Epistemic Beliefs Moderate Mediations Among Attitudes, Prior Misconceptions, and Conceptual Change
Bibliographic record
Abstract
We investigated the mediating and moderating roles of attitudes and epistemic beliefs in conceptual change during learning about genetically modified foods (GMFs). One hundred twenty undergraduate students participated. To measure misconceptions about GMFs, students first completed a prior knowledge test. Students then completed self-report inventories to measure their attitudes and topic-specific epistemic beliefs regarding GMFs. Students were then randomly assigned to read a refutation or expository text about GMFs. Following reading, students completed a test to assess conceptual change. Results of a repeated measures ANOVA revealed participants who read a refutation text changed more misconceptions at post-test than participants who read an expository text. A moderation mediation analysis revealed attitudes toward GMFs significantly mediated the relationship between prior misconceptions and conceptual change, and that this relationship was moderated by learners’ beliefs regarding the source and justification of GMFs knowledge. Theoretical and educational implications are discussed.
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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 | 0.008 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".