The Influence of Parents’ Involvement on Children with Special Needs’ Motivation and Learning Achievement
Bibliographic record
Abstract
Some of the abnormal children face burden, distraction, interruption, tardiness, or risk factors so that they cannot get an optimum growth without special treatment or intervention. This study was aimed at discovering the influence of parents’ involvement to the learning motivation and achievement of children with different abilities. This research is a regressive model. The population was children with different abilities in SMP Negeri 4 Gresik, East Java Indonesia. The data collected through questionnaire and documentation, were then analyzed using linear regression test. The t-test results showed tcalculate value for variables of parents’ involvement (X) was 3,813. The results showed that tcalculate>ttable or 3,813> 2,093 or t value is higher than t table. It means that parents’ involvement sigifcantly influences children’s motivation. The result of the t-test also indicated that tcalculate value for parents’ involvement (X) was 3,601. If compared to ttable, then, tcalculate>ttable or 3,601> 2,093. It means that there is an influence of parents’ involvement on children’s achievement as well. Based on the finding, it can be recommended that parents should be more intensive in assisting, accompanying, and guiding their children, especially especially to the children who have special needs so that their motivation and academic achievement can be enhanced. It is also recommended that teachers and school should give more fruitful collaboration between schools to facilitate their needs and potentials.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".