An adult educator’s reflection on designing and delivering an embodied learning community development programme and embodied teaching and learning methods
Bibliographic record
Abstract
Purpose This paper presents an educator’s perspective, on creating and facilitating an embodied learning programme with implications for theory, research and practice. Embodied learning methods, which centre the body in learning, have been discredited for being alternative to traditional learning methods and underappreciated in many formal institutions. Hence, this paper aims to challenge assumptions regarding quality education and proposes alternative directions to support the quality of education for migrants and refugees. Design/methodology/approach The research followed a qualitative decolonial methodological approach. The principal investigator developed and delivered an embodied learning community development programme in Canada consisting of 12 sessions. Data was collected using embodied ethnographic methods which included fieldnotes and a reflective journal. Data sources were analysed using reflexive thematic analysis (Braun and Clarke, 2021). Findings The embodied learning approach was well received and resulted in establishing deep interpersonal connection. However, developing and facilitating an embodied learning programme, from the perspective of a researcher and practitioner, takes a significant amount of energy and involved profound levels of engagement. Originality/value This research makes two important contributions. The first is the evidence of ways in which embodied learning approaches can improve the quality of education for migrants and refugees. The second comes from the insights on factors to consider for quality design and delivery of embodied learning programmes. This research has value to researchers and practitioners interested in alternative education and migrant education. The results and discussion provide suggestions for future development of embodied educational programmes.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".