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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".