Performance Determinants of Kenya Certificate of Secondary Education (KCSE) in Mathematics of Secondary Schools in Nyamaiya Division, Kenya
Why this work is in the frame
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Bibliographic record
Abstract
The study found the performance determinants of students’ performance in mathematics Kenya certificate of secondary education (KCSE) in Nyamaiya division of Kenya. The study employed descriptive survey design of the ex-post facto type with a total student population of 151 and 12 teachers. Four validated research instrument developed for the study were Mathematics Achievement Test (MAT) (r = 0.67), Students Questionnaire (SQ) (r = 0.75), Teachers Questionnaire (TQ) (r = 0.60 and Head teachers Questionnaire (HQ) (r = 0.70). Three research questions were answered. The data was analyzed using multiple regression analysis. There was a positive correlation among the six independent variables and the dependent measure – mathematics performance(R= 0.238; F(6,151)=1.53843; p<0.05). The six variables accounted for 45.6% of the total variance in the independent measure (R2 = 0.564). Teachers’ experience (B=0.972, t=2.080; p<0.05), teachers’ qualification (B=0.182, t=2.390; p<0.05), teachers/students’ attitude (B=0.215, t= 2.821; p<0.05) and school category (B=0.064, t=0.352; p<0.05) could be used to predict students’ academic performance in mathematics. It is therefore recommended that adequate attention should paid to these variables that can predict students’ performance by the government and other stakeholders of education in Kenya.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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