"The School of Life": personal storytelling in a multicultural classroom
Bibliographic record
Abstract
This thesis seeks to provide a deeper understanding of the pedagogical approach of personal storytelling in a multicultural classroom, where the teacher creates a safe and comfortable space for students and encourages them to share their personal experiences as they reflect upon and engage with the educational curriculum. This research used a qualitative case study to explore personal storytelling in the McGill University School of Continuing Studies hospital training program, particularly in an English as a Second Language (ESL) class, which consisted of adult medical professionals, certified doctors, nurses, administrative staff and psychologists who came from a wide range of ethnic backgrounds. Thematic analysis revealed significant academic and social benefits for both the teacher and the students—highlighting the importance and pedagogical benefit of sharing stories and recalling memories of lived experiences in the multicultural environment. Personal storytelling, as a pedagogical method, generated a safe environment that encompassed empathy and acceptance amongst the students. As students felt at ease sharing their personal experiences with one another, they were able to practice their spoken English skills and deepen their knowledge about a wide array of issues and topics. In addition, the instructor's teaching skills were remarkably enhanced. This demonstrates the strength of personal storytelling in facilitating the learning process. It connects students to the curriculum, to one another and to their teacher, especially in multicultural contexts like Canadian classrooms.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.019 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".