Student participation in university governance: a qualitative study
Notice bibliographique
Résumé
Abstract This qualitative study explored the perceptions of students who were involved in the governance process of a case university. The focus of the study was to learn how the university context contributes, or not, to participation in student governance. More specifically, the questions that guided the study were: "How do students become involved in university governance?", "What were the kinds of governance activities in which they were involved?", and "What issues and/or challenges did the student representatives encounter, or not, while participating in governance?" The data sources included student interviews, professor interviews, field notes, and university public documents. Constant comparison analysis of the student interviews resulted in eight descriptive categories from which three major themes emerged. The first theme, "governing framework," included the complex arrangement of subcategories, disciplined governing, and executing responsibilities. This theme revealed the complex organization of university and student associations, their functions and the significance of their role in university governance. The descriptive sub-categories participatory factors, interactional factors, and personal propensity of students were merged into the "enticing involvement" theme, which helped anticipate students' participation in university governance processes and how the university could further support their involvement. Students' personal reluctance, role definitions and sense of belongingness established the conceptual theme, "defining the line." These themes reflected the overall university governance process and the corresponding student engagement status. Exploration of the governance process of a large Canadian university through students' eyes revealed many examples of "micro-aggressions". Such incidents of micro-aggression were not very evident to casual observers and people around students. Even though these micro-aggressions were not intentional, students faced problems that included, but were not limited to, gender-specific biases, racial biases, student-specific biases, and so forth. Students felt that such occurrences had occurred as they were inferior to any other group of university. Finally it had been suggested that mainstream students should be recognized as a specific type of stakeholder of university, which could counter the problems faced by students. Future research should explore the issue involving students, professors, administrators, and other stakeholders.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,012 | 0,010 |
| Communication savante | 0,007 | 0,006 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».