Determining the Effectiveness of Direct Instruction in Developing the Reading Skills of Students with Autism Spectrum Disorder
Bibliographic record
Abstract
This research assessed the effectiveness of the Direct Instruction Program in developing the reading skills of students with Autism Spectrum Disorder (ASD). Qualitative research methodology of phenomenology and focus group discussion were utilized to gain an in-depth understanding of the personal experiences of the research participants. To achieve this, the researcher conducted in-depth interviews with the participants. Upon analyzing the gathered data, Direct Instruction (DI) manifested that it has helped in developing the reading skills of students with ASD as a promising approach. However, the participants noted that there are some strengths and challenges associated with its implementation. By creating learning experiences that are tailored to the needs of the individual student, DI can help students with ASD improve their reading skills significantly. Modifications are needed to ensure that the lessons are personalized and that they meet the unique needs of each student. The modifications might include simplifying the script, using pictures, and providing additional support to help students understand the material.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".