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Student Perspectives on the Utility of Crib Sheets for Learning

2024· article· en· W4398166782 on OpenAlexaff
Anita Woods, Bryn Bhalerao

Bibliographic record

VenuePhysiology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyBiology

Abstract

fetched live from OpenAlex

In response to the noticeable rise in anxiety with the return to in person, closed book exams, our department embraced an alternate testing method that permitted the use of a self-created note resource, also known as a crib sheet, in a third year Human Physiology course. Although anxiety reduction was certainly a reason for this change in evaluation methods, it was predicted that crib sheet exams would encourage a shift to deeper learning studying methods, rather than a reliance on rote memorization. Crib sheets have been shown to decrease test-taking anxiety (Ozer, 2021), and different crib sheet organizational strategies have been correlated with increased exam performance (Dickson & Bauer, 2008; Shaw & Almeida, 2018). However, there is a lack of understanding of the benefits and potential detriments beyond the effect of crib sheets on exam performance (Larwin et. al, 2013). Furthermore, what has not been established is if crib sheets promote more learning prior to the exam or if they are a source of dependency and therefore detract from learning. From the two hypotheses that were first suggested by Dorsel and Cundiff (1979), we expect that most students learn the material while they create their crib sheets, supporting the coding hypothesis rather than a reliance on the crib sheet, which would support the dependency hypothesis. For each of the three exams in this course, students were permitted to bring a 4x6 inch cue card with them containing any information they deemed important. After each exam, students completed an optional post-exam reflection, which was a combination of Likert scale responses to questions about their anxiety levels, questions about study methods, and about the utility of the crib sheet that they created for the exam. At the end of the academic year, data was deidentified for consenting participants for subsequent analyses. In total, of the 434 registrants in this third-year physiology course, 58 consented to have their data analyzed. Additionally, instructors involved in courses that used crib sheets, including this physiology course, were also invited to participate in the study for their perspectives of the use of crib sheets. Of the 14 total instructors who taught in these team-taught courses that used crib sheets, 6 agreed to participate in the interviews. Semi-structured interviews were conducted for instructors’ perspectives towards crib sheets. The transcripts from these interviews were analyzed by thematic analysis using NVivo. One of the compelling findings from the instructors’ interviews within our study cohort, show that although most were accepting of the use of crib sheets, they were also hesitant to embrace crib sheets as a pedagogical tool due to the lack of literature that would support these as a learning tool. However, early investigation of both Likert scale responses and open-ended text responses from the student participants shows that many students report learning while creating the crib sheets. Furthermore, student participants reported a change in study methods while preparing for crib sheet permitted exams, with a shift to incorporating more methods that promote less rote memorization, such as condensing notes and creating flow charts/mind maps. Therefore, early analyses of student data provide support for the coding hypothesis, which supports that learning does occur during crib sheet construction in a human physiology course. From these analyses, which combine student and instructor perspectives, we further recognize the importance of delineating the utility of crib sheets, based off of student reports. With our study, we aim to advise teaching and learning practices surrounding the use of crib sheets in higher education. REFERENCES Dickson KL, Bauer JJ. Do Students Learn Course Material During Crib Sheet Construction? Teach Psychol. 2008;35(2):117-120. doi:10.1080/00986280801978343 Dorsel TN, Cundiff GW. The Cheat-Sheet: Effcient Coding Device or Indispensable Crutch? J Exp Educ. 1979;48(1):39-42. doi:10.1080/00220973.1979.11011712 Larwin KH, Gorman J, Larwin DA. Assessing the Impact of Testing Aids on Post-Secondary Student Performance: A Meta-Analytic Investigation. Educ Psychol Rev. 2013;25(3):429-443. doi:10.1007/s10648-013-9227-1 Özer S. A Convergent Parallel Mixed-Method Research into the Use of the Cheat Sheet in Teacher Education: State Test Anxiety, Exam Scores and Opinions of Prospective Teachers. Turk Online J Educ Technol - TOJET. 2021;20(3):101-113. Shaw JA, Almeida MG. Does the Quality of Student Crib Cards Influence Anatomy and Physiology Exam Performance? HAPS Educ. 2018;22(1):50-54. doi:10.21692/haps.2018.005. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.417
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
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