Teachers’ pedagogical skills and student readiness and achievement in data processing in senior secondary schools in Ibadan, Nigeria
Bibliographic record
Abstract
This study investigated the teachers’ pedagogical skills, students’ readiness, and achievement in data processing in senior secondary schools in the Ibadan metropolis, Oyo State. The correlational design was adopted in this study to establish the relationship among the variables of concern. We used a multi-stage sampling procedure to select samples. Data was gathered using the pedagogical skills rating scale, the student's readiness questionnaire and the data processing achievement test. Data collected from the respondents were analysed using frequency, percentage, graph, Pearson product-moment correlation, and multiple regression analysis. The study revealed the pattern of teachers’ pedagogical skills with regard to communication skills, evaluation skills, adaptability skills, inclusivity skills, and compassion skills, with compassionate skills having the greatest percentage of value. The results further show the composite contributions of teachers’ pedagogical skills and students’ readiness, having a significant contribution to achievement in data processing. Also, there was no significant relative contribution of teacher pedagogical skills, while there was a significant contribution of student readiness to achievement in data processing. It was recommended that the government should not relent in providing appropriate training and seminars to improve teacher pedagogical skills, while students should work hard to attain positive achievement in data processing.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".