Mapping the development of transformative learning theory across continents: A literature review.
Bibliographic record
Abstract
This literature review paper aims to explore the current state of transformative learning \ntheory in a global context by examining how scholars from different world regions understand, utilize, and develop transformative learning theory in their own contexts. Transformative learning theory has been a significant framework for investigating individuals’ personal transformations (Mezirow, 1997, 2000) and \npromoting social transformations (Allman, 1999). Our review covers scholarship from the USA, Canada, Europe, Asia, the Middle East, Africa, and South America. The results reveal an unequal development of transformative learning theory among countries in the West and East and North and South. This paper argues that mapping the understanding of transformative learning theory in a global context could help bridge the theoretical gap between different regions, enrich our understanding of the broader meaning of transformative learning, and promote more inclusive and equitable practices in education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".