EXAMINING THE IMPACT OF COOPERATIVE LEARNING STRATEGIES ON STUDENT PERFORMANCE IN GEOGRAPHY, NINE YEARS BASIC EDUCATION PROGRAM, GS MUSHERI, MUSHERI SECTOR, RWANDA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study concerns the impact of cooperative learning on students’ performance in Geography in nine years of primary education in Musheri Sector. The study used a descriptive survey design; 46 subjects were used as a sample from 230 as a target population. Stratified sampling and purpose sampling were used to get the sample size, questionnaires and interview guides were used to collect data, and Microsoft Excel was used to analyze the data. The study found that teachers use different cooperative learning methods, including jigsaw, think pair share, three-minute review, teamwork and group performance. The study found that 17.4% of the respondents revealed that teachers use round tables as the simple cooperative learning structure used in the G.S Musheri, enabling them to cover much content, build team spirit, and incorporate writing. Of 46 respondents, 36.9% indicated that the teacher's negative attitude led to the lack of effective use of corporative learning in the classroom. This was brought up by the issue of lack of teachers' motivation. The study recommends having assessments such as daily competitions, quizzes, tests, and other types of assessments to increase student performance. The study recommended that the government train teachers on cooperative learning skills as one way of helping students acquire knowledge, skills and attitudes and also to have continuous professional development for teachers on teaching and learning methods.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0977/a.php" alt="Hit counter" /></p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it