Developing Student-Centered Learning Model to Improve High Order Mathematical Thinking Ability
Bibliographic record
Abstract
The purpose of this research was to develop student-centered learning model aiming to improve high order mathematical thinking ability of junior high school students of based on curriculum 2013 in North Sumatera, Indonesia. The special purpose of this research was to analyze and to formulate the purpose of mathematics lesson in high order mathematical thinking ability and also to develop and to try-out the learning model developed. The subject of the research was 7th graders from state and private Junior High School in Medan and Deli Serdang, which were taken proportional randomly. It was elected SMP N 36, SMPN 2 Tembung, and private SMP Bandung Bandar Khalifah. This developmental Research that orientated on developing product was done in three steps. From the first step, it was revealed that either lesson preparation (students’ book, teachers’ guided, and lesson material) or the instrument was judged valid and need only a little revision. Analysis on data revealed that the students’ high order thinking ability especially in mathematical problem solving, mathematical understanding, and mathematical communication enhanced significantly. By analysis, the reliability of instruments on mathematical understanding, mathematical problem solving, and mathematical communication ability was categorized good.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".