Measuring Students’ Perceptions of Teacher Involvement in Mathematics Homework Assignments: A Scale Development
Bibliographic record
Abstract
This study aimed to develop a scale to determine students’ perceptions of teacher involvement in mathematics homework assignments. An item pool (n = 30) was generated based on a literature review. Based on expert feedback, the number of items was reduced to 21 scored on a 5-point Likert-type scale. A draft named the “Scale of Teacher Involvement in Mathematics Homework Assignments (STIMHA)” was developed after the items were reviewed by a linguist. A pilot study was conducted with six middle school students to check for comprehensibility. The items were revised and finalized based on their feedback. The main study sample consisted of 751 middle school students from four schools in Demirci/Manisa in Turkey during the 2017-2018 academic year. Data were analyzed using the Statistical Package for Social Sciences (SPSS 24.0) and Analysis of Moment Structures (AMOS 21.0). Validity and reliability were established.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".