Measurement of Assistive Technology Outcomes Associated with Computer-Based Writing Interventions for Children and Youth with Disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Young people who have chronic disabilities use computer technologies and receive rehabilitation services to overcome functional limitations associated with writing activities. However, the functional impact of these specialized assistive technologies on the everyday lives of children is not clearly understood; in part due to the lack of targeted outcome measures. This article describes the development and evaluation of the Family Impact of Assistive Technology Scale for Writing Interventions (FIATS-WI). The FIATS-WI is a multi-dimensional, parent-report questionnaire designed to measure child functioning and outcomes associated with computer-based writing interventions for children and youth aged 5–18 years. Participants included parents of children with writing-related disabilities who completed the questionnaire at home during one of two study phases. In the first phase, 121 eligible parents, out of 364 invited, completed a single administration of the questionnaire. In the second phase, 28 out of 33 eligible parents completed the FIATS-WI twice to assess its stability. Item and subscale correlations informed an item reduction plan, and Cronbach’s alpha and intraclass correlation coefficients provided acceptable estimates for internal consistency and test–retest reliability, respectively. Correlations between FIATS-WI scores and scores from a standardized home participation measure tested its convergent validity. The study provides emerging evidence for the FIATS-WI as a sound measure of computer-based writing technology outcomes for children and youth with disabilities.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it