Improving Student Learning Outcomes in Aqidah Akhlak Learning at MTs S NW Tembeng Putik Through Active Learning Models
Bibliographic record
Abstract
This study aims to improve the activeness and learning outcomes of class II students of MI Yakti Ngadirejo in the subject of Akidah Akhlak by using the application of the mastery learning model. This study is a classroom action research consisting of three cycles. The subjects used in this study were 15 class II students of MI Yakti Ngadirejo. Each cycle consists of four stages, namely the planning, action, observation, and reflection stages. The instruments used to collect data were observation sheets, field notes, and daily test assessment sheets (evaluation). The results of the study showed an increase in student activeness in learning and student learning outcomes in the form of an increase in daily test scores from students who were used as subjects in this study. This increase occurred after students were guided in learning with the mastery learning model approach (complete learning). This is also supported by the results before and after the action. Thus, it can be concluded that learning with the mastery learning model approach is able to improve the activeness and learning outcomes of class II students of MI Yakti Ngadirejo in the subject of Akidah Akhlak.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".