Action research: a methodology for transformative learning for a professor and his students in an engineering classroom
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
An engineering professor of a first-year thermodynamics course and a PhD student with a focus in engineering education in a large research university in Canada participated in an ethnographic action research study with the intention of increasing active learning in the classroom to enhance student engagement and learning. Unexpected findings included transformative changes to the professor’s epistemology of teaching and learning. Through the action research cycle of planning, implementing, observing, and critically reflecting, modifications were made to the instructional strategies and the learning environment that created a micro engineering community of practice where both students and teaching assistants engaged in deep learning and legitimate peripheral participation on the trajectory to ‘becoming engineers’. Qualitative interview data from the professor, three students, and three teaching assistants are analysed through approaches to learning research and situated learning theory. Engaging in action research had profound repercussions in this case. The authors make the argument for action research as a catalyst for transformative learning required for teachers to engage students in the twenty-first century classroom.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it