Learning experience and relationships among learners in online Recovery College courses: an exploratory qualitative study
Bibliographic record
Abstract
Introduction: Recovery Colleges (RC) are community-based learning centers. They offer courses in mental health, well-being and recovery. RC courses are co-constructed and co-facilitated by two trainers with complementary knowledge. Learners come from diverse backgrounds ensuring a variety of expertise and experiences. Studies have demonstrated the benefits of RC courses for learners. The mechanisms of action specific to RC explains the benefits. Studies about the mechanisms of action of RC show the importance of the social environment of RC. The Centre d'apprentissage Santé et Rétablissement (CASR) is a Canadian French-language RC offering free online courses to the public. Objectives: The study aims to answer two research question: 1- How do learners of CASR’s online courses describe their learning experience? 2- How do learners of CASR’s online courses describe the relationships they experienced? Methods: An exploratory qualitative study consisting of ten individual interviews followed by a thematic analysis was conducted. Results: Participants describe their learning experiences in terms of the characteristics of the CASR course space: inclusive and benevolent learning space; connected, supportive, and egalitarian space for interaction; collaborative and co-constructed knowledge space. Participants describe the relationships in terms of: equality; respect and non-judgment; recognition and belonging; collaboration and mutual support. Conclusion: The results confirm the existence of mechanisms of action in CASR courses like those identified in previous studies. The learning context of the CASR prompts some participants to prioritize their personal roles over their professional roles during courses. By exposing their vulnerability, they show humility and encounter equal relationships.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".