Conceptual change in chemistry schematic modelling: a cross-sectional study of 10th–12th-grade Belgian students
Bibliographic record
Abstract
Practice-oriented studies on conceptual change in chemistry education remain relatively scarce. In agreement with the constructivist approach, in which learners build their own cognitive structure, many results have shown that learning through modelling positively contributes to conceptual adaptation. From this point of view, this study presents a cross-sectional study of secondary school learners’ schematic modelling abilities in the upper secondary school. The schematic modelling skills and competences of 216 students (15–18 years old, 10th–12th grade), ranging from purely macroscopic conceptions to an adequate interplay between the three levels of Johnstone’s triangle, have been assessed within selected contextualized situations. The data were collected using a three-part instrument, namely the analysis of the information contained in a graphical scheme, the perception of the role and relevance of schematic modelling, and the autonomous production of schematic modelling. The collected data show that 12th-grade students have a significantly higher capability of analysing the information of a scheme compared to 10th and 11th grades. Moreover, autonomous schematic modelling skills follow the same trend. The data also provide some evidence that students with better model analysis competences design higher quality autonomous models at the submicroscopic level.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".