Autonomy support for the academic goal pursuit and subjective well-being of students with disabilities
Bibliographic record
Abstract
Students with disabilities often face greater challenges flourishing in postsecondary academic settings and achieving academic goals than their peers. Over an academic semester, 234 university students with registered disabilities (75.60% female, Mage = 22.30) were recruited to participate in a three-wave, longitudinal study. The present research utilized a Self-Determination Theory framework to examine how perceiving autonomy support (i.e., listening, providing choices and options) from close others related to psychological need satisfaction (i.e., feelings of autonomy, competence, and relatedness), progress on academic goals, and subjective well-being. Specifically, the results suggest that autonomy support was significantly related to psychological need satisfaction, goal progress, and subjective well-being. Results also suggest the relation of autonomy support to subjective well-being was mediated by psychological need satisfaction and goal progress. The findings have broader implications regarding the academic success and well-being of students with disabilities and aid in understanding how close others can provide meaningful support despite the difficulties encountered. Practical ramifications and directions for future research are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".