PENERAPAN PEMBELAJARAN INKUIRI MODEL ALBERTANTUK MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIS MAHASISWA PADA MATA KULIAH KALKULUS 1
Bibliographic record
Abstract
AbstractThis study aims to enhance of students' mathematical problem solving ability at Calculus I through application of inquiry learning of alberta's model. This research is classroom action research. Subjects were students at Calculus I, amounting to 40 people. Analysis of the data used is the t-test to the data enhancement (N-gain) the ability of mathematical problem solving. The results of this study showed that the average increase (N-gain) the ability of students' mathematical problem solving in the first cycle is 0.43 (medium category) and the second cycle is 0.45 (medium category). These results indicate that the application of inquiry learning of alberta's model can enhance of students' mathematical problem solving ability at Calculus I. Key words: Mathematical problem solving ability, inquiry learning of alberta's model, classroom action research, Calculus I.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".