The Effect of Two Stay Two Stray and Think Pair Share Techniques on Students’ Speaking Skills at Grade XI of Madrasah Aliyah Swasta Al Manaar
Bibliographic record
Abstract
This investigation tries to ascertain The Effects of the Two Stay Two Stray and Think Pair Share Techniques on Class XI Students at Al-Manaar Private Madrasah Aliyah's Speaking Skills The goal of this study was to ascertain and evaluate the impact of the Two Stay Two Stray and Think Pair Share Techniques on the Speaking Skills of Class XI Students at Madrasah Aliyah Al-Manaar Private. It is a quantitative form of study. Pre-test, post-test, control group design describes the research methodology used in this study. Students in class XI at Madrasah Aliyah Al-Manaar Private made up the population of this study. The class XI 2 MIA 25 students who were chosen for the study's sample using non-purposive sampling served as the study's sample population. employing essay tests as a data collection method. Testing is divided into two tests, namely pre-test and post-test. They were carried out to find out the students' speaking skills before and after receiving treatment. This study uses the Man Whitney and Kruskal Wallis formulas to analyze research data. The results show that Mean TPS > Mean TSTS or 26.56 > 14.24. This means that Ha is accepted and H0 is rejected, "there is a significant difference between the average Two Stay Two Stray and Think Pair Share techniques on students' speaking skills". The calculation results of the three groups obtained the value of H = 291 and H table = 101 which means that H0 is rejected and Ha is accepted, meaning that "there is a significant effect between Two Stay Two Stray and Think Pair Share on students' speaking abilities.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".