Exploring Secondary Students’ Conceptions about Fire Using a Two-Tier, True/False, Easy-to-Use Diagnostic Test
Bibliographic record
Abstract
This article describes the design of a misconception diagnostic test about fire-related phenomena. It proposes a new test format in which a certainty-measuring tier has been integrated into each of the true/false response choices. This format is argued to be easier for teachers to use than the increasingly popular three-tier format. First, we review the available literature about misconception diagnostic tests and then literature about fire-related misconceptions. We then describe the design process of the test, which was preceded by an interview phase. We then describe its administration to 221 secondary school students. We finally present, in an explorative and accessible manner, the results that were obtained. These results support the existence of previously recorded misconceptions, but also bring certain nuances to some of their previous interpretations. They also support the hypothesis according to which some misconceptions are presumed to be more widespread than they truly are. Conclusive remarks are formulated about the benefits of the use of our—and other— misconception diagnostic tests.
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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 | 0.006 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".