What were They Thinking? Using Cognitive Interviewing to Examine the Validity of Self-Reported Epistemic Beliefs
Bibliographic record
Abstract
We employed cognitive interviewing with a sample of secondary, college, undergraduate and graduate students to examine the cognitive validity of a popular epistemic beliefs self-report measure, the Discipline-Focused Epistemological Beliefs Questionnaire [DFEBQ] (Hofer, 2000). In addition, we examined cognitive validity across two domains. Analyses of interviews revealed that cognitive validity was good, wherein students ’ responses were typically within an expected range of interpretations. However, students ’ interpretations of items were not always consistent with researchers ’ intended meanings, interpretations sometimes differed across domains, and that the response option “3 ” as a neutral response was not always used as intended. To improve validity of self-report measures of epistemic beliefs more generally, we recommend that explicit anchors are used, such as “mathematician ” instead of “expert, ” and that definitions of the dimensions are presented to respondents to ensure interpretations align with researchers ’ intended meanings. We end with broader methodological implications.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".