Why do instructors pass underperforming students? A Q-methodology study
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Notice bibliographique
Résumé
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.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,022 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle