Design of a teachers’ training workshop for improving technology integration skills
Bibliographic record
Abstract
Educationists and researchers recommend integration of simulations in classrooms to promote student-centric constructivist learning. The simulations need to be carefully designed toward improvement ofconceptual understanding of students. In this paper, we report on a training workshop for teachers with the specific goal of imparting simulation integration skills for classroom teaching. In the workshop, we used SEQUEL, a freely downloadable circuit simulator, and focused on electronic circuits taught typically at the second-year undergraduate level. We applied education technology principles as well as constructivist alignment methods to design the workshop. In particular, collaborative learning strategies such as think-pair-share and peer instruction were covered specifically for the intended simulation integration. Furthermore, application of the flippedclassroom model in the context of circuit simulation was explained to the participants. We report on the workshop design in detail and report the impact of the training workshop on integration skills of the teachers. We found that teachers (N=15) perceived the workshop to be usefulin designing their aligned lesson plans. Teachers also reported their field study in which they found improved motivation of students to solve electronics circuit problems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".