Online Learning for Students with Learning Disabilities and Their Typical Peers: The Association between Basic Psychological Needs and Outcomes
Bibliographic record
Abstract
Abstract For some students, online learning, particularly as it relates to the COVID‐19 pandemic, can have negative implications for self‐efficacy, fatigue, and burnout. One way to combat these negative outcomes is for institutions to support students’ basic psychological needs (BPNs) of autonomy, relatedness, and competence. However, online learning may also frustrate students’ BPNs, particularly if they have a learning disability (LD). The purpose of the current study was to investigate the satisfaction and frustration of BPNs in relation to self‐efficacy, fatigue, and burnout for students with and without LD. We surveyed postsecondary students about their courses online and examined differences between students with LD and their typical peers. We also examined BPN satisfaction and frustration as predictors of self‐efficacy, fatigue, and burnout. Recommendations are provided from a universal design for learning perspective. Moreover, limitations and future research directions are discussed.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".