The Dominant Factor of Teacher’s Role as A Motivator of Students’ Interest and Motivation in Mathematics Achievement
Bibliographic record
Abstract
This study aims to identify the most dominant factor of the teacher’s role as a motivator that influences students’ interest and motivation to perform in mathematics achievement. It is conducted in eighth grade of senior high school with 209 students, consisted of five state schools and two private schools from seven regencies in North Sumatera. The data collecting technique uses questionnaire about students’ interest and motivation toward mathematics and teacher’s role as motivator. Numerical data on mathematics achievement of students is obtained from school documents. The result of data with path analysis is obtained by dominant factor of teacher’s role as motivator that is factor of delivery of learning goal and learning comfort equal to 6.10%, and 6.00% is influenced by the delivery of learning objectives and variations of learning approaches, 5.17% is influenced by the delivery of learning objectives, 5.06% is due to variations in the learning approach, 4.61% is influenced by learning comfort and variation of learning approach, and 4.26% influenced by pleasant class atmosphere.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".