Perceived Influencers of the Decline on Performance of Students in Botswana General Certificate of Secondary Education’s Agriculture Examination Results
Bibliographic record
Abstract
The purpose of the study was to investigate factors perceived to contribute to the decline of students’ performance in the Botswana’s General Certificate of Secondary Education (BGCSE) agriculture results. Ninety-one agriculture examiners were randomly sampled out of 100 teachers who were invited to mark the 2012 end of year examination scripts. A questionnaire was mailed by post and partly hand delivered to gather quantitative data. The SPSS software was used for statistical analysis. The results showed that majority (57%) of the agriculture teacher examiners were male, 66% were in the age range of 31-35 years old. A large proportion (66%) of them had taught for a period of 6 to 15 years. The study revealed positive perceptions of teachers on three constructs influencing the decline on the students’ performance in agriculture. The study revealed that under the construct, Students’ behaviors, social and economic related factors, students attitudes towards the subject yielded high mean (x̅)‘= 4.45, STD (σ) ’ = .81; on Factors related to curriculum issues, the study showed “interpretation of examination items” had high mean (x̅) ‘= 4.39, STD (σ) = .75 and under the construct on Factors related to resources and infrastructure the mean (x̅) was = 4.79, STD (σ) = .53 was high on the student teacher ratio. The study concluded that the three constructs studied had influence towards students’ performance in agriculture. However, based on interpretational correlations the results did not find any strong relationship among the demographic variables studied.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".