions on high playback speed while looking for individual contribution quality, and in the end, I have found the grading time to be far shorter than when assigning papers. In a class of 100, I have 14 videos to skim through, and the individual student's prep and post-meeting reflection can be graded at a fairly quick glance using a rubric. No need to watch an entire video: as I skip around and watch selections on high playback speed, I click through the rubric for each student when I've witnessed a sufficient number of high-quality, on-topic contributions throughout and ensured they aren't reading from a script when discussing their assigned chapters to lead.

I have used this assignment in synchronous courses (in-person and online), in which case the groups meet during our assigned class time in order to keep scheduling simple, but I have also used it in asynchronous courses. In the latter case, it requires some logistical work ahead of time to set up scheduling: I provide a little logistical support in the form of sign-up sheets for possible times and a discussion board to propose alternative times. In other words, for asynchronous courses, they group based on schedule availability rather than me assigning groups first. 

In feedback and course evaluations for asynchronous courses, students have told me this one synchronous assignment really increased their sense of belonging and connection to their peers far better than alternatives like discussion boards.

This assignment is certainly not identical to writing a paper about a scholarly book, but for me it has served to retain many of the same learning objectives (around critical reading, communicating, making connections to course concepts). Crucially, it seems harder for students to do well if they haven't done the work (i.e., read the book and given it some thought) because the nature of live critical discussion requires students to respond in the moment to arguments and connections raised by their peers.

While this assignment idea is far from solving the AI issue, I have found it to be a fun updated assignment option that -- for now -- seems better than traditional papers at guaranteeing active and critical engagement with material like a scholarly book.

 

References

Albada, N. A., & Woods, V. E. (2024). Giving credit where credit is due: An artificial intelligence contribution statement for research methods writing assignments. Teaching of Psychology. Advance online publication. https://doi.org/10.1177/00986283241259750

Bastini, H., Bastini, O., Sungu, A., Ge, H., Kabakci, O., Mariman, R. (2024). Generative AI can harm learning. The Wharton School Research Paper, 1-59. https://doi.org/10.2139/ssrn.4895486

Costello, T. H., Pennycook, G., & Rand, D. G. (2024). Durable reducing conspiracy beliefs through dialogues with AI. Science, 385(6714). https://doi.org/10.1126/science.adq1814

Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 1-28. https://doi.org/10.3390/soc15010006

Koumpan, E., & McOwen, L. (2024). Revolutionizing talent: The path in 21st century workforce transformation. In: V. Salminen (Ed.), Human factors, business management and society vol. 135 (pp. 74–83). AHFE International. https://doi.org/10.54941/ahfe1004932

Lee, H., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3706598.3713778

Lim S. C. J., Lee M. F. (2024). Rethinking education in the era of artificial intelligence (AI): Towards future workforce competitiveness and business success. In A. O. J. Kwok & P. Teh (Eds.), Emerging technologies in business (pp. 151–166). Springer. https://doi.org/10.1007/978-981-97-2211-2_7

Malik, M. A., & Aljad, A. I. (2025). AI vs AI: How effective are Turnitin, ZeroGPT, GPTZero, and Writer AI in detecting text generated by ChatGPT, Perplexity, and Gemini? Journal of Applied Learning & Teaching, 8(1), 1-11. https://doi.org/10.37074/jalt.2025.8.1.9

Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., & Feizi, S. (2024, February 19). Can AI-generated text be reliably detected? ArXiV preprint. https://doi.org/10.48550/arXiv.2303.11156

Scarfe, P., Watcham, K., Clarke, A., & Roesch, E. (2024). A real-world test of artificial intelligence infiltration of a university examinations system: A "Turing Test" case study. PLoS ONE, 1-21. https://doi.org/10.1371/journal.pone.0305354 

Spatola, N. (2024). The efficiency-accountability tradeoff in AI integration: Effects on human performance and over-reliance. Computers in Human Behavior: Artificial Humans, 2(2), 1-10. https://doi.org/10.1016/j.chbah.2024.100099

Stadler, M., Bannert, M., & Sialor, M. (2024). Cognitive ease as a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry. Computers in Human Behavior, 160, 1-7. https://doi.org/10.1016/j.chb.2024.108386

Stone, B. W. (2025). Generative AI in higher education: Uncertain students, ambiguous use cases, and mercenary perspectives. Teaching of Psychology. Advance online publication. https://doi.org/10.1177/00986283241305398

Tufts, B. Zhao, X., & Li, L. (2025, February 9). A practical examination of AI-generated text detectors for large language models. ArXiV preprint. https://doi.org/10.48550/arXiv.2412.05139

Mircea Zloteanu
Kingston University London

A considerable amount has been written about the challenges surrounding teaching statistics in psychology, often in a self-reinforcing loop: “We teach these methods because they are expected, and they are expected because this is what is taught.” For decades, critiques of hypothesis testing have highlighted the problems caused by an overreliance on dichotomous decisions, p-values (e.g., p > .05), and the pursuit of statistical significance (Emmert-Streib, 2024). The debate has alternated between calls to “abandon p-values” and retorts that “p-values are fine*” (*where issues are reframed as features rather than bugs). For example, the fact that p-value are affected by sample size, leading to their “dance” in small samples and their certainty of significance in large samples, is often not given the importance it should when teaching statistics (Cumming & Calin-Jageman, 2024). Yet while statisticians and philosophers of science engage in these debates (Chen, et al., 2023), they often overlook a critical audience: people trying to learn this stuff.

One recurring, and valid, critique of null hypothesis significance testing (NHST) is that “it is difficult to understand.” While the process is often outlined in a few easy steps, the reality of frequentist hypothesis testing is much more nuanced and requires a specific kind of thinking that is (arguably) not intuitive to many learners (Rafi & Greenland, 2020).

A good example is simply the probability that p-values refer to. Many students (and researchers) tend to produce a sentence like this: “The p-value is the probability that the null hypothesis is true." This might seem correct, but this is a false statement, referred to as transposing the conditional. A p-value refers to the following probability: P(data | null hypothesis is true). In lay speak, it is the probability of the data given that the null is true. Thus, a p-value only speaks to the compatibility or surprisingness of the data given what we believe to be the state of the world (Rovetta, 2024). However, people often mistakenly think the p-value tells us: P(null hypothesis is true | data). This is the probability that the null hypothesis is true, given the observed data. These two probabilities are not the same and can have real-world consequences if confused (e.g., the prosecutor’s fallacy).

In my own teaching, I have found this to be a common mistake students make; one that is difficult to correct, as the misinterpretation seems to resonate more with people. Even if a diligent student attempts to learn the correct interpretation on their own, the textbook they use may be of no help (Gliner, et al., 2002). A study found 89% of introductory statistics handbooks contain incorrect definitions of p-values (Cassidy, et al., 2019). NHST seems to be a difficult framework to learn.

Having NHST as the default approach for research and publishing in psychology extends beyond researchers to students who are learning these methods. The incentive structure of academic publishing prioritizes statistical significance, leading to questionable research practices (QRPs)—strategies to artificially enhance "statistically significant" results (e.g., p-hacking; Amrhein, et al., 2017). This mentality affects students from the moment they begin learning statistical analyses, fostering “significance anxiety.” Students often worry when their dissertation results yield a non-significant p-value, believing they have done something wrong, that their thinking was incorrect, or that they will fail their degree. Such concerns are unwarranted, as both significant and non-significant results are part of the scientific (and learning) process, but this fact seems at odds with all other signals in our field (Moran, et al., 2023).

Learning Made Easier with Estimation Statistics

The above paints a bleak picture of the NHST framework for teaching and practice. While there are several frameworks that can substitute the traditional approach, most require significant time commitments and adjustments to how we think about experiments (e.g., Bayesian statistics). One alternative that permits a more fluid transition away from p-values while retaining the core components of frequentist thinking is Estimation Statistics (ES). ES, as its name suggests, focuses on estimating effects of interest, contrasting the NHST’s “is there an effect?” mentality. The core question asked by ES is “what is the magnitude and uncertainty of my effect?”

ES shifts the focus to understanding what the study in front of you can say, prioritises communicating effects in a meaningful way, accompanied by their margin of error and practical importance, and focuses on the visual presentation of results. Importantly, the emphasis is placed on meta-analyses and cumulative evidence, reminding researchers that a single study cannot say much. Tools like estimation plots, which display all data points, and meta-analyses make it easier to see patterns across studies rather than fixating on individual p-values. While I cannot do the approach justice in a few paragraphs, I encourage readers to read Introduction to the New Statistics (Cumming & Calin-Jageman, 2024). This has been the handbook I have used for the past 3 years, with great success, especially in my 1st year introduction to statistics classes.

To provide a concrete example of the difference in approaches, let us imagine a study comparing Aerobic and Strength-based exercise for decreased resting heart rate. Now we assume that there is a difference observed between the two groups. The table below provides an example of how this result would be reported under the two approaches:

In NHST, results can be confined to simply reporting the observed p-value (or even just p < α) and claiming that a non-zero effect was found. This says nothing of the size of the effect, its uncertainty, or its relevance. In ES, reporting focuses specifically on the effect size in question, communicating its magnitude, margin of error, and interpretation.

