TPS as an Effective Technique to Enhance the Students’ Achievement on Writing Descriptive Text
Bibliographic record
Abstract
Students’ achievement in writing descriptive text is very low, in this study Think Pair Share (TPS) is applied to solve the problem. Action research is conducted for the result. Additionally, qualitative and quantitative techniques are applied in this research. The subject of this research is grade VIII in Junior High School in Indonesia. From this study, the mean of the first evaluation sharply increased to the mean of the second evaluation and to the mean of the third evaluation. They are 66.4375, 78.125 and 87.5625 respectively. Observation result showed that the students gave their good attitudes and responses during teaching and learning process by applying the application of TPS (Think Pair Share) technique. Questionnaire and interview report showed that students agree with the application of TPS (Think Pair Share) technique have helped them in writing descriptive text. It can be conclude that the students’ achievement is improved when they are taught by TPS Technique.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".