Gender Differences in Attitude towards the Learning of Agricultural Science in Senior High Schools in the Assin South District of the Central Region, Ghana
Bibliographic record
Abstract
Agriculture has predominantly been observed as the activity of men with little or no interest by women hence this study was conducted in two public senior high schools in the Assin South district of the Central region of Ghana aimed to investigate gender differences in attitude towards the learning of agricultural science. A sample of 198, comprising of 188 students and 10 teachers of agricultural science took part in the survey. The research instrument used for the data collection was questionnaire which was developed by the researchers in two different forms, one for the agricultural science students and the other for the agricultural science teachers. Research findings from the study indicated that gender had no significant influence on students’ attitude towards the learning of agricultural science. Also, the attitude of female students towards agricultural science as a profession is not different from that of the male students. The study again concluded that teachers and parents play a key role influencing students to pursue related science courses. However students should be given the room to express their choice of programme to pursue at the senior high level. It must be reiterated that teachers have a major role to play in increasing and sustaining the interest of students in the study of agricultural science. The study recommends that students especially females should be encouraged, towards building a positive attitude in learning of agricultural science to take up major future roles related to the field.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".