Understanding the learning context in shaping the relational experience in online recovery college courses: a qualitative study
Notice bibliographique
Résumé
Purpose In learning context, interaction among learners is a fundamental mechanism of action that contributes to learning, a principle exemplified by Recovery Colleges (RCs). RCs offers universal access to mental health, well-being and recovery courses that focus on the nature of social interactions as a central mechanism of action. During the pandemic, some RCs had to switch from face-to-face to online courses, which made it more difficult to maintain the quality of social interactions between learners and trainers. This study aims to describe the relationships experienced by learners in online Recovery College (RC) courses and to identify the contextual elements that contribute to connectedness among them. Design/methodology/approach A qualitative study was conducted using exploratory focus groups and individual interviews with 26 participants. The data were analyzed using an inductive thematic approach. The elements of the learning context that contribute to connectedness among learners have been schematized. Findings The first theme that emerged from the analysis concerns the study participants’ relational experiences describing the relationships experienced in the course, the postures they adopted and the benefits they gained. In addition, the elements of the learning context that contribute to connectedness are the climate, the course format, the trainers’ and learners’ influence and the RC principles and values. Research limitations/implications The small sample size constrains the diversity of perspectives captured, and thus, the findings should be interpreted with caution. The study may not fully encompass the range of negative or dissatisfying experiences that learners could encounter. The findings may also be influenced by social desirability bias. Finally, this study would have benefited from the involvement of a broader range of collaborators with diverse types of knowledge throughout the research process. Practical implications This study provides practical advice for trainers wishing to implement elements that promote connectivity between learners in online course. Key strategies include clearly outlining RC values and principles from the outset, designing activities that promote discussion and consistently modeling inclusive, supportive, authentic behaviors. The trainers have a central role in cultivating a positive and connected online learning environment. Social implications Since the pandemic, many training initiatives, such as RC, have changed their operations and transitioned online. While online courses can be convenient, flexible and accessible, they also present several challenges. These findings can benefit any online training initiative related to mental health and recovery. The elements of the learning context that contribute to connectedness among learners. Originality/value To the best of the authors’ knowledge, this is the first published study to focus exclusively on the relationships among learners in online RC courses and the contextual elements that influence these relationships.
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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 | 0,014 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,009 | 0,010 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».