Another advantage of ES is that it deepens students’ understanding of effect size interpretation. Students begin to think more about what effects actually mean, move beyond binary conclusions, and develop a stronger appreciation for the role of uncertainty in statistical analyses and communication. Furthermore, they engage more deeply with their research questions: they ask whether the results make sense and explore concepts such as practical significance. This reflective approach strengthens their analytical and scientific reasoning.

Estimation-based approaches also foster a stronger focus on data visualisation, an essential skill in statistics. Students become more comfortable plotting data and critically evaluating the appropriateness of their figures. They begin to consider diverse visualisations and often uncover hidden patterns or issues in the data that might otherwise go unnoticed. By placing greater emphasis on data visualisation, students develop the habit of thinking critically about effective science communication.

On the left would be a typical bar plot that accompanies the NHST reporting above, with the asterisks denoting a “significant” difference. On the right is an estimation plot (aka. a Gardner-Altman plot) that would accompany the above ES reporting. The ES plot displays all data points, the mean of each group, and confidence intervals per group. Alongside these is the mean difference (the effect) and its uncertainty, with appropriate labels to understand the direction of the comparison. The estimation plot reduces misleading interpretations regarding the variability of the data by illustrating that values can/do occur above the group mean (and higher than one may believe if relying on the standard error bars) and highlights the size and uncertainty of the effect (for details, see Ho et al., 2019).

Switching to ES can improve students’ understanding of statistical concepts. Within my own experience across several cohorts, test scores show marked improvement and first-attempt progression rates increase. Beyond measurable outcomes, students report feeling more confident and frequently comment that it just “makes sense,” to connect the statistics being reported with the information one wants: the effect. As ES’ entire focus is on reporting, interpreting, and visualising the effect of interest and the abstraction of the hypothesis to the statistical procedure is reduced. NHST can be quite opaque in how it treats testing, amounting to a convoluted p-value producing contraption. ES places communication and clarity at the heart of the testing procedure, giving students more confidence in their reporting and understanding. This confidence is reflected in the quality of their work. By focusing on estimation, students engage more directly with the meaning of their results, rather than relying on rote procedures. No longer is the focus on a single number summary being above or below a critical threshold; now, attention shifts to the actual observed effect and how it contributes to our scientific understanding.

Navigating Institutional Resistance to Change

A barrier to adopting ES is the difficulty of institutional change. Transitioning away from entrenched practices like NHST requires supervisors, lecturers, and support staff to not only understand the new methods but also actively support students who use them. This can be challenging, as academic staff often juggle numerous commitments, leaving little time to learn a new framework or adapt their own workflows. Without adequate time, resources, and institutional support, the adoption of ES can feel like an added burden rather than an improvement. Successful implementation requires thoughtful onboarding, with line managers and department heads providing the necessary resources, training, and encouragement. Institutional inertia—where established practices are seen as "good enough"—can slow progress, as some may view the change as unnecessary or disruptive.

Thankfully, adopting ES does not require discarding the foundations of NHST. The two approaches operate under the same principles, and much of the information is interchangeable. For instance, any NHST values—such as p-values and t-values—can be re-computed using the descriptive statistics provided in estimation outputs (see Francis, 2017). This means that switching to estimation as the default teaching framework does not prevent students from understanding or using NHST methods when required. Moreover, the common objection that “real-world publications will demand p-values” is rendered moot; researchers can simply reply “compute it yourself.” By grounding students’ understanding in estimation first, they are better equipped to handle modern and traditional statistical demands without being constrained by the limitations of NHST.

Summary

ES offer a practical and effective alternative to NHST, easily integrating into existing curricula. Students, even those with minimal statistical background, find the approach intuitive and accessible, reducing misunderstandings and improving their ability to interpret and communicate findings. With a wealth of free online resources available (e.g., www.estimationstats.com; esci.thenewstatistics.com), including comprehensive courses, ES is both affordable and adaptable (dabsetr R package, esci module in Jamovi, and soon in JASP). Most importantly, it enhances statistical thinking for all learners, fostering a deeper understanding of data and its interpretation. Adopting ES is a step forward in creating more proficient and critical researchers.

References

Amrhein, V., Korner-Nievergelt, F., & Roth, T. (2017). The earth is flat (p> 0.05): significance thresholds and the crisis of unreplicable research. PeerJ, 5, e3544.

Cassidy, S. A., Dimova, R., Giguère, B., Spence, J. R., & Stanley, D. J. (2019). Failing grade: 89% of introduction-to-psychology textbooks that define or explain statistical significance do so incorrectly. Advances in Methods and Practices in Psychological Science, 2(3), 233-239. https://doi.org/10.1177/2515245919858072

Chen, O. Y., Bodelet, J. S., Saraiva, R. G., Phan, H., Di, J., Nagels, G., ... & De Vos, M. (2023). The roles, challenges, and merits of the p value. Patterns, 4(12). https://doi.org/10.1016/j.patter.2023.100878

Cumming, G., & Calin-Jageman, R. (2024). Introduction to the New Statistics: Estimation, Open Science, and Beyond (2nd ed.). Routledge. https://doi.org/10.4324/9781032689470

Emmert-Streib, F. (2024). Trends in null hypothesis significance testing: Still going strong. Heliyon, 10(21).

Francis, G. (2017). Equivalent statistics and data interpretation. Behavior research methods, 49(4), 1524-1538. https://doi.org/10.3758/s13428-016-0812-3

Gliner, J. A., Leech, N. L., & Morgan, G. A. (2002). Problems With Null Hypothesis Significance Testing (NHST): What Do the Textbooks Say? The Journal of Experimental Education, 71(1), 83–92. https://doi.org/10.1080/00220970209602058

Ho, J., Tumkaya, T., Aryal, S., Choi, H., & Claridge-Chang, A. (2019). Moving beyond P values: data analysis with estimation graphics. Nature methods, 16(7), 565-566. https://doi.org/10.1038/s41592-019-0470-3

Moran, C., Richard, A., Wilson, K., Twomey, R., & Coroiu, A. (2023). I know it’s bad, but I have been pressured into it: Questionable research practices among psychology students in Canada. Canadian Psychology / Psychologie canadienne, 64(1), 12-24. https://doi.org/10.1037/cap0000326

Rafi, Z., & Greenland, S. (2020). Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise. BMC medical research methodology, 20, 1-13. https://doi.org/10.1186/s12874-020-01105-9

Rovetta, A. (2024). S-values and Surprisal intervals to Replace P-values and Confidence Intervals. REVSTAT-Statistical Journal.

Rachel T. Walker
University of the Incarnate Word

Have you ever said, “I will never do that!”?

In the past, I told myself I’d never take a psychology course—and then I ended up earning a Ph.D. in Experimental Psychology. I said I’d never teach college classes, but that changed when I started teaching as an undergraduate student. I claimed I’d never do research on human behavior (my focus has always been animal behavior), yet I found myself studying teaching and learning strategies. I was certain I’d never teach an online class, but then COVID hit, and suddenly all my classes were online.

I used to say I’d never use ChatGPT in my teaching. But life has a funny way of challenging our “nevers”! Now, it’s become an integral part of my teaching strategy. The moment I started exploring generative AI tools, I realized their potential to transform educational practices. These tools offer support in designing interactive and inquiry-based lesson plans, making it easier to create engaging content that fosters curiosity and encourages active learning (Moundridou et al., 2024). Inspired by these possibilities, I searched for research articles to understand how generative AI could enhance my approach as an instructor. I even discovered how classifying these tools by their potential applications provides educators with a clear pathway to integrate technology effectively into the classroom (Mollick & Mollick, 2023). It’s amazing how what I once resisted is now helping me grow in ways I never imagined.

When ChatGPT was first released, I took a cautious approach and waited a few years before considering it as a teaching tool. However, as I developed a new course titled Psychology in the Digital World, it became clear that generative AI could significantly enhance the creation of engaging classroom discussions and assignments. The course's focus on the digital world naturally led me to explore the potential of incorporating generative AI to streamline the development of instructional materials.

Let us start at the beginning: How did I use generative AI tools to assist in creating assignments? I had often thought about ways to design in-class discussions that would encourage students to reflect on and engage with content in meaningful ways. For instance, early in my courses, I teach research methods and ethics by providing definitions, examples, and exploring their advantages and disadvantages. I wanted students to go beyond simply understanding the material—I wanted them to process and apply what they had learned by evaluating hypothetical research scenarios. While I knew I could brainstorm ideas on my own, I was not confident in my ability to create scenarios outside my area of expertise. Additionally, I wanted the discussions to have a clear structure and be directly applicable to real-world situations, ensuring students could see the relevance of what they were learning.

While there are various generative AI tools available to assist in this goal, I decided to use ChatGPT. ChatGPT has the potential to enrich student discussions, foster collaboration, and provide more relevant and meaningful learning experiences (Adıgüzel et al., 2024). I was interested in how this generative AI tool could assist with the process of creating: scenarios that could be used in class discussions, written assignments based on the discussion, and grading rubrics for the assignment. I used ChatGPT to learn how to create clear engineering prompts and evaluate scenarios to ensure they met my learning objectives. Additionally, ChatGPT’s application for creating in-class discussion scenarios helped me investigate a potential practical impact on student learning. In these in-class discussion scenarios, I have students interact in small groups. Instructions generated by ChatGPT provided students with clear objectives and directions for their in-class discussion and writing assignment. The small groups then shared their discussion with the class.

