Pre-Service Class Teacher’ Ability in Solving Mathematical Problems and Skills in Solving Daily Problems
Why this work is in the frame
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Bibliographic record
Abstract
<p>This study aims to investigate the ability of pre-service class teacher at University of Petrain solving mathematical problems using Polya’s Techniques, their level of problem solving skills in daily-life issues. The study also investigates the correlation between their ability to solve mathematical problems and their level of problem solving skills in daily-life issues. The study sample consisted of 65 female students majoring in class teacher. Data were collected using two questionnaires: the mathematical problem solving test which was developed by the researchers and daily life problem solving scale which was developed by (Hamdi, 1998). The findings indicate that students had high level skills in solving daily problems; there are no statistically significant differences in daily problem solving in relation to their academic year or high-school stream. Conversely, the findings also indicate weaknesses in students’ skills in solving mathematical problems, with no statistically significant differences among students in solving mathematical problems according to Polya’s problem solving steps. However, there were statistically significant differences in students’ performance in solving mathematical problems in relation to the mathematical topic, and in favor of measurements and algebra; in addition to statistically significant differences in students’ ability to solve mathematical problems in relation to academic year and high-school stream, but no correlation between students’ abilities in solving mathematical problems and those in solving daily problems.</p>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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