Illuminating Transformative Learning/Assessment: Infusing Creativity, Reciprocity, and Care Into Higher Education
Bibliographic record
Abstract
In this article, the authors speak to the paradox of assessing transformative learning (TL) in higher education. TL theory, developed by Jack Mezirow, is a theory of learning to describe the process of change in how individuals view the world based on previous experiences. Recognizing that the 10 phases of Mezirow’s TL theory are fluid and intertwined, three prominent aspects resonated within the individual narratives: the importance of a disorienting dilemma, the qualities of self-reflection, and liberatory actions. By exploring the complexities, challenges, and possibilities encountered in their classrooms, the shared narratives reveal how students were engaged in TL and embedded within are holistic assessment processes the authors enacted with learners. Throughout this dialogical narrative inquiry focused on assessment, the authors underwent their own TL in the presence of each other, confessing uncertainties and vulnerabilities, thus showcasing the potential to transform understanding with and through reciprocal learning.
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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 | 0.047 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.065 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.004 | 0.009 |
| 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".