Facilitating Academic and Mental Health Resilience in Students with a Learning Disability
Bibliographic record
Abstract
This qualitative study explored the educational journeys of five postsecondary students with learning disabilities (LD) from the perspective of the students and their families. Using a resilience lens, it examined the challenges that they faced and the capacities and resources that facilitated their resilience and helped them achieve their current level of academic achievement and mental health. A retrospective, multiple case study design was used, and a series of three interviews was conducted with each university student with an LD and their families. The participants identified a number of interactions among the students and their parents, teachers, and peers that helped shape and develop the capacities they needed in order to negotiate for the supports and resources that sustained their well-being. These capacities included an awareness and acceptance of their LD and themselves as learners, the self-advocacy skills they needed in order to seek out and negotiate for the supports and accommodations that would help them succeed, the ability to set lofty yet attainable goals, the perseverance to work toward these goals in spite of setbacks and challenges, and the willingness to use the supports and resources that were available to them.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".