Thus far, I have provided a broad overview of how I used ChatGPT to investigate teaching strategies, highlighting its role in generating ideas, refining approaches, and identifying potential challenges. Now, I will provide a more detailed description of the process.

When I began my journey with ChatGPT, I had to learn to be both creative and patient. I first asked a question about how to use artificial intelligence (AI) tools in teaching college students, specifically focusing on the benefits and disadvantages. The benefits included personalized learning assistance, 24/7 availability, reduced administrative burden, and increased engagement and motivation. ChatGPT also highlighted potential disadvantages, such as accuracy and reliability issues, potential over-reliance, and bias in AI responses.

What I found particularly helpful was that ChatGPT provided detailed statements and references within these topics. However, I also learned during this process that it was important to confirm that references came from the original source, as hallucinations in generated content can sometimes introduce false or misleading information.

I then started asking ChatGPT questions to help me brainstorm how I could effectively use it in my courses. First, I asked it to generate discussion questions that would explore the potential uses of ChatGPT in college courses. ChatGPT provided a series of responses, including:

• Ethical Considerations: What are the ethical implications of using AI tools like ChatGPT in academic settings? How can we ensure responsible and fair use of AI-generated content?
• Critical Thinking: How can instructors incorporate ChatGPT in a way that promotes critical thinking rather than replacing it? What types of assignments or activities could be designed to ensure students actively engage with the material?

While exploring the use of ChatGPT, I became interested in examining how it is utilized in the workplace. I wanted to learn more about how ethics can be considered in a workplace setting. Here is one example I received:

• Ethical and Privacy Considerations: What ethical and privacy concerns should organizations address when using AI tools like ChatGPT in the workplace? How can businesses ensure data security and ethical use of AI-generated content?

These types of responses helped me brainstorm more specific questions about how ChatGPT could assist in creating scenarios for in-class discussions.

I thought I was ready to ask ChatGPT to provide me with a research scenario for a psychological study that might or might not involve ethical issues. This is where my creativity and patience had to come into play as I moved forward. When I posted a simple prompt, ChatGPT provided one research scenario: The Effects of Virtual Reality Exposure on Social Anxiety. It included a description of a hypothetical research scenario, bullet points on the study's method, and potential ethical issues.

While this was a good starting point, it was not exactly what I was looking for in my in-class discussion groups. I wanted students to engage with a variety of scenarios and apply what they had learned in class to identify and discuss potential ethical issues, such as confidentiality, deception and bias. ChatGPT had provided a great example of one in-class discussion, but I wanted additional scenarios.

I decided to modify how I asked ChatGPT for these research scenarios. At this stage, I continued refining my questions and clarifying what I needed for the discussion scenarios. One example of these changes was adjusting the style and detail: shaping ChatGPT's responses to match the students' academic level and engagement needs. At the end of this process, I was provided with 10 research scenarios from different areas of psychology, all addressing potential ethical questions related to the intersection of technology and psychology. I also requested ChatGPT to provide support materials to help me effectively implement these scenarios in class, such as teaching instructions, student instructions, discussion questions, and rubrics. At the time of discovering how to use ChatGPT I was unaware of the use of “prompt engineering.” Prompt engineering prompts refer to the process of carefully designing and refining the questions or instructions to get more accurate, relevant, and useful responses. Good prompt engineering helps improve the quality of AI-generated content and reduces errors like hallucinations. My experience served as a valuable lesson.

Did I use everything ChatGPT provided? No. But I was able to modify the content it generated to better fit my specific course needs.

I have provided a broad overview and detailed the process of using ChatGPT; now, I will share examples that illustrate these details.

An Example of How I Generated a Scenario for my Course

One of the learning outcomes was for students to demonstrate an understanding of digital technologies and their applications in research. To achieve this, I wanted to create an in-class discussion on research methods and ethical considerations in studies where technology has been used. These discussions followed the lecture, allowing students to apply and engage with the content.

Let’s investigate each step in my use of ChatGPT. While using ChatGPT, I explored different components, as previously mentioned. First, I prompted ChatGPT with the following statement: Create 10 in-class discussion scenarios centered on hypothetical psychology research scenarios and potential ethical considerations in technology and psychology. After I identified the scenarios I would use, ChatGPT provided a title and project objective for the scenarios.

• Title: Exploring Research and Ethics in Technology and Psychology, along with the objective of the project: To critically examine the ethical considerations and challenges associated with conducting research involving technology in psychology.

I asked for instructions that would be helpful in setting up this assignment. ChatGPT provided Instructor Instructions that allowed me to modify the suggested layout for the group of students in my course. Here is my modified version of the Instructor Instructions.

1. Begin the class by providing a brief overview of the ethical principles and guidelines that govern research involving human participants, such as informed consent, confidentiality, and protection from harm.
2. Divide the class into small groups of 3-4 students.
3. Provide each group with a hypothetical research scenario involving the use of technology in psychology.
4. Instruct the groups to discuss the ethical considerations raised by the scenario, considering both potential benefits and risks to participants.
5. Encourage students to brainstorm possible solutions or strategies to address ethical concerns while maintaining the integrity of the research.
6. Allocate 20-30 minutes for group discussion.
7. After the discussion, each group will present a summary of their key ethical considerations and proposed solutions to the class.
8. Facilitate a whole-class discussion to explore common themes, differences in perspectives, and additional insights.

This provided ideas about how I might use the scenarios in the classroom. My initial plan was to randomly assign one scenario to each small group. However, during the class discussion, it became apparent that a few groups finished more quickly than others. For those who finished early, I allowed them to select another scenario to discuss. This approach gave students a broader understanding of ethics across diverse types of research scenarios.

ChatGPT provided 10 hypothetical research scenarios, and I selected five that related to anxiety, self-esteem, PTSD, cognitive development and eating disorders.

1. A study aims to investigate the effectiveness of a smartphone app in reducing symptoms of anxiety in college students. Participants will be asked to use the app daily for eight weeks and complete weekly surveys assessing their anxiety levels. The study is funded by the developer of the app.
2. Researchers plan to conduct an online survey to explore the relationship between social media use and self-esteem among adolescents. The survey will ask participants to disclose personal information, including their social media accounts and feelings of self-worth.
3. A psychology lab is conducting an experiment to examine the impact of virtual reality exposure therapy on individuals with post-traumatic stress disorder (PTSD). Participants will be immersed in virtual environments simulating traumatic experiences while their physiological responses are monitored.
4. A longitudinal study seeks to investigate the long-term effects of excessive screen time on cognitive development in children. Participants will be recruited from local schools and asked to complete cognitive assessments annually for five years, with data collected including hours of daily screen time and academic performance.
5. Researchers plan to conduct a cross-cultural study examining the impact of cultural factors on the manifestation and treatment of eating disorders. Participants from diverse cultural backgrounds will be recruited from multiple countries and asked to complete surveys assessing eating disorder symptoms, body image perceptions, and cultural attitudes towards food and body image.

The following are questions that ChatGPT provided for the in-class discussion and writing assignment on these scenarios.

1. Discuss the ethical considerations raised by the scenario, considering both potential benefits and risks to participants.
2. Brainstorm possible solutions or strategies to address ethical concerns while maintaining the integrity of the research.

ChatGPT also provided guidance on creating the rubric for this assignment. The rubric was designed to evaluate each student’s participation, understanding of the topic, depth of ethical analysis, the feasibility and effectiveness of the solutions, and the overall written reflection on the research scenarios. During the in-class discussion I visited each group and observed their discussion activity. I applied the additional aspects on this rubric to assess the written assignment based on the in-class discussions. I provided an example of the rubric that I adapted from ChatGPT.

As mentioned previously, I used ChatGPT to assist in organizing the written guidelines for this writing assignment.

Formatting Guidelines:

• Use Times New Roman font, size 12, and double-spacing.
• Ensure proper grammar, punctuation, and adherence to formatting guidelines.
• The assignment should be at least 2 pages.
• Use your own words to write up the paper- Generative AI should not be used, as discussed previously in the course.

Evaluation Criteria: Your assignment will be evaluated based on the following criteria:

• Participation in group discussions.
• Understanding the topic.
• Depth of your ethical analysis.
• The feasibility and effectiveness of their proposed solutions.
• Written reflection on the ethical considerations raised by the research scenarios and their implications for conducting ethical research in psychology.

Provided below is an example of one of the students’ written reflections of the in-class discussion assignment based on the previous questions (shared with her permission).

1. The first issue in this hypothetical research scenario is that the app’s developer funds the study. Thus, the study’s results may be biased and manipulated so that more consumers will use the app, and the company will have higher profits. Secondly, the participants in the study will be asked to give out private information, and it is not said who will have access to the college students’ anxiety levels and how this data can be used by researchers or the developer of the app. The last consideration relates to the app’s digital monitoring. More specifically, the scenario does not include any information about how the app works and who is monitoring it. For example, the app’s system could use AI to enhance user experience. In this case, the participants would have to know about the presence of AI in the app and how it stores and uses their private data for analysis.
2. The researchers could provide an informed consent form with information about what specific data will be collected through the app and who or what (for example, AI) will have access to their anxiety levels and other personal information provided through the app. There should also be a detailed description of possible risks of the app usage and a debriefing form where participants can find information on who to contact if their anxiety levels increase after the study to get assistance. The researchers could also check participants’ anxiety levels before the start of the study to have a basis for the analysis. Lastly, there should be more specifications on the amount of time the app should be used and during what time of day to keep the integrity of the research.

