The Implementation of the Polya Method in Solving Euclidean Geometry Problems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research is aimed at analyzing the solutions of Euclidean Geometry problems using the Polya method. This present study was made through qualitative and quantitative approaches with 85 respondents of the second semester students at the Department of Mathematics Education, University of Muhammadiyah Malang Indonesia, in the 2012/2013 academic year. The quantitative study was made through instruments used to understand students’ responses to the implementation of the Polya method and to know their capabilities in solving two Euclidean Geometry problems. All instruments before being applied were tested for their validity and reliability, and the tests show that the instruments have fulfilled validity and reliability requirements. Qualitative study was made to reinforce the results through interviews to 6 students chosen from those in the low, medium and good levels. The results show that in terms of their understanding of the problems, majority students are good. Dealing with the planning of problems solution, the results show that the majority students made such plans. Then for the carry out the plan, all students did implementation, but for look back, most students did not make any review.
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.
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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it