Influence of Learning Model Using Laboratory and Numeric Ability to Student Learning Result on Thermochemical Material
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to determine the influence of learning models and numerical ability of students’ chemistry learning outcomes on Thermochemical materials, as well as the interaction between learning models through the use of laboratory and numerical ability. The study was conducted on the students of grade XI IPA SMA N 1 Stabat consisting of 9 classes and 2 classes as samples taken by purposive sampling. Experimental research with factorial 2 × 2 factorial ANOVA design. Learning result data obtained from result of thermochemical learning result and student numerical ability data obtained through numerical ability test which have all been validated. The data analysis technique used two way analysis of variance (ANOVA). The result of the research shows that the influence of the learning model using the laboratory on the students’ learning outcomes on thermochemical materials with Fcount> Ftable is 4.015> 3.99, there is the effect of high numerical ability and low numerical ability to the chemistry learning result on thermochemical material with Fcount> Ftable value is 23.717 > 3.99 and there is interaction between learning model using laboratory with numerical ability to result of thermochemical learning with value Fcount>Ftable that is 11.142>3.99.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it