College Instructors’ Theories of Intelligence and Awareness of Student Dyslexia as Related to the Feedback Provided for the Student’s Writing Assignment
Bibliographic record
Abstract
Research indicates that teachers' theories of intelligence (incremental vs. entity) are likely to affect their teaching practices, and some teachers hold lower expectations for students with learning disabilities. This study explored the relationships between college instructors' theories of intelligence and the feedback they provided based on a student's writing sample under two conditions: the student's dyslexia was mentioned versus not mentioned. One hundred and one college instructors completed a survey. Results of path analysis indicated the instructors who endorsed the incremental theory of intelligence gave significantly more encouraging comments than those who endorsed the entity theory. Instructors' theories of intelligence did not predict the grade assigned, the number of weaknesses pointed out, and the number of suggestions provided. The instructors informed of the student's dyslexia gave significantly higher grades than those not informed, but the instructors' feedback did not differ. No significant interaction between instructors' theories of intelligence and awareness of student dyslexia was found.
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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 | 0.004 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".