In search of student engagement in high school physics through contextual teaching
Bibliographic record
Abstract
This action research study compared student intellectual engagement between two different instructional delivery methods. The first instructional method was a non-contextual teaching approach using a textbook to teach the work outcomes for the S4 physics mechanics unit. The second instructional method was a contextual teaching approach where students built an electric guitar pickup and a simple electric guitar in order to provide a context for the teaching of the electromagnetism outcomes for the S4 physics electricity unit. To measure the intellectual engagement of students, data was collected from personal student journals and from questions generated by students following different instructional activities. The student generated questions were categorized and ranked to judge the degree of student intellectual engagement and depth of thought using a framework where numerical values were assigned to the questions. Each question was categorized as peripheral, factual, conceptual, or philosophical where the peripheral questions had the lowest intellectual ranking and the philosophical questions had the highest intellectual ranking. Data was also collected from cumulative unit tests, short exit slips and a personal teacher journal. The research revealed that students were more intellectually engaged and exhibited much more positive attitudes during the contextual lessons. The questions generated by students during the contextual lessons were of the higher order factual and conceptual types while the questions generated during the non-contextual lessons were predominantly of the lowest order peripheral type. By using the electric guitar and electric guitar pickup as a context, this action research study demonstrated that these contextual activities intellectually engaged students and helped to facilitate their deeper understanding of electromagnetism.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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 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".