Integrating New Instructional Assistive Technology to Support Academic and Behavioural Instruction for Students with Learning 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
Assistive Technology can be a highly effective tool in supporting students with Learning Disabilities (LD) in addressing foundational academic skill gaps as part of academic and behavioural one-to-one instruction. However, there are barriers to administrators wanting to equip in-service educators to integrate assistive technology into special education contexts, such as in-service educators' technology acceptance and the need for effective in-service training. This article explores a model for supporting in-service educators to integrate assistive technology into an existing academic and behavioural one-to-one instruction program for students with LD through a partnership with a nonprofit educational provider and a university's social robotics laboratory. We applied a co-design approach and followed a human-centred design methodology, incorporating a technology acceptance model to support educators in broadly integrating assistive technology into existing research-based programs for students with LD.
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.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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