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Grade Negotiation Behaviours in Higher Education: Has the Pursuit for Good Grades pushed Learning to the Wayside?

2021· article· en· W3168216434 on OpenAlexaff
Andrew J. Horne, Sarah McLean, Tyler S. Beveridge

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern University
Fundersnot available
KeywordsMindsetPerceptionPsychologyMedical educationNegotiationMedicine

Abstract

fetched live from OpenAlex

Introduction Allen (2017) describes a grade enquiry continuum (GEC) that seeks to characterize student's behaviours with instructors into four categories: grade neutral, grade enquiry, grade challenge, and grade‐grubbing. While the process of discussing grades may promote learning, the de‐emphasis of content mastery associated with the latter two categories may have detrimental effects. Concerningly, anecdotal reports suggest a high prevalence of grade challenging/grubbing attempts in higher education, and it remains unknown what motivates these adverse behaviours. Thus, this study aims to explore the prevalence of GEC behaviours in undergraduate medical science students, their perceptions about negotiating grades, and the factors that motivate grade challenging/grubbing attempts. Methods In our first objective, a survey was administered to 2,500 undergraduate medical sciences students (n=367 completed) at our institution to examine students’ self‐reported prevalence, perceptions and motivations for grade challenging/grubbing. To determine the validity of these reports, we also conducted an observational study with 31 students (n=4 completed) to explore if their self‐reported behaviours aligned with their observed behaviours. In our second objective, we explored whether the perception of losing versus earning grades influenced their propensity to grade challenge/grub through an experimental manipulation of how grades are presented on their learning management system (n=31). Focus groups were used in a follow‐up with participants to examine the reason for changed/unchanged behaviour or mindset. Results Our survey results indicated that 50% of students who had met with an instructor/teaching assistant before had also negotiated a grade (n=99). Furthermore, of the 40 students in their 4th year answering this question, 65% had negotiated a grade. In addition, results from our second study showed that ≥14 accounts of grade challenging and four accounts of grade grubbing were self‐reported over just the course of one semester (n=31). Qualitative findings suggest that many students within the study population are extrinsically driven by career goals and view their grades as a way to competitively distinguish themselves for post‐graduate programs. These motivational factors and perceptions towards grades may be influencing these adverse behaviours. Conclusions: This study was the first to quantify self‐reported grade negotiation behaviours at a program level. It was also the first to use an experimental design to document and observe these behaviours in a real classroom setting. Our findings clearly show that GEC behaviours are as prevalent as anecdotally suggested. This understanding is necessary moving forward to further investigate whether these behaviours are getting worse, what causes students to exhibit these behaviours and what interventions or actions can be implemented to deter these behaviours in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.065
GPT teacher head0.340
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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