Teacher action research and student voice: Making sense of learning in secondary school
Bibliographic record
Abstract
The Making Sense of Learning project began with the premise that for teachers to understand the ways in which their practice influences student learning, they need to invite and listen to students’ accounts of their learning experiences. Initiated by classroom teachers, supported by a university researcher, and informed by student voice, this teacher action research involved the empirical-reflective (self-) study by teachers of their practice as interpreted and critiqued by their students and themselves. This article explores how researchers challenge teachers to move beyond taken for granted conceptions of teaching, learning, and roles of students, to engage in learning-centered dialog with their students and through this, transform classroom practice. Supported by the researchers, teachers and students gain a sense of empowerment as they deepen their relationships and negotiate new roles as partners and coresearchers making sense of learning in their classrooms. Teachers and students come to situated understandings of the complexity of teaching and learning that reveal transformative and emancipatory outcomes.
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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 | 0.031 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.058 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".