Identifying Student Use of Ball-and-Stick Images versus Electrostatic Potential Map Images via Eye Tracking
Bibliographic record
Abstract
This pilot study examined students’ use of ball-and-stick images versus electrostatic potential maps when asked questions about electron density, positive charge, proton attack, and hydroxide attack with six different molecules (two alcohols, two carboxylic acids, and two hydroxycarboxylic acids). Students’ viewing of these dual images was measured by monitoring eye fixations of the students while they read and answered questions. Results showed that students spent significantly more time with the ball-and-stick image when asked questions about proton or hydroxide attack, but equal time on the images when asked about electron density or positive charge. When comparing accuracy and time spent on the images, students who spent more time on the ball-and-stick when asked about positive charge were less likely to be correct, while those who spent more time with the potential map were more likely to be correct. The paper serves to introduce readers to eye-tracker data and calls for replication with a larger subject pool and for the inclusion of eye tracking as a chemical education research tool.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".