Patterns, predictors, and outcomes of situated expectancy‐value profiles in an introductory chemistry course
Bibliographic record
Abstract
Using latent profile analysis, we identified profiles of expectancy beliefs, perceived values, and perceived costs among 1433 first- and second-year undergraduates in an introductory chemistry course for STEMM majors. We also investigated demographic differences in profile membership and the relation of profiles to chemistry final exam achievement, science/STEMM credits completed, and graduating with a science/STEMM major. Four motivational profiles were identified: Moderately Confident and Costly (profile 1), Mixed Values-Costs/Moderate-High Confidence (profile 2), High Confidence and Values/Moderate-Low Costs (profile 3), and High All (profile 4). Underrepresented students in STEMM were more likely to be in profile 2 relative to profile 3. First-generation college students were more likely to be in profile 4 than profile 3. Finally, students likely to be in profile 3 had higher final exam grades than the other profiles and were more likely to graduate with a science major compared to profile 1. There were no differences in graduating science major between profile 3 and the other two profiles. Thus, profile 3 was most adaptive for both proximal (final exam) and distal (graduating with a science major) outcomes. Results suggest that supporting motivation early in college is important for persistence and ultimately the talent development of undergraduate STEMM students.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".