An instructional challenge through problem solving for physics teacher candidates
Bibliographic record
Abstract
The teaching of science, especially at pre-college and teacher education levels has undergone tremendous transformation over the years: from teacher-centred transmission to student-centred approaches rooted in constructivism. Whereas constructivism has been charged with all manner of shortfalls, it still can be of benefit to the way physics instructions are organized and implemented. In this paper, the importance of learners' prior knowledge in understanding physics concepts is discussed. This study comprised a case of two cohorts of physics teacher candidates who had strong content knowledge of physics, but lacked pedagogical knowledge as demonstrated by their struggles to implement appropriate grade-level strategies in physics problem solving tasks (which are amenable to a variety of mathematical tool-choices). The case cohorts were used as exemplars to underscore the importance of learners' prior mathematical knowledge. Thus, the paper is concluded by focusing on implications for pre-service teacher preparation, and the effects mathematical tool-choice can bear on their students' conceptions.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".