A Designed Teaching Sequence as a Tool to Improve Students’ Conceptual Understanding of the Conductivity in the Electrolytic Cell
Bibliographic record
Abstract
This paper reports on a study to determine the efficacy of a teaching sequence following the Leeds model framework designed for a specific content of learning in electrochemistry. The design of the teaching draws upon theoretical insights into perspectives on learning and empirical studies to improve the teaching of this topic, specifically ‘Electrolytic Cell’. A case study involving two classes, the Experimental and Baseline classes was carried out for 16-year-old Malaysian upper secondary school students. Also, eight classes of similar age in eight different schools who served as convenience samples (reference groups) were selected in order to compare the differences on their conceptual understanding in a wider sample. The evaluation of students’ responses in one of the items in the post diagnostic test shows that there were significant differences in the experimental class students’ performances in comparison to the baseline class students and the convenience samples. The experimental class students who followed the designed teaching sequence demonstrated better conceptual scientific understanding regarding the roles of ions and electrons in the conductivity of the electrolytic cell.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".