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Record W4403377322 · doi:10.1186/s12909-024-06126-2

Why do instructors pass underperforming students? A Q-methodology study

2024· article· en· W4403377322 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMC Medical Education · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicQ Methodology Applications
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedical educationMathematics educationComputer sciencePsychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Formal evaluations are an integral part of a student's learning and encourage students to learn and help instructors identify students' weaknesses. Over the past few decades there have been growing concerns that instructors and evaluators are passing students who do not meet expectations. This phenomenon, in which instructors pass students who do not meet expectations, has been referred to as "failure-to-fail". In this study, we used Q-methodology to identify instructors' justifications for failure-to-fail. METHODS: A Q-methodology study was conducted to identify the major viewpoints of instructors at a Canadian university. A by-person factor analysis with principal component factor extraction and Varimax rotation was used. The analysis was conducted using the QFACTOR program in Stata. A Cohen's effect size of 0.80 was used to identify distinguishing statements. RESULTS: Fifty seven instructors participated in this study. Through a by-person factor analysis, three factors representing three viewpoints emerged: Intrinsically Motivated, Extrinsically Motivated, and Administratively & Emotionally Deterred. The Intrinsically Motivated group perceived mental barriers that prevented them from failing students. They strongly disagreed that they experienced pressure from either students or their schools to pass students. The Extrinsically Motivated believed that their higher-ups and the university encouraged them to pass all students. They perceived discomfort associated with defending their reasons for failing students and were concerned that failing students would damage their own career advancements. The Administratively & Emotionally Deterred group believed that the process of failing a student was stressful and exhausting. They disagreed that a failed student is a result of the instructor's own inadequate guidance or mentorship. CONCLUSIONS: This study identified three distinctive viewpoints that outline areas of consideration for addressing the failure-to-fail mechanism. More transparent discussions within schools, as well as identifying solutions, are required to create systems that ensure educational and professional standards are maintained. Further replication of this study in various disciplines may be used to determine whether these findings are consistent in different fields.

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.

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)0.022
metaresearch head score (Gemma)0.064
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.372
GPT teacher head0.587
Teacher spread0.215 · 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