Enhancement of Creativity in Math Skills of People with ID in Education Process
Bibliographic record
Abstract
This paper describes the enhancement of the math skills of people with ID in the education process and development of the mathematics methodology. As well this research gives details of its piloting and evaluation with a cohort of learners with ID who were enrolled in an education course. The objective of the correctional school is to provide learners with the necessary math training, to introduce them into the big world of math, to make it an effective means of learning about the surrounding reality, development of thinking and moral perfection. All of the above determines the relevance of the problem of math education of children with mental retardation in the circle of calculations. The aim of the study is theoretically substantiated and experimentally test the system of correctional and pedagogical work on the math education of younger school children with intellectual disabilities in circle math classes. Learners with intellectual disability (ID) have to overcome many barriers and difficulties in order to access all levels of education and partake in college life. Thankfully, educational institutes around the globe are slowly beginning to examine how they can support the equal rights of individuals with ID. In Kazakhstan, one university has recently accredited an innovative education program for college learners with intellectual disabilities. The results of the study are presented by the emergent methodology’s which focuses on mathematics and realizes the important role that numeracy, which plays a great role in today’s society. Despite the increased emphasis on general mathematics education, the authors found there to be a dearth of research regarding the development of such a methodology for learners with ID.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".