Examining the Lived Experience of University Students Receiving Academic Accommodations for Concussion
Bibliographic record
Abstract
Purpose. The present study aimed to gain insight into the lived experiences of post-secondary students with concussion(s) who are receiving academic accommodations. This was explored in the context of the COVID-19 pandemic, where the shift to online learning became ubiquitous. The purpose was to determine whether university students with concussion face similar challenges compared to (1) younger populations of students with concussion (i.e., elementary and high school aged students) and (2) individuals with more severe Traumatic Brain Injuries (TBIs). Method. Nine university students who were registered with academic accommodations at a Canadian university engaged in semi-structured interviews. Interpretative Phenomenological Analysis was used to inductively analyze the interview data. Results. Student experiences with their academic accommodations were mixed; the transition to online learning resulted in both new barriers (i.e., test-taking difficulties with Proctortrack) and the amplification of pre-existing barriers (e.g., an exacerbation of concussion symptoms due to increased screen time). Factors that were often beyond students’ control (e.g., faculty and familial support, financial resources) affected whether students felt well-accommodated in their classes, and created discrepancies across students in the provision of accommodations. Faculty members, peers, and friends of students who had more concussion-related knowledge were more readily supportive and accommodating. Students who exhibited personal resourcefulness fared better overall and engaged in less catastrophizing. Conclusions. Barriers to accessible education in students with concussion in the post-secondary setting exist and have been amplified by the shift to online learning. Potential areas for intervention at the individual and systems levels 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".