Additionally, I asked ChatGPT for student feedback questions regarding their experience. I did not include these questions in their assessment, but I used students’ feedback to modify future in-class discussions as needed. The questions were:

• How effectively did your group work together to discuss and analyze the project?
• What helped your group facilitate a productive and respectful discussion?
• How can your group improve collaboration and communication in future discussions?

Students reported that the assignment was effective and that they felt comfortable participating in their in-class discussion groups. For example, a student indicated that:

The discussion assignments were very pleasurable and helpful to engage with my classmates. I think discussions let us share our opinions regarding the topics and observe each other’s points of view. To me, it was the most fun and mind-opening activity.

In summary, this was my story of exploring the use of ChatGPT in creating classroom assignments. Through this journey, I discovered how generative AI can serve as a tool to enhance learning experiences, encourage critical thinking, and foster meaningful discussions among students. By using ChatGPT, I was able to design scenarios, create rubrics, and generate discussion questions that aligned with my course objectives. Using generative AI improved my creativity, clarity, and ability to develop in-class activities, which I previously found challenging. This experience also emphasized the importance of adapting and customizing AI-generated content to fit specific classroom needs.

Overall, using ChatGPT in my teaching not only enriched the classroom experience but also demonstrated how technology can be integrated into education in a thoughtful and impactful way. I look forward to continuing to explore its potential and sharing these experiences with others.

References

Adıgüzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology 15(3), ep429. https://doi.org/10.30935/cedtech/13152

Mollick, E., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. arXiv preprint arXiv:2306.10052. https://doi.org/10.48550/arXiv.2306.10052

Moundridou, M., Matzakos, N., & Doukakis, S. (2024). Generative AI tools as educators’ assistants: Designing and implementing inquiry-based lesson plans. Computers and Education: Artificial Intelligence, 7, Article 100277. https://doi.org/10.1016/j.caeai.2024.100277

Serena Zadoorian
University of California, Riverside

As a doctoral student, I am always eager to seek opportunities to teach courses. When I was hired to teach an introductory level research methods course at California State University, San Bernardino, I was extremely excited. This lower-division class has been designed to provide students with essential knowledge and skills to conduct and evaluate psychological research, which fosters critical thinking. The topics covered include the philosophy of science, scientific thinking and reasoning, correlation vs. causation, threats to validity, formulating testable research questions and hypotheses, basic concepts of research design, and research ethics. As I was preparing to teach this class, my goal was to ensure that, by the end of the semester, students not only had a comprehensive understanding of research but also demonstrated the ability to apply their knowledge to real-world scenarios. To facilitate this, I incorporated active learning assignments into the curriculum using the flipped classroom method. This method requires students to take responsibility for their learning both inside and outside of the classroom (Prust et al., 2015). Students are expected to engage with the course materials (e.g., recorded lecture videos, chapter readings, quizzes, etc.) prior to class session with minimal support from the instructor. Then, during class hours, students are presented with class activities and discussion to strengthen their understanding of the learning materials (see Al-Samarraie et al., 2020).

The flipped classroom method offers many benefits over the traditional lecture, such as: reviewing the course materials at one's own pace and as many times as needed (Goodwin & Miller, 2013); watching lecture segments individually at the most convenient times (Forsey et al., 2013; Jensen, 2011); and engaging in active learning during class (Daniel & Braasch, 2013; Freeman et al., 2014; Karpiak, 2011). It is important to note that in addition to the benefits, there are also potential drawbacks to consider. For instance, students may find the pre-recorded lecture materials less engaging (Jensen, 2011; Foertsch et al., 2002) or encounter technical difficulties when viewing the materials (especially those with fewer financial or technical resources). Lastly, some students may also face challenges upon anticipating, scheduling, and completing the out-of-class learning (see Dunning et al., 2003).

Flipped Classroom in Action

In a study conducted by Roehling and colleagues (2017) flipped pedagogy was used in an Introduction to Psychology course at a small liberal arts college. The instructors selected four topics, including research methods, to be flipped. Their results revealed that students found the flipped classroom method more interesting than the traditional one. Previous research has also shown that the flipped classroom method could enhance students’ metacognition (Van Vliet et al., 2015) and promote students’ engagement and self-efficacy (see Esson, 2016). Taking these results into account, this method was utilized when teaching my lower-division research method class at CSU San Bernardino. The particular flipped model employed was developed by me, and it was my first time applying it in the classroom.

The class consisted of a total of 38 students, all of whom utilized materials from PsycLearn—a digital resource provided by the American Psychological Association. Students were instructed to review the course materials prior to the class session within a period of five days. PsycLearn enables students to complete each chapter section by section, which makes it easy to navigate through the modules. Each module consists of reading materials, video lectures, and assessments (e.g., quizzes, short-answer questions) with immediate feedback. Additionally, for each chapter, real-world scenarios are included to allow students to apply psychological science to real life. For example, when learning about reliability, students were presented with scenario-based examples that demonstrated how researchers collect and analyze data. They were then required to match each type of reliability with the appropriate scenario.

In addition to completing the online modules, students were asked to post a question related to the course materials and reply to another students’ post on the Canvas discussion board. Pre-class activities took about one and a half to two hours per week. To reward students for their progress, they earned points for completing the online modules and posting questions. Although the majority of students found the class structure easy to follow and said that they benefited from the discussions, some noted in the end-of-year evaluations that the course was time-consuming. Specifically, these students found it challenging to allocate time outside of class to review the course materials.

The in-class materials were presented through PowerPoint slides and focused on the concepts students found most challenging, as reflected in the questions raised on the discussion board. It is important to note that the concepts students find challenging may vary between classes. For this reason, faculty will likely need to adjust the slides to better address these challenges based on the needs of each group. This research methods class met twice a week, with the first day dedicated to reviewing the course materials and encouraging students to ask questions. During the second day, we focused on collaborative work. Students were randomly placed in groups of 4 to 5 to work on active learning assignments designed to help them apply their knowledge to real-world scenarios. For instance, when teaching about ethical guidelines, students were given various research proposals and asked to act as members of the Institutional Review Board committee, deciding whether to approve, reject, or request additional supporting documents form the “researchers.” This activity not only enhanced students’ engagement but it also allowed them to put their knowledge into practice. Furthermore, as part of the course requirement, students were asked to learn about APA formatting. To help them better understand APA style, students were provided with texts that included both in-text citations and references. They were instructed to identify any APA style errors (if present) and provide explanations on how to correct those errors. Although students were asked to work in groups, they were required to submit their own work after each class session.

Students were assigned to the same group for the entire semester. This approach was implemented to facilitate communication and encourage students to collaborate more efficiently. To enhance their learning experience, I actively moved around the classroom, checking in with each group to ensure they were progressing in the right direction. For active learning assignments involving challenging concepts, we reviewed the answers as a class. Reviewing assignments as a class provided students with additional support, reinforcing key concepts. Each week, assignments were submitted via Canvas and graded within five days and returned with constructive feedback. Students were invited to attend office hours to ask any additional questions or for support. It is important to note that if a student was absent for a valid reason, they were granted an extension to complete the assignment independently, with the opportunity to receive guidance and support from the instructor as necessary. Finally, it is important to emphasize that this class does not require a final research paper or proposal. Students majoring in psychology at CSU San Bernardino are mandated to enroll in an upper-division methods course that primarily focuses on writing research papers and proposals. Considering the importance of mastering APA format and the critical steps in writing papers and proposals, I believe the flipped classroom method may not be the best approach. Students may find it challenging and discouraging without a solid foundation. It is essential for students to learn how to write research papers through traditional classroom methods, as academic writing is crucial for success in many upper-division courses and for those pursuing graduate school.

Conclusions

As a faculty, I tend to create a cooperative student-faculty environment in the classroom. Teaching a diverse group of students during my graduate career has made me aware of the importance of creating a supportive learning environment to ensure inclusivity for diverse learners. As shown by previous research, the flipped classroom method has been shown to improve students’ metacognition and promote engagement. Given the lower-division research methods class at CSU San Bernardino, I noticed that students who typically refrained from asking questions during discussion time were actively engaged and communicative with their peers during the active learning assignments.

Furthermore, the flipped method also provides instructors with more time to address questions during class and allows them to integrate active learning assignments, giving students the opportunity to apply the concepts they have learned to real-world scenarios. In the end-of-year evaluations, students described the class as highly engaging and informative, noting that the class activities were both captivating and enjoyable. Moving forward, my next steps include maintaining the same class structure and curriculum as outlined. However, I also aim to gain deeper insights into students’ prior experiences and preferences regarding flipped vs. traditional classrooms. Collecting these data at the beginning of the semester will enable me to better understand my students’ backgrounds and needs and will help me tailor my teaching strategies to align with my students’ preferences.

References

Al-Samarraie, H., Shamsuddin, A., & Alzahrani, A. I. (2020). A flipped classroom model in higher education: a review of the evidence across disciplines. Educational Technology Research and Development, 68(3), 1017-1051.

Daniel, F., & Braasch, J. L. (2013). Application exercises improve transfer of statistical knowledge in real-world situations. Teaching of Psychology, 40(3), 200-207.

