Effectiveness of a Computerized Program in the Treatment of Dyslexia in a Sample of Fourth Grade Students
Bibliographic record
Abstract
Dyslexia is a specific learning disorder which has a neurobiological origin and is characterized by the presence of reading difficulties not accounted for by sensory, neurological, or intellectual deficits. Many researches indicated have conducted to study the effect of a computerized program to help students with dyslexia as it has proven its effectiveness in many fields. This study aimed to test the effectiveness of a computerized program in the treatment of dyslexia among the fourth grade students in a sample of Jordanian schools. The study sample consisted of (90) students in the fourth grade for the academic year 2017/2018. They were divided into two groups: a control group and an experimental group: 35 students and 55 students. This study was conducted through the introduction of an educational program to develop reading skills to address the difficulties of learning in reading, where learning is a necessary requirement because of its importance in the lives of students, so it was necessary to focus on learning to read to students at different levels of special needs, including those with learning disabilities who They may need some methods and strategies that suit their different learning styles. Therefore, this study came within the framework of teaching reading for people with learning difficulties in the basic stage. Provide teachers with training skills by training them in the use of the computer program in teaching reading skills, providing a theoretical background on the phenomenon of learning difficulties, especially in the field of reading, its causes and educational strategies for people with learning disabilities, and this helps to provide the necessary educational care for them.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".