Investigating feedback-associated stress and mindfulness in undergraduate physiology students and other higher education programs
Notice bibliographique
Résumé
Study objective: Students who engage with and learn from academic feedback have developed what is known as feedback literacy skills. Being able to learn from feedback is an exceptionally powerful way of growing as a student; however, the process of receiving feedback can be stressful. This can lead to behaviours such as avoidance, denial or diminishing the importance of feedback, which can impact learning. Providing students with the skills needed to learn from feedback and to manage feedback associated stress is therefore increasingly relevant to student success and wellbeing. Feedback literacy skills include managing affect (emotions), focus, and self-advocacy, which are skills that are supported by mindfulness. Mindfulness is being present, on purpose, and without judgement, and is a proven practice that helps to reduce and manage stress. This study is of post-secondary students’ perceptions concerning feedback literacy, mindfulness, and stress, and their thoughts on digital mindfulness tools intended to support students who experience feedback-associated stress. Hypothesis: Students with higher mindfulness skills will also have higher feedback literacy skills and will also have lower stress. Methodology: Students were recruited from across several disciplines (+1000 students), including Physiology and Pharmacology, Dentistry, Occupational Therapy, Information and Media Studies, and Law, along with students supported by the Learning Development and Success Centre at Western University. The study included an online survey ( n=237) and focus groups ( n=6). Gender and program were both included in the survey; however, due to limited sample size, no additional analysis of these factors was conducted. Coding and thematic analysis was conducted by three faculty and two graduate research assistants. Summary of results: The survey data demonstrates that students with greater mindfulness have significantly greater feedback literacy, as well as lower stress. Thematic analysis of focus group data shows a broad range of affective and behavioural responses were shaped by how students perceive their own abilities, circumstances, and feedback itself. Thematic analysis also suggests there is a developmental trajectory for both mindfulness and feedback literacy as graduate students discussed more mindfulness and feedback literacy skills. Discipline-specific views on mindfulness and stress were also apparent. Conclusion: Survey results indicate that students who are more mindful have higher feedback literacy skills; however, when mindfulness and feedback literacy were discussed in focus groups, data suggests that few students considered explicitly linking mindfulness to academic feedback. Students across the various programs expressed vastly different familiarity with mindfulness and feedback literacy. All students expressed interest regarding the development of digital mindfulness tools to alleviate feedback-associated stress and offered recommendations for their implementation. These recommendations were discipline-specific and included the development of program competencies with respect to feedback literacy and wellness. Internal grants from the University of Western Ontario and the Schulich School of Medicine and Dentistry. 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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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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».