Effects of Three Combined Reading Instruction Devices on the Reading Achievement of Adolescents with Mild Intellectual Disability
Bibliographic record
Abstract
Upon entering high school, students with ID who may be able to read simple texts often have difficulty grasping meaning when required to understand more complex texts. This failure affects their overall academic performance, since at this age, it is no longer just a question of learning to read, but rather of reading to learn, in all disciplines. To date, only a very small number of studies have described the types of instruction essential to promote reading comprehension among adolescents with ID; none provide teachers with guidance on how to implement optimal evidence-based instruction. This paper presents the results of an intervention design combining three reading instruction devices with regard to the reading achievement of students with MID. Developed through a collaborative research project, this approach showed promise when used in an experimental context. While outcomes did not quite correspond to what was expected in terms of significant improvement in comprehension, significant effects were observed, especially in relation to phonics and accuracy. Practical implications and recommendations for future research are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".