The Effectiveness of Touch Math on Improving Early Mathematics Ability of Kindergarten Children with Mild to Borderline Intellectual Functioning in an Inclusion Classroom
Bibliographic record
Abstract
Touchmath®, also known as Touchpoint, is a multi-sensory method that involves visual, auditory, and tactile learning, and it can be used effectively with children with disabilities. It has successfully solved addition and subtraction problems with a single digit and two digits, specifically for children with disabilities. Six children participated. A multiple baseline design was used. The Test of Early Mathematics Ability was employed. The findings revealed that the touch math training program effectively improved the Early Mathematics Ability of each participant. All six children were found to be successful at the end of the teaching session compared to the baseline. The finding that Touchmath® showed positive effects based on a direct teaching approach in improving the Early Mathematics Ability of kindergarten children with mild to borderline intellectual functioning and their typically developing peers in an inclusion classroom is effective, sustainable, generalizable, and socially valid in teaching basic addition skills to students with mild intellectual disabilities in general education classrooms, conforms to other research conclusions in the literature.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".