Dunning, D., Johnson, K., Ehrlinger, J., & Kruger, J. (2003). Why people fail to recognize their own incompetence. Current Directions in Psychological Science, 12(3), 83-87.

Esson, J. M. (2016). Flipping general and analytical chemistry at a primarily undergraduate institution. In The flipped classroom Volume 2: Results from practice (pp. 107-125). American Chemical Society.

Foertsch, J., Moses, G., Strikwerda, J., & Litzkow, M. (2002). Reversing the lecture/homework paradigm using eTEACH® web‐based streaming video software. Journal of Engineering Education, 91(3), 267-274.

Forsey, M., Low, M., & Glance, D. (2013). Flipping the sociology classroom: Towards a practice of online pedagogy. Journal of Sociology, 49(4), 471-485.

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410-8415.

Goodwin, B., & Miller, K. (2013). Research says/evidence on flipped classrooms is still coming in. Educational Leadership, 70.

Jensen, S. A. (2011). In-class versus online video lectures: Similar learning outcomes, but a preference for in-class. Teaching of Psychology, 38(4), 298-302.

Karpiak, C. P. (2011). Assessment of problem-based learning in the undergraduate statistics course. Teaching of Psychology, 38(4), 251-254.

Prust, C. J., Kelnhofer, R. W., & Petersen, O. G. (2015, June). The flipped classroom: It's (still) all about engagement. In 2015 ASEE Annual Conference & Exposition (pp. 26-1534).

Roehling, P. V., Root Luna, L. M., Richie, F. J., & Shaughnessy, J. J. (2017). The benefits, drawbacks, and challenges of using the flipped classroom in an introduction to psychology course. Teaching of Psychology, 44(3), 183-192.

Van Vliet, E. A., Winnips, J. C., & Brouwer, N. (2015). Flipped-class pedagogy enhances student metacognition and collaborative-learning strategies in higher education but effect does not persist. CBE—Life Sciences Education, 14(3), ar26.

Shlomit Flaisher-Grinberg
Saint Francis University

Background:

As a behavioral neuroscientist, I always loved rats. I have seen them master complicated cognitive tasks and wanted my students to have the opportunity to learn, first-hand, just how social, clean, and clever they really are. Thus, I was thrilled when my department chair asked me to teach the “Psychology of Learning” course. Integrating rat-training experiences into the curriculum, my students used learning methodologies to teach their rats to “play soccer,” ride tiny scooters, and complete agility courses, among other tasks. During the semester, my students also learned to care for their rats, and many grew to love them. In fact, many students decided to adopt their rats at the end of the semester.

The Transformation:

Even though the course was effective, and students’ feedback was positive, there was always this one nagging thought I couldn’t get rid of. I was breeding (or purchasing) rats for the course, while animal shelters were overloaded with abandoned, neglected, abused, and betrayed animals. Having created an upper-level shelter dog-training program a few years ago (Flaisher-Grinberg, 2023), and knowing that every year, more than 3 million cats enter animal shelters worldwide (American Society for the Prevention of Cruelty to Animals, n.d.), I wondered if I could replace the course’s focus on rat training with shelter cat training. I assumed that like the training of rats, the training of cats (and assessment of the training efficacy) will contribute to students’ working knowledge of psychology and enhance their scientific reasoning skills. I envisioned that unlike the training of rats, the training of shelter cats would provide students with an opportunity to apply psychological content to practical, ‘real-world’ problems and empower them to make a difference in their lives and in their communities (American Psychological Association, 2022). Specifically, I wanted my students to use learning concepts to socialize shelter cats and train them towards behaviors that could advance their wellbeing and adoptability (Kogan et al., 2017). I hoped that the ability to improve the quality of lives of shelter cats, while supporting animal shelters in their effort to care for sheltered animals, will also promote my students’ personal and professional development, and therefore produce an impact that will span people and animals alike.

Course Set-Up:

My first step into the transition included the creation of a partnership with a local animal shelter, which was willing to entrust us with their cats and agreed to support the program by providing some of the cats’ needs (crates, blankets, litter boxes, litter, toys, and food). This task was easy, given that we have previously established a reciprocal and mutually beneficial collaboration with one of the animal shelters around us, centered around my students’ efforts to train shelter dogs and write grant applications on behalf of the shelter. Next, I secured permission to house shelter cats on campus premises and attained relevant protocols. This task was more complicated and took almost a year to conquer. Specifically, I worked with our Business Office to ensure insurance coverage for our course, with our Office of Risk Management to create appropriate liability agreement documents, with the Students Health Center to generate allergy screening/management procedures, and with the Biology Department to identify a classroom appropriate for the course. I submitted detailed care protocols to our Institutional Animal Care and Use Committee, and an internal grant application ($1,000) to our Office of Advancement. The grant allowed me to purchase cats’ carriers, leash/harness kits, click sticks, “place” mats, and training treats. Later, I was able to sustain the program financially via the addition of minor lab fees to students’ course enrollment ($20/student). Given that my institution has a small vivarium, I was able to transform the rats’ space into a cat-dedicated room, supplied with cat trees, hiding boxes, and toys. Finally, I recruited a group of TAs, trusted with cleaning/feeding protocols (for additional information about the course, see Flaisher-Grinberg, 2024).

Course Delivery:

The integration of cats into the curriculum was accomplished via a variety of classroom activities, four lab sessions, and a 3-part research assignment. The labs focused on the demonstration of 1) habituation processes, 2) classical conditioning, 3) operant conditioning, 4) generalization and discrimination procedures, and the research assignment was built around a student-generated cat training project. During the labs (and the following weeks) students learned to gently handle the cats, respect their personalities, and interact with them in a way that enabled both cats and students to calm down and enjoy each other’s company. The cats learned that the carriers, “place” mats, click sticks and harnesses predicted the availability of treats, and later, that entering the carriers, sitting on the “place” mats, following the click sticks, or wearing the harnesses, awarded them with treats. Concurrently, the TA team utilized similar methodologies to facilitate cats’ nails trimming, ears cleaning, and teeth brushing. Since many cats associate their carriers with aversive consequences (e.g., a visit to the vet), are wary of wearing a harness (even if for a nice walk outdoors), and despise being groomed, I hoped that these tasks will be beneficial to both the cats and their future adopters. With the intent of introducing my students to the growing field of animal-assisted interventions (e.g., the incorporation of animals into human-oriented therapeutic/educational processes, Fine & Weaver, 2018), the final lab session took place within the institutions’ clinical educational facility set as a simulated hospital. During the lab, the cats generalized previously learned tasks, demonstrated via their ability to walk in a harness into the medical environment, sit on their “place” mats by “mock patients”, follow the click stick to execute entertaining tricks, and spread love and happiness all around. For their research assignments, students selected a research question (“Can a cat learn to…?”), designed a training methodology, chose assessment parameters (e.g., latency to complete the task, number of correct responses, etc.) that were evaluated before and after the training, collected and analyzed the data, wrote an APA-style research paper describing their project, and disseminated their findings to their classmate via a 10-minute presentation.

Findings:

The course, in its shelter-cats-integrated format, was offered for the first time in the spring of 2023. It was repeated in the spring of 2024 and will be offered again in the spring of 2025. Set as a mandatory curricular item for psychology majors and an elective for students in other majors, the course is well-enrolled, attracting students with interest in health sciences, biological sciences, and a variety of other disciplines. Each iteration thus far included 40-48 students (across two sections), and six cats. Depending on the cat’s needs and personality (e.g., outgoing or shy), each cat was assigned to one or two students’ groups of 3-4 students per group. This structure seems suitable, as students’ and cats’ number accommodate the size of the classroom/cat-room, and since in this fashion the cats receive adequate (yet not overwhelming) attention and students are able to coordinate their training time with their group members to maximize the efficiency of their work. Although protocols allow students with allergies to substitute the course for another alternative within the department’s curriculum, to date, none of the students who took the course had severe cat allergies, and the three that had minor allergies chose to enroll in the course while complying with safety regulations (i.e., wearing lab coats, gloves, and face masks during their interactions with the cats). Most of the cats learned most of the tasks (some cats dislike walking in a harness, while some seem to like it), and students were able to design research projects that involved a variety of tasks (giving a ‘high five’, “playing soccer”, etc.). The students indicate that they truly like their cats, enjoy training them, and are proud of both their cats’ and their own accomplishments throughout the semester. Students attest that they recognize the positive impact that they make on shelter cats and on the local community and that they feel that the course contributes to their educational, professional, and personal development. Representatives of our shelter partner indicate that they are thrilled with the partnership and desire to see it continue and develop in the future. Various faculty, staff, and administrators also enjoy the presence of cats on campus, and I often find myself engaging in conversations about our cats and about pets and animals in general. Importantly, regardless of age, sex, behavioral tendencies, and health status, the cats seem to prosper in the campus environment. Moreover, up to date, all cats in the program have been successfully adopted by their student trainers, other students in the course, campus community and the general community.

New Directions:

Given the popularity of the cats-integrated course, the success of the collaboration with our local animal shelter, and the cats’ high adoption ratio, the fall of 2024 marked the beginning of a new, shelter-cats-integrated program. In the past few months, we identified a small room at the campus library that did not contribute to the air circulation within the library, received all necessary permissions, gathered equipment, and brought shelter cats to live in our own “Library Cat Room.” I trained a team of eight students who previously took my cat-focused course to clean, feed, and socialize the cats, and created ‘meet-n-greet’ sessions (3-4 hours/week) which enabled the campus community to spend time with the cats (the cats are not allowed outside the room). Although the program is very new, the three cats that spent the past few months living in our library environment have already brought much joy to students, faculty, staff and administration. All of them were successfully adopted by the end of the fall semester, and it is our hope that our program will continue and develop in future years.

