Students with LD at Postsecondary: Supporting Success and the Role of Student Characteristics and Integration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Students with learning disabilities (LD) are attending postsecondary education more than ever, but are also less likely to complete their education compared to non‐LD peers. Using the Inputs–Environment–Outcomes model of Astin, we examined students with LD and non‐LD peers during their first year of postsecondary studies. Using structural equation modeling, we found that for all students, perceived academic ability had a positive direct effect on outcomes, whereas drive to achieve had only an indirect effect. Academic integration was important for grade point average and satisfaction. Social integration was important for the acquisition of knowledge and skills and satisfaction, and these connections were stronger for students with LD. Our discussion highlights potential supports for students with LD.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it