Teacher’s agency orientations in flipped learning: An ecological perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• examines the agency of experienced Flipped Learning mathematics teachers. • identifies three agency orientations that give meaning to Flipped Learning. • illuminates ecological conditions that enable and constrain teacher agency. • supports the implementation and sustainability of Flipped Learning. This study examines teacher agency in applying Flipped Learning (FL), focusing on four mathematics teachers in Finnish schools who have implemented FL in their classrooms for several years. Using an ecological perspective, it identifies three distinct agency orientations in teachers’ accounts, each characterised by unique temporal features. These agency orientations—Reproductive, Practical-Projective, and Reflective-Reconstructive—illuminate the meaning teachers attach to FL in their classroom practice and how these meanings evolve over time. The study highlights the need to consider teachers’ agency orientations along with their cultural, structural, and material dimensions to fully understand FL’s transformative potential in classroom practice.
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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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it