References:

American Psychological Association (2022). APA guidelines for the undergraduate psychology major. Version 3.0. APA. www.apa.org/ed/precollege/about/psymajor-guidelines.pdf

American Society for the Prevention of Cruelty to Animals (n.d.). Pet Statistics. Retrieved January 31, 2023, from https://www.aspca.org/helping-people-pets/shelter-intake-and-surrender/pet-statistics

Fine, A. H., & Weaver, S. J. (2018). The human-animal bond and animal-assisted intervention. In M. V. D. Bosch, & W. Bird (Eds.), Oxford textbook of nature and public health: The role of nature in improving the health of a population (pp. 132-138). Oxford University Press.

Flaisher-Grinberg, S. (2023). Community-Engaged Pedagogy in the Psychology Classroom: Shelter Dogs go to College. Teaching of Psychology, 0(0). https://doi.org/10.1177/00986283231191748

Flaisher-Grinberg, S. (2024). Creating a College-Based Shelter Cats’ Training Program. Journal of the International Association of Animal Behavior Consultants, IAABC. 29(1). Retrieved from: https://journal.iaabcfoundation.org/sfu-cats/

Kogan, L., Kolus, C., & Schoenfeld-Tacher, R. (2017). Assessment of Clicker Training for Shelter Cats. Animals, 7(10), 73. https://doi.org/10.3390/ani7100073

Chelsea Romney
Brigham Young University

While attending a teaching seminar at my university on the importance of experiential learning,(1,2) I found myself experiencing academic discipline FOMO (fear of missing out). A dance professor explained, “Instead of having students learn the steps of the cha-cha from their textbook, we use our classroom time to actually dance the cha-cha.” I thought to myself, if only I were in a discipline that lent itself so well to experiential learning. How could I possibly demonstrate concepts like bias, group dynamics, or social cognition in my upcoming social psychology course? Surely, such erudite concepts weren’t meant for experiential learning methods. 

Later, as I was preparing a lecture on the “Psychology of Law” chapter of the course textbook, I realized that I might have discovered my own version of the cha-cha. I began developing a plan for students to view live courtroom proceedings to see how social psychology influences the practice of law. I knew that court was a public place that could be visited by civilians, and that all arraignments and trials were public records. However, we know from community-based participatory research (CBPR) that groups, especially academic groups, should take care when visiting or studying community organizations to respect the functioning of the organization. Proper CBPR involves an equitable approach where both the academic group and the community stakeholders both benefit from the interactions. (3) 

I met with the local city justice court judge to determine how they might benefit from having students observe court. Fortunately, the judge was enthusiastic about having students in the court and was particularly motivated by the idea of collecting data to determine how the court was functioning. Specifically, the judge had already used a validated national court survey(4) to assess the accessibility and fairness of the court from the customers’ perspective and was enthusiastic at the idea of students from the local university assisting in the collection of a new batch of these surveys. Since another learning outcome of the course was to increase the students’ understanding of the research process, collecting data for the court created an additional opportunity for experiential learning in my class. 

The judge and I worked together to determine a series of interactions, assignments, and specific statistical associations we wanted to assess in the outcomes of the validated survey to mutually benefit our organizations. The course courtroom assignment followed this timeline: 

1. The judge visited our classroom, provided a guest lecture related to course material, described the purpose of the validated court survey, and provided information about proper conduct while visiting the court.

2. 25 students visited the courtroom in pairs of two to collect data throughout the semester. During their court visit, they also completed a courtroom observation assignment where they identified at least three social psychological phenomena occurring in the court in a 2-page paper. This encouraged them to think critically about course concepts and gave their visit structure when they weren’t collecting data.

3. With instruction, students completed data analyses with the data collected from the validated survey and wrote brief research papers on their findings for course credit.

4. The Judge visited the classroom again for the students to deliver their findings in the form of oral presentations that were graded as part of the course.

Students reported how observing court in person and engaging with court customers and employees improved their understanding of course concepts. One student wrote,

“I was able to understand the social psychology vocabulary much better because I could see at the court different concepts like emotional intelligence, intrinsic and extrinsic motivation in the court customers, receptivity, yielding (William McGuire’s model of persuasion), and stigma.”

Another student made sense of course concepts through observing the Judge,

“The biggest social psychological principle that I was able to see while watching the Judge’s court was his high emotional intelligence. The book breaks up emotional intelligence into four different parts. The first was the ability to perceive your emotions and the emotions of those around you. This was definitely something that was practiced by the Judge as he was able to recognize the way that others felt and how his emotions were influencing his judgements. To have awareness of how others feel is a great quality to have in the court system because how people feel influences the way that people perceive fairness and furthermore their actions after the court hearing. The second type of emotional intelligence is facilitating thought which is described as the ability to generate an emotion and then regulate that emotion. The third is understanding emotion which explains that a person is able to acknowledge an emotion and recognize when that emotion switches from a simple emotion to a complex emotion. The last type of emotional regulation is called managing emotions which explains that an individual is open to theirs and others emotions and they are able to understand them, along with being able to grow and develop because of them. I saw the Judge demonstrate each portion of emotional intelligence in his courtroom and that is one of the reasons why so many court customers perceive him as fair.”

Due to the experiential nature of the courtroom project, students also gained additional insights beyond the course assignments. One student shared their initial apprehension about the court environment, stating,

“I had a lot of preconceived notions about court even though I had never been to a court before in real life. I thought the layout made it easy for people to learn observationally because they are seated in the courtroom until it is their turn to speak. I liked this composition because I feel like it helped them know what to say.”

Another student noted,

“While spending time at the court, I was surprised that the people who worked there were normal people. They even laughed and talked and joked around with each other. I wished that other people got to see the human side of the judge, the cops, and the staff who work in the court and not as people who want to give you the harshest sentence that they can.”

And lastly, students learned about human nature and increased their awareness of the  complexity of human behavior. One student reflected,

“While at court, I saw a case where a son was trying to protect his mother from a violent ex-boyfriend by hitting the man with a skateboard. He was charged with very heavy charges. Through previous meetings and litigation between the Judge and the attorney, they ended up dropping the charges and allowed him to pay a fine of $100 and he got his bail money back. I saw the family hugging and crying in the parking lot. I was very touched by this experience that sometimes people may commit crimes to protect others.”

Since the courtroom assignment, I have applied the principles of community-based participatory research as a base for experiential learning assignments for other courses. Recently, I taught a Health Psychology course with an emphasis on the health benefits of social inclusion. I targeted on campus clubs as an effective venue to study student social engagement. I followed the lead of the stakeholder, the overall campus clubs staff coordinator, to design an assignment that would benefit both the students and the campus clubs. Like the judge, the clubs coordinator was also interested in data to understand how the clubs were functioning. Students selected clubs and administered surveys to assess the effect of club attendance on outcomes like well-being, happiness, and belonging. The assignments followed a similar pattern as the courtroom study with a guest lecture from the clubs coordinator, instruction on research methods, data collection, and a final presentation to the stakeholder. I believe this format could be applied to courses that cover other types of content and I plan to implement a similar project in my Psychological Statistics course.

In conclusion, incorporating community or campus engagement into the classroom provides invaluable experiential learning opportunities for students, fostering a deeper understanding of academic concepts through real-world application. By engaging with community stakeholders, such as local courts or campus clubs, students not only gain practical experience but also contribute to the community, creating a mutually beneficial relationship. These experiences challenge students' preconceived notions, enhance their critical thinking, and provide them with a nuanced perspective on human behavior and social dynamics. Ultimately, integrating experiential learning through community or campus engagement enriches the educational experience, promoting both academic growth and social responsibility, and you don’t even have to dance the cha-cha in front of your students.  

References

1 Kuh, G. D. (2012). High-impact educational practices: What they are, who has access to them, and why they matter. Peer Review, 14(3), 29-30.

2 Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. New Jersey: Prentice-Hall.

3 Fontaine, S. (2006). Journal of Higher Education Outreach and Engagement, 11(2), 45.

4 https://www.ncsc.org/courtools/trial-court-performance-measures

Dina Gohar
University of Michigan-Ann Arbor

People with a growth mindset—the belief that intelligence and other abilities can develop through effort—enjoy numerous benefits inside and outside of the classroom (Dweck, 2006, 2017). For example, students with a growth mindset are more likely to persist when challenged and to succeed in college with higher grades and course completion rates (Yaeger at al., 2019), and even enjoy greater well-being overall (Tao et al., 2022). A growth mindset can be particularly beneficial for students from historically underrepresented or marginalized groups who are likely to face systemic barriers, such as those related to race, socioeconomic status (SES), or first-generation status (Fink et al., 2018). Such students often encounter additional hurdles that can impact their educational journey, from stereotypes to limited resources, which a growth mindset can help them be resilient enough to overcome. For example, an online intervention encouraging high school students to view intellectual abilities as capable of growth through effort, new strategies, and seeking help significantly improved grades among lower-achieving students, especially when the school environment aligned with the growth mindset message (Yaeger et al., 2019).

