Postsecondary Students with Specific Learning Disabilities and with Attention Deficit Hyperactivity Disorder Should Not be Considered as a Unified Group For Research or Practice
Bibliographic record
Abstract
Objective: To examine similarities and differences among college/university students with ADHD, LD, and comorbid ADHD and LD on variables related to academic performance. Method: Students who self-reported ADHD ( n =42), LD ( n =72), or comorbid ADHD and LD ( n =42), completed an online questionnaire which evaluated grades, parental education, course and social self-efficacy, and personal and school related obstacles and facilitators. Results: Students with ADHD (with or without comorbidity) reported the worst grades, personal situations (e.g., study habits, personal motivation), and course-related self-efficacy (e.g., time management, keeping up-to-date with school work). The single exception was that students with ADHD had more confidence in understanding textbooks than students with LD. Comorbid ADHD and LD sometimes led to worse outcomes than LD or ADHD alone. Conclusion: The common practice of combining all three groups, “LD and/or ADHD”, should be avoided. Suggestions are made about what could be done to help students with ADHD.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".