The Experience of Transition to College for Students Diagnosed with Asperger’s Disorder
Bibliographic record
Abstract
Background: Obtaining a college degree is a positive and often necessary step to adulthood, independence, and knowledge. Students diagnosed with Asperger’s Disorder (AD) typically experience difficulty in college, especially in the transition to college. To assist students with AD in the transition to college, an occupational therapy mentoring program was developed in a college setting. This article describes this program, provides quantitative and qualitative outcomes of the program, and uses the outcomes to determine factors to facilitate a successful transition. Method: A mixed methods design with quantitative and qualitative components was used. The quantitative measures included the Canadian Occupational Performance Measure (COPM) and data on college retention, and the qualitative measure consisted of in-depth progress note documentation throughout the program. Results: Eleven participants met criteria for the study. There was a statistically significant difference between COPM pretest and posttest scores on performance (p. = .000) and satisfaction (p. = .000). Nine of the 11 students confirmed college retention. Three themes regarding college transition included (a) maladaptive patterns linked to the characteristics of AD, (b) adaptive patterns linked to the characteristics of AD, and (c) parental influences. Implications for positive transition are proposed based on the findings. Conclusion: Students with AD can succeed in college, especially with a combination of internal characteristics and external supports.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".