Learning From Interactive Whiteboard Instruction Technology in Teaching Students With Autism Spectrum Disorders
Bibliographic record
Abstract
Interactive whiteboard instruction technology provides interactive learning environment and serves as a motivational tool for the students. The study aims to investigate the effectiveness of interactive whiteboard (IAW) to teach early numeracy skills to the ASD students. The study has employed single-case design methodology and evaluated students for the effectiveness of using interactive whiteboard for teaching skills to the students through multiple probe design. A total of five baseline sessions were conducted on total four recruited students. During the intervention, data was obtained for at least three sessions from the date each student reached the acquisition criteria. The results showed that introduction of the intervention resulted in all participants meeting the established criteria. The early numeracy skills were generalized by all the four students to a different setting and with different materials. These results have supported the effectiveness of the interactive whiteboard, coupled with DTT to teach early numeracy skills to students with ASD. The study has concluded that interactive whiteboard with DTT was effective to teach early numeracy skills to the ASD students.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".