Developing Pre-Service Teachers' Technological Pedagogical Content Knowledge for Teaching Mathematics with the Geometer's Sketchpad through Lesson Study
Bibliographic record
Abstract
The purpose of this study was to develop pre-service secondary teachers' technological pedagogical contentknowledge (TPACK) for teaching mathematics with The Geometer’s Sketchpad (GSP) through Lesson Study(LS). Specifically, a single-group pretest-posttest design was employed to examine whether there was asignificant difference in the pre-service secondary teachers' TPACK for teaching mathematics with GSP afterengaging in LS which was incorporated into the mathematics teaching methods course during the first semesterof the 2011/2012 academic session in a Malaysian public university. Forty-six pre-service secondary teacherswho enrolled in the course completed both the pretest and posttest questionnaires on teachers' TPACK forteaching mathematics with GSP. The results of the paired-samples t-test indicated that there was a significantdifference in the pre-service secondary teachers' TPACK for teaching mathematics with GSP for all thesubscales after engaging in LS.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".