However, a growth mindset is NOT a panacea, and not having one is far from the only reason why marginalized students may struggle academically. Overemphasis on individual effort might obscure structural and systemic factors that impact student success, such as discrimination and limited resources. Although many studies suggest that those who are marginalized or from low SES may benefit most from adopting a growth mindset, some studies suggest the opposite (Sisk et al., 2018). For example, Bernardo (2020) found that a growth mindset was positively related to learning outcomes only among higher SES students, highlighting the importance of social resources supporting students’ efforts to improve for the benefits of their growth mindset to be realized. How do we ensure these interventions are successful for the students who stand to benefit from them the most?

Growth mindset interventions can sometimes backfire for disadvantaged students if not implemented carefully enough to avoid encouraging self-blame or shame for failure. As Hoyt and Burnette’s (2020) “double-edged sword model” highlights, growth mindset messaging can not only yield positive outcomes due to increased self-efficacy (and reduced social essentialism), but also indirectly predict adverse outcomes due to more self-blame and adopting personal responsibility for problems. Therefore, in stigmatizing contexts and in isolation, differentiating responsibility for a problem from expectations for potentially managing the problem is integral for positive growth mindset-related outcomes. For instance, frame marginalized students’ academic difficulties within broader societal contexts. Instead of saying "Your grade is a result of your effort,” you could say “Your grade reflects your current performance, which can be negatively impacted by systemic inequalities that we can hopefully address together.” Rather than saying “if you work harder, you will improve,” acknowledge that “improvement often requires both effort and support. Let's explore the resources available to you, such as tutoring services, my office hours, and study groups, that can complement your hard work so it is reflected in your final grade.”

In addition to promoting a growth mindset in our students without encouraging self-blame or false hope, we should discuss and actively address systemic barriers that can affect their performance to the best of our ability. We can truly empower our students by providing the resources they need to reap the benefits of a growth mindset while advocating for structural changes that support all students.

Your Course Syllabus Can Cultivate A Growth Mindset

As educators, we have the power to cultivate a growth mindset in our students without encouraging self-blame for failure, which can facilitate their resilience and success. How can we do so through small changes in our classes so that we don’t burn ourselves out? My online experiment (N = 200) suggests that an easy way to cultivate a growth mindset in the classroom, whether online or in person, is through our course syllabus as the first point of contact with our students. Compared to those randomly assigned to read a conventional syllabus, students who read a growth mindset-based syllabus scored significantly higher on Dweck’s Growth Mindset Scale afterward (Gohar, 2024). Moreover, students perceived a typically dreaded Research Methods course and its instructor more positively if the syllabus was growth-mindset oriented, much like students perceive a course and its instructor more positively if the syllabus is detailed (Saville et al., 2010), learner-centered (Richmond et al., 2016), inclusive (Fuentes et al., 2020), and warm in tone (Gurung & Galardi, 2021). More specifically, students reported more desire to take and less anxiety about a growth-mindset based course, which was perceived as less challenging, too. This was especially the case for students who identified as female or lower income, who even expected higher grades in the growth-mindset based course–perhaps helping to mitigate stereotype threat. Students also perceived the growth-mindset based instructor as more qualified, reasonable, and nice, which is an added bonus.

So, what does a growth-mindset based syllabus look like? Using language that emphasizes the potential for growth when describing your learning outcomes (e.g., “grow in your ability to think critically”), assignments, and course (e.g., “This course is challenging, but I truly believe that every student is capable of succeeding with enough effort and persistence, and it is my job to help everyone do well!”). I even include an explicit message that, “studies suggest that the more you challenge yourself to learn, the more your brain actually grows! So, even difficult things like learning how to do research and statistics get easier as you get smarter over time,” which I highly recommend doing at least for research methods and statistics courses that can cause math anxiety and stereotype threat (Luo & Chen, 2024).

It is not enough to use growth mindset facilitating language in your syllabus, though. Your course design needs to reflect growth mindset practices to show students that you really mean it. it can be hard for students to adopt and sustain a growth mindset if they don’t have the chance to make mistakes without hurting their final grades. Therefore, it is critical to use recursive assessment and grading that actually rewards students’ effort and improvement as well as their performance whenever possible. For example, students can earn an “effort score” that is incorporated into their final grades on assignments, as described in the figure below.

Click here for a link to a copy of the post with figures.

If you want to make sure that your students actually read the Syllabus that you put so much time into, at the beginning of the course, you can have them annotate the syllabus with their questions or comments as a graded assignment, which I highly recommend.

More Tips for Cultivating a Growth Mindset in Your Students

How else can you help your students develop a growth mindset to reap the benefits while avoiding potential pitfalls? First, if you tend to believe that ability is fixed (you can find out by taking the short linked Mindset Quiz), work on cultivating more of a growth mindset yourself because your mindset can impact your students’ mindset and thus their performance. For example, STEM faculty with a fixed mindset inspire less student motivation and have larger racial achievement gaps in their classes (Canning et al., 2019). For maximal benefit, students’ growth mindsets must also be supported by their teacher’s own growth mindsets (Yaeger et al., 2022), and ideally, peer norms, which can be influenced by teachers. Model a growth mindset for your students by sharing your mistakes and struggles and how you learned from or overcame them for inspiration.

Second, praising effort and process, rather than performance or ability, can effectively foster a growth mindset and improve student performance, especially after setbacks (Mueller & Dweck, 1998). For example, instead of saying things like "you're a really great writer,” say something like "I can tell you put a lot of thought into this paper." Rather than just praising students for performing well, thank them for the hard work they put into the assignment, highlighting the connection between invested effort and improved performance if relevant. Third, it can be helpful to normalize struggle and “failure” as part of learning and emphasize the opportunity for growth, especially in the face of adversity, which can even facilitate post-traumatic growth beyond pre-trauma levels (Tedeschi & Calhoun, 2004). Simply reminding students that “everyone makes mistakes” can go a long way to normalize them. However, remember to acknowledge the barriers faced by disadvantaged students to prevent them from blaming themselves for struggling and work to address those barriers whenever possible.

Fourth, help your students develop self-compassion, especially if they tend to be overly self-critical when they make mistakes. Neff’s website, selfcompassion.org, has great free exercises for cultivating more self-compassion. Encourage your students to review their mistakes in a nonjudgemental fashion and to learn from them by rewarding their doing so. Fifth, students can be instructed to say “stop” and breathe when their fixed mindset voice is getting out of hand and to add “yet” to the end of their fixed mindset statements to reap the benefits (e.g., “I can’t do this… YET!”). Finally, remember that a growth mindset isn’t about having “positive thoughts only” but about embracing challenges and learning from our mistakes because we believe in our capacity to improve.

Best of luck as you carefully nurture a growth mindset in your students and empower them to achieve success inside and outside of the classroom as lifelong learners!

References

Bernardo, A. B. I. (2020). Social dominance goals, perceived socioeconomic status, and the academic achievement of Filipino students. Journal of Applied Social Psychology, 50(5), 269-282.

Canning, E. A., Muenks, K., Green, D. J., & Murphy, M. C. (2019). STEM faculty who believe ability is fixed have larger racial achievement gaps and inspire less student motivation in their classes. Science Advances, 5(2), eaau4734. doi: 10.1126/sciadv.aau4734

Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.

Dweck, C. (2014, November). The power of believing that you can improve [Video]. TED Conferences.

Dweck C.S. (2017). Mindset: Changing the Way You Think to Fulfill Your Potential . Little Brown Book Group.

Fink, A., Cahill, M. J., McDaniel, M. A., Hoffman, A., & Frey, R. F. (2018). Improving general chemistry performance through a growth mindset intervention: Selective effects on underrepresented minorities. Chemistry Education Research and Practice, 19(3), 783-806. https://doi.org/10.1039/C7RP00244K

Fuentes, M. A., Zelaya, D. G., & Madsen, J. W. (2020). Rethinking the course syllabus: Considerations for promoting equity, diversity, and inclusion. Teaching of Psychology, 48(1), 69-79.

Gohar, D. (2024). A growth mindset-based syllabus improves students’ perceptions of taking and succeeding in research methods. Manuscript in preparation.

Gurung, R. A. R., & Galardi, N. R. (2021). Syllabus tone, more than mental health statements, influence intentions to seek help. Teaching of Psychology, 49(1), 32-37.

Hoyt, C. L., & Burnette, J. L. (2020). Growth mindset messaging in stigma-relevant contexts: A double-edged sword? Journal of Social Issues, 76(3), 645-667.

Luo, Y., & Chen, X. (2024). The impact of math-gender stereotypes on students' academic performance: Evidence from China. Journal of Intelligence, 12(8), 75. https://doi.org/10.3390/jintelligence12080075

Mueller, C. M., & Dweck, C. S. (1998). Praise for intelligence can undermine children's motivation and performance. Journal of Personality and Social Psychology, 75(1), 33-52.

Richmond, A. S., Slattery, J. M., Mitchell, N., Morgan, R. K., & Becknell, J. (2016). Can a learner-centered syllabus change students' perceptions of student–professor rapport and master teacher behaviors? Scholarship of Teaching and Learning in Psychology, 2(3), 159-168.

Saville, B. K., Zinn, T. E., Brown, A. R., & Marchuk, K. A. (2010). Syllabus detail and students' perceptions of teacher effectiveness. Teaching of Psychology, 37(3), 186-189.

Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological Science, 29(4), 549-571.

Tao, V. Y. K., Li, Y., & Wu, A. M. S. (2022). Growth mindset and psychological well-being: The mediating role of personal growth initiative and self-efficacy. Journal of Happiness Studies, 23(3), 1187-1203.

Tedeschi, R. G., & Calhoun, L. G. (2004). Posttraumatic growth: Conceptual foundations and empirical evidence. Psychological Inquiry, 15(1), 1-18.

Yeager, D. S., Carroll, J. M., Buontempo, J., Cimpian, A., Woody, S., Crosnoe, R., ... & Dweck, C. S. (2022). Teacher mindsets help explain where a growth-mindset intervention does and doesn't work. Psychological Science, 33(1), 18-32.

Yeager, D. S., Hanselman, P., Walton, G. M., Murray, J. S., Crosnoe, R., Muller, C., ... & Dweck, C. S. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573(7774), 364-369.

Jennifer Samson
Queens University of Charlotte

I love teaching Research Methods. When I accepted my present position, I enthusiastically agreed that this would be my primary teaching responsibility. (I think they might have expected me to run away screaming instead.) Our year-long methods sequence is relatively unique in that every year, my 25 or so students propose, design, implement, and report on their own projects in any area of Psychology. Every year there are some unbelievably thoughtful, creative, and interesting projects. But also every year, I have to drag myself through grading the drafts. Even the “good” projects. Especially when I feel like I’m providing the same feedback on draft after draft with little to no improvement.

How can we help students understand the writing process as iterative instead of “one [draft] and done”? How can we as instructors help students become effective critics of their own writing? How can we keep our grading load manageable and still provide students with the feedback they need? This essay describes trials and errors, lessons learned, and lessons I’m still learning in my search for the elusive answers to these questions.

Spoiler: There’s not one easy solution.

Background:

The year-long research methods sequence I teach is required for all Psychology majors in their junior year at my small, liberal arts university. By the time they get to me, students have completed their first-year writing sequence as well as the specific course prerequisites, including Introduction to Psychology, Statistics and a class we call Information Literacy – reading and writing in a professional Psychology setting, including a focus on literature review. Ultimately, the majority of my students are relatively well-prepared for college-level work but are still learning to write the type of professional academic paper required for the course. It is also worth noting that a sizable minority every year take Information Literacy simultaneously with the fall semester of Methods and so need extra support in my course.

The research methods sequence is centered around students’ individual empirical projects. In the fall, students complete a four-credit class where we delve into the study of research, emphasizing design for association versus cause/effect and critiquing for different types of validity (designing and critiquing research is an explicit goal for undergraduate students set out by the American Psychological Association, APA, 2023). Concurrently with the class, they complete a two-credit-hour lab where they write a proposal to identify a research question and propose methods to answer it. In the spring, students complete a second four-credit class where they collect data, analyze it, and revise/extend their proposal so it becomes a complete, journal-style empirical paper. They also present their work in a poster session at a local undergraduate conference. The completion of not only the proposal but the entire project and the opportunity for every student to present in a conference setting is a hallmark of our program.

What I Tried:

At the beginning of last academic year, I knew I needed to do something different. An influx of late transfers caused the class size to swell by almost a third, and I knew that, short of learning to clone myself, there was no way I could keep up with marking everyone’s drafts in a timely manner (see Ambrose et al. 2010, about importance of constructive, timely feedback for student motivation). Meanwhile, I had already been looking at ways to increase student buy-in for writing as an iterative process and to increase students’ meta-cognitive skills as evaluators of their own work (see Ambrose et al., 2010; Bain, 2004). Therefore, I implemented the following procedures.

I cancelled lab at key points in the semester (e.g., as outlines were coming together) to instead conduct 20-30 minutes oral check-ins with each student individually during the pre-writing process. In these meetings, we discussed how the ideas were going to be organized within the paper. Meetings, and requiring outlines in the first place, hopefully got students thinking about their papers earlier in the semester than many would have otherwise and encouraged them to engage in prewriting organization rather than diving right into drafting as many are prone to do). I returned minimal written feedback for these preliminary steps and marked primarily completion credit; if they did it thoughtfully and in a timely manner, they earned all the available points for that preliminary step.

So far, what I was trying was not very different from what I’d done previously. But then, after students turned in their drafts of each section (e.g., literature review, methods), instead of marking it and returning it, I asked them to complete a short self-evaluation. The open-ended questions on the self-evaluation prompted them to focus on the areas of content and organization, common mechanical issues, time management completing the draft, and goals for revision. I then met with each student one-on-one to discuss their drafts. In these 30-minute meetings, we read the draft together and marked some key suggestions using Word’s track changes and comments features. I often used their self-evaluation as a starting place, especially if they had identified strengths or areas for improvement similar to those I noticed. I made a point to not mark the whole paper, but targeted examples. For instance, if my suggestion was for the student to use more parenthetical and fewer narrative (“___ found”) citations, we edited one or two paragraphs together to show them what that might look like.

At the end of these meetings, we completed the grading rubric (separate from the self-evaluation) together. Students left the meeting with their marked-up paper and (after my first round of meetings where I learned it would be more efficient to record the score and send it on the spot) the completed rubric. Working together to evaluate the drafts not only got them graded more efficiently, but provided students ownership in their learning process and therefore, theoretically, more buy in for the learning process (see Doyle, 2011). The assessment was now part of the learning process (see Bain, 2004).

At the end of the semester, students submitted not only their final paper, but also a revision reflection (similar to a revise and resubmit letter to the editor) in which they described the feedback they received, what they changed, and what they didn’t change (and why). On this revision reflection, I prompted them to describe the feedback they’d received on each section of their paper and how they’d incorporated it (or not).

Conclusions So Far:

Overall, I would say my experiments were a success and this is moving in a good direction, although maybe not there yet. (Will it ever be perfect? Probably not.) Many of the self-evaluations were thoughtful and, anecdotally, I believe more of the students at least registered and gave some thought to the feedback they received. By the end of the academic year, after meetings for the literature review, methods, and results, I noticed that students were doing more of the evaluating as we discussed the rubric for their discussion drafts, rather than waiting for me to tell them what score they earned. I asked the class for their thoughts and, even on the anonymous evaluations, most of them chose not to comment (I’ll take that as, “no complaints”). One student did tell me that they liked having meetings instead of a paper returned so they could ask clarification questions.

From a professor workload point of view, this approach was exhausting during meeting weeks, when I often had 6-8 meetings per day for several days in a row, but generally much more efficient than grading and returning papers. There were a few (less than 5%) students who delayed scheduling their meetings and/or with whom I had to make special arrangements for an evening or weekend due to athletics, jobs, or other outside commitments taking up most of their days, but we made it work. In the future I should probably be clearer that the onus is on the student to take more initiative and get these scheduled (aka your poor planning is not my emergency, schedule early to have enough choices that will work for you).

In part because I was forced to stay on schedule, students got their feedback in a timelier manner, even though I spent about the same amount of time on each student (30 minutes per paper to mark vs. 30 minutes meetings). I’m hopeful, although I only have anecdotal evidence thus far, that the feedback was clearer. For example, instead of writing a comment, “be sure to clarify the main idea of this paragraph,” I was able to ask students face to face, “what’s the main idea of this paragraph supposed to be? Yes. Write that.” I am also hopeful that feedback was deeper. It’s easy when I’m reading a paper to get caught up in marking the details, but I found with a one-on-one conversation, I could focus more on discussing the bigger pictures of organization and what points they were trying to make. One area where I saw a marked change was in reference formatting; in a face-to-face situation, I could point to a correctly formatted example and say, “this is correct. How is it different from this other one [that has an error]?”

In short, I will keep this self-evaluation and oral feedback approach, but with some tweaks. First, I will likely spend some time scaffolding useful self-evaluation, so maybe more students will use the self-evaluation to their best advantage instead of (as I’m sure some did) seeing it as another box to check. For instance, I might do the first self-evaluations in class on the day after drafts are due and maybe show them some of my self-evaluation process on nearly-complete papers. I might also add another meeting, even earlier in the process as students are collecting their potential sources. The biggest change, though, is timing. Last year I cancelled lab on the day the draft was due and held meetings then. This year, I’ll move meetings to the week after the draft due date. I think meeting as a lab on the day the draft is due will allow me to get the students started on next steps more efficiently and having a gap between due date and feedback will allow me to do more skimming ahead and preparation for more effective one-on-one meetings.

Nothing I’ve written about here is ground-breaking or even particularly innovative. But, sometimes it’s difficult to break from the way we were taught or the way we’re used to doing things. I hope that by sharing my journey so far I might contribute to the conversation as we, as individuals and as a field, strive for that magic solution that will be sustainable for us but still provide our students with the best possible learning experience.

References:

Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: 7 research-based principles for smart teaching. Jossey-Bass.

American Psychological Association [APA]. (2023). APA guidelines for the undergraduate Psychology major. Version 3.0. American Psychological Association. https://www.apa.org/about/policy/undergraduate-psychology-major.pdf

Bain (2004). What the Best College Teachers Do. Cambridge: Harvard University Press.

Doyle, T. (2011). Learner-centered teaching: Putting the research on learning into practice. Sterling, VA: Stylus Pub.