Enhancing Measurement Education in Schools: A Study on the Efficacy of STAD (Student Teams Achievement Division) in Undergraduate Mathematics Education
Bibliographic record
Abstract
This study examines the effectiveness of the Student Teams Achievement Division (STAD) cooperative learning technique in enhancing the teaching skills of mathematics pre-service teachers in the context of school-level measurement. The primary objectives were to assess the impact of STAD on learning achievement related to measurement concepts and to investigate the learning experiences of participants. Employing a one-group pre-post test design, 25 mathematics education major students in a Thai public university engaged in STAD activities. The instruments were a set of learning activities designed using the principles of STAD (Student Teams Achievement Division), learning achievement test, and a satisfaction questionnaire. The results reveal that STAD significantly improved learning achievement and generated highly satisfactory learning experiences among the participants. Academic and pedagogical recommendations are made, while acknowledging limitations related to the need for qualitative data collection and the exploration of teaching evaluation assessments in future research. This study underscores the potential of STAD as a valuable tool in teacher preparation programs, contributing to the development of effective educators.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".