Students’ perceptions of their self-efficacy in mathematics in a public school in Kenya
Bibliographic record
Abstract
The purpose of this study was to find out students’ perceptions of their self-efficacy in mathematics. In the study, 104 form four students (83 boys and 20 girls) from a public rural coeducational school were surveyed using a modified version of Nielsen and Moore’s (2003) Mathematics Self-Efficacy Scale (MSES). Thereafter, eight students selected on the basis of their mean responses on the MSES were interviewed. Through descriptive statistics, it was found that students’ self-efficacy percepts in mathematics varied from 15 to 50 on a scale of 10 to 50. About one quarter of the students were found to be highly efficacious in secondary school mathematics. Meanwhile, boys were more efficacious than girls. At the same time, the variation in the strengths of students’ self-efficacy percepts in mathematics was attributed to the interpretations that the students gave to the various indicators of capability in mathematics that operated in their environment. It is recommended that teachers use the MSES to measure their students’ self-efficacy percepts in mathematics, and thereafter, use interviews to identify the underlying sources of the self-efficacy percepts in order to institute intervention strategies that will work best in their particular contexts so as to enhance students’ self-efficacy percepts in mathematics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".