Unipolar Reasoning in Electricity: Developing a Digital Two-Tier Diagnostic Test
Bibliographic record
Abstract
The purpose of this study was to develop a two-tier test to diagnose unipolar reasoning in electricity. Thus, at first, we built a questionnaire composed of four questions with two choices (True / False) with justification. The justification step is methodologically essential; it has allowed us to identify different categories of conceptual representations. Then we administered it to students (N = 100) in the Science education training program. The students’ answers were analyzed and used to create the choices for the two-tier questions. The two-tier questions allow the student to give his explanation if the choices presented do not conform to his representation. Finally, high school students (N = 25) completed an electronic version of the two-tier test to solicit their commentary. The majority was enthusiastic about their participation, despite the conceptual destabilization generated by completing this test.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".