Web‐based diaries − windows to student internship feedback experiences
Notice bibliographique
Résumé
Context and setting Clinical internships in physiotherapy are a valued learning experience providing students with authentic problems and complex challenges. Students need to reflect on their experiences during the internship to enhance their learning. Feedback experiences are a powerful but largely neglected component of learning in clinical settings. Why the idea was necessary The web-based diary program was created to promote student reflection about their internship experiences and to provide academic faculty with a window to the students' experiences in the clinical environment. Reflection is recognised as a vital component of learning and professional practice but may be neglected by students in demanding clinical internships. There are geographical and system barriers between the clinical and academic settings which prevent academic faculty from fully understanding the students' experiences during internship. What was done Twenty-one senior physiotherapy students in advanced outpatient musculoskeletal clinical internships volunteered to submit bi-weekly web-based diary entries during their 5-week internship. Students used diary software with embedded guiding questions to write about the feedback they received from their clinical instructors. The software developed by Atsoft Inc., specifically for this study allowed faculty and researchers to interact with students while maintaining confidentiality and anonymity on a secure web site. Evaluation of results and impact Over a 5-week period, 210 feedback interactions yielding 229 pages of diary entries were captured. Diary entries were analysed for emerging themes about feedback. Analysis yielded 3 key findings about feedback received by students in the clinical setting. Students perceived the need for a clear and explicit delivery process. From the diaries a feedback process was developed which was later presented by the students to the clinical instructors in a workshop. The second theme focused on the conflict of openness in the clinical environment. Students referred frequently to ‘openness’ and used the word in a variety of contexts. They expressed an appreciation of the value of openness on the part of the instructor about their performance but admitted that they felt reluctant to disclose their own knowledge deficits or to acknowledge that they had made a mistake. They recognised the inherent danger that potentially existed in admitting or denying errors and knowledge deficiencies. Finally, the relationship between the clinical instructor and student was found to be a powerful determinant of whether the students described their clinical internships as a positive or negative experience. Students gained valuable insights by reflecting about their feedback experiences and became more active participants in the process of ensuring that the internship met their learning needs. Academic faculty gained a deeper understanding of the concerns and issues faced by students during internship which can be addressed through the program curriculum. Web-based diaries improved student reflection and allowed faculty to view and understand student experiences without temporal or geographical constraints. This software has the potential to encourage students to reflect on a variety of topics and allows faculty to identify and provide real-time intervention regarding issues that might otherwise be overlooked during clinical internships.
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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 | 0,004 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,004 |
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 ».