The Effects of Deductive Learning Activities With Games on the Topic of “Single Variable Linear Equations” of Mathematics on Learning Achievement of 7th Grade Students
Bibliographic record
Abstract
The purposes of the research were 1) to compare the scores of 7th grade students from deductive learning activitites managaement with games on the topic of “Single Variable Linear Equations” to the standardized criteria of 75%, 2) to compare the achievement of the 7th grade students before and after using the deductive learning activities with games, and 3) to study the satisfaction of the students with the deductive learning activities with games. The research samples were twenty-eight 7th grade students of class one at Triam Udomsaksa Patanakarn Roi-Et School in the second semester of 2021. They were selected by cluster random sampling method. The research instrument consisted of lesson plans, an achievement test, a questionnaire, a recording form after teaching and an observation form. The statistics used were mean, standard deviation, percentage, one-sample t-test and t-test for dependent. The research results indicated that compare the mean score of 7th grade students from deductive learning activitites managaement with games on the topic of “Single Variable Linear Equations” was higher than the standardized criteria of 75% at the .05 level of the statiscal significance. 2) The findings revealed that the mean postet score after using deductive learning activitites managaement with games was higher than that of the pre-test score at the .05 level of the statiscal significance. 3) The overall satisfaction of the student with the deductive learning activities with games was at a high level.
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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 | 0.002 | 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 | 0.001 |
| 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".