Meeting the Challenge of a Changing Teaching Environment: Harmonize with the System or Transform the Teacher's Perspective
Bibliographic record
Abstract
The beliefs that teachers hold about the appropriate roles and responsibilities of teachers shape the ways they teach and the ways they think about teaching. In this paper I describe four teaching roles based on a taxonomy that I've recently developed. Teachers who are guided primarily by the Content Expert Role view themselves as experts who serve as resources, like books or pictures. Teachers who are guided primarily by the Performance Role view themselves as agents who make learning happen by transmitting information or shaping students. Teachers guided primarily by the Interactive Role view themselves as guides who facilitate learning by interacting with learners. And teachers guided primarily by the Relational Role view themselves as engaged in relationships with learners for the purpose of helping them. Using examples taken from the health sciences I explain how each of the four teaching roles might succeed or fail depending upon the position that it occupies within a teaching-learning system. When teaching is viewed as part of a system, not as something a teacher does to a learner, teachers are successful if their particular contribution to the system is essential to the learning system. I also describe the process whereby teachers expand their belief system to include more roles. Such changes in belief systems are major shifts that qualify as "perspective transformations". Perspective transformations take place slowly and are typically attended by strong emotions. I end this paper with advice to teachers regarding ways they can harmonize with the educational system or face the challenge of perspective transformation.
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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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.042 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".