Developing the Ability to Solve Mathematics Problems ‘Polygons’, Through Open Approach Learning Management for Sixth-Grade Students
Bibliographic record
Abstract
This action research aims to develop the ability to solve mathematical problems, particularly in polygons, through open-approach learning management for sixth-grade students, with the goal of achieving an average score exceeding 70% of the total possible score. The target group consisted of eight students in the second semester of the academic year 2023. Data collection tools included lesson plans, mathematics problem-solving ability tests, student behavior observation forms, and student journal logs. The data were analyzed using statistical methods, including percentages, means, and standard deviations. The findings showed that an open approach to learning management can effectively enhance mathematical problem-solving skills. Furthermore, it was observed that the students demonstrated various problem-solving approaches, actively engaged in group and inter-group learning exchanges, displayed confidence in problem-solving, and improved their mathematical problem-solving abilities.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".