Gender Dimension in the Development of Effective Teaching Skills among University of Cape Coast (Ucc) Distance Education Students
Bibliographic record
Abstract
The study examined gender dimension in the development of effective teaching skills among distance education (DE)students. The conceptual framework for the study is gender mainstreaming which centres on pluralistic approach todiversity issues among both men and women. A longitudinal developmental research design was used for the study.A sample size of 376 distance education students made up of 173(46.01%) female and 203 (53.99%) male werepurposefully selected from 5 regional study centres of College of Distance Education, University of Cape Coast(UCC) across Ghana. Data was collected using the Teaching Practice (Practicum) Assessment Form ‘A’ of UCC.The two research questions sought to find out the performance of male and female DE students on On-CentreTeaching Practice (OCTP) and School-Based Teaching Practice (SBTP) respectively. Five hypotheses were alsoformulated to guide the study. Results of the study revealed that the teaching skills acquired by both male and femaleDE students during OCTP and SBTP were good. However, a statistically significant difference exists between theteaching skills acquired by male and female DE students. Similarly, gender was found to have effect on theacquisition of teaching skills. It is recommended that all policy makers in the area of teaching practice should bemindful of gender issues in the development of teaching skills. Institutions involved in training teachers usingdistance education mode should stress the four levels of effective teaching skills assessed in this paper formeaningful practical teaching during teaching practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".