The Influence of Infrastructure and Teacher’s Work Motivation on Student’s Learning Achievement
Bibliographic record
Abstract
This research aims to determine the influence of infrastructure and student learning motivation on the learning achievement of SMPN 01 Jayapura OKU Timur. This type of research is quantitative research with a research design using an ex post facto research design. The sample in this study were students of SMPN 01 Jayapura, East OKU Regency, class IX, and class VIII groups A-C, totaling 114 students. The data collection technique used a questionnaire. Data analysis techniques use quantitative descriptive analysis techniques and multiple regression. The results of this research state that there is there is significant influence partially and jointly between infrastructure and teacher’s work motivation on student’s learning achievement at SMPN 01 Jayapura OKU Timur. It implies to all stakeholders of education in Indonesia to pay more attention toward infrastructure and work motivation to gain good student’s learning achievement.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".