Tumu College of Education trainee teachers’ perceptions of mentors’ pedagogical knowledge
Bibliographic record
Abstract
The study accessed the perceptions of final year students in the Tumu College of Education towards the Pedagogic Knowledge (PK) of their mentors. It also investigated whether statistically significant differences existed in terms of mentees’ gender and programmes of study regarding the pedagogic knowledge of their mentors. The study used a census method to collect data from respondents for the study by distributing a closed-ended five-point Likert scale on Perceptions of Knowledge and Skills in Teaching (PKST) Questionnaires to all 215 students pursuing Early Grade and Primary Programmes, with an 84.2% (181) return rate. However, 175 respondents’ data were used, as six of the questionnaires contained incomplete data. Findings of the study revealed that participants perceived their mentors as having a high measure of PK, with an overall mean value for the student teachers ‘perceptions of their mentors PK of 3.62 (SD =.77). The study also revealed that there was no statistically significant difference in the perceptions of student teachers towards the PK of their mentors in terms of gender or programme of study. However, the study revealed that participants perceived their mentors to be less competent in effectively incorporating information and communication technology (ICT) in the classroom. It is recommended that the Ministry of Education and Ghana Education Service organise capacity building workshops for teachers to improve their competencies in integrating ICT in their classrooms.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".