Developing a Measure of Fatigue for Deaf and Hard of Hearing Students
Bibliographic record
Abstract
Fatigue is a prevalent issue in school-aged children and has been shown negatively impact well-being and academic performance. This is especially the case for deaf and hard of hearing (D/HH) students, who must produce greater auditory and visual efforts than their hearing peers, leading to greater levels of cognitive and physical fatigue. At present, there exists no standardized measure of fatigue that can be used in schools to specifically evaluate fatigue in students, let alone those who are D/HH. Such a measure would be incredibly valuable as it would allow for accurate identification of fatigue, allowing for supports and interventions to be implemented. The present research aimed to identify strengths and weaknesses of existing measures of fatigue in order to inform the construction of a measure that would specifically address fatigue in D/HH students. It was found that fatigue has largely been determined to be best assessed using a unidimensional measure with responses based on a 5- or 7-point Likert scale. Additionally, it was found that the development of measures usually follows the same general process. Items included in measures are typically generated based on focus-group interviews, then preliminary items are administered to a test group. Statistical tests are conducted based on the data generated to reduce the number of items, as well as to ensure reliability and validity. The next steps of this research will be to conduct focus group interviews to aid in generating preliminary items. Presented in absentia on April 27, 2020 at Student Research Day at MacEwan University in Edmonton, Alberta. (Conference cancelled) Faculty Mentor: Natalia Rohatyn-Martin Department: Biological Sciences
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".