Computer Instructional Approach and Students’ Creative Ability in Sculpture Education in Nigeria Universities: Obafemi Awolowo University as a Case Study
Bibliographic record
Abstract
This paper assessed the use of computer assisted instruction in enhancing students’ creative ability in sculpture education in Obafemi Awolowo University, Ile-Ife. The study adopted non- randomized pretest, posttest control group. Data were analyzed using mean, standard deviation and analysis of Covariance (ANCOVA). The mean score were used in testing the only research hypothesis. There was no significant difference in students’ creativity ability in sculpture when taught using computer instructional and conventional approach. The results of data analysis using Analysis of Covariance (ANCOVA) and scheffe post – hoc showed that students with high and average creative ability benefited most than their counterparts in conventional teaching methods. It was concluded that application of computer in learning environment has significant influence on the student’s performances in sculpture.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".