Building Learning Trajectory Mathematical Problem Solving Ability in Circle Tangent Topic by Applying Metacognition Approach
Why this work is in the frame
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Bibliographic record
Abstract
Mathematical problem solving ability is one of the most important abilities students must have to process the information provided in solving problems. Before using mathematical problem solving skills, prior knowledge becomes the most crucial thing that makes students able to connect all available information so that they can construct new knowledge through the process of assimilation or accommodation.The purpose of this reseach is to:(1) Analyze prior knowledge what student has so the student can solve the problem of tangent circle given; (2) Know how learning trajectory in student’s mathematical problem solving ability by applying metacognition approach. This reaseacrch is a design research to improve the quality of learning. In this reseacrh researchers gave 3 test questions on students’ mathematical problem solving abilities. One trial was conducted in class VIII-B and trial II was conducted in class VIII-A, each consisting of 30 students junior high school. The result of students answer analysis shows the mast problematic topic that makes the studnts are difficult to solve the problem is about the tangent cicrcle that is the elements of the circle and the concept of circle circumtance there are three phased in learning path of students mathematical problem solving skill that are under standing the problem, making the problem solving plan by prrior knowledge and doing problem solving and evaluating it. From this explanation, it is better for teachers to ensure students have sufficient prior knowledge to make it easier to construct new knowledge, as well as make the learning process fun and meaningful so that students will remember knowledge in long-term memory.
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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 | 0.000 |
| 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