How Gaps between Target and Midcourse Grades Impact Undergraduates’ Studying Intentions and Grade Improvements*
Bibliographic record
Abstract
ABSTRACT We examine how gaps between students’ chosen target grades and actual midcourse grades relate to their exam studying intentions and subsequent grade improvements. We further investigate whether those relationships are moderated by students’ academic ability (as measured by high school averages) and implicit theory of intelligence or mindset (as measured by questionnaire scores). Our study involved 250 undergraduate students in a first‐year business course. The study used linear regression to analyze survey responses at the course's beginning, survey responses near the course's end, and actual course grades. The analysis showed students had greater studying intentions and grade improvements when midcourse grades were farther below initial target grades. Mindset moderated the relationship between grade gaps and studying intentions, whereas academic ability moderated the relationship between grade gaps and grade improvements. These results enhance our knowledge of how students respond to grade feedback and could help instructors assist students to make better decisions about their studying.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".