Information and communication technology use in higher education: Perspectives from faculty
Bibliographic record
Abstract
ABSTRACT The paper discusses how the faculty finds it difficult to apply their experiences in teaching and use of information and communication technology (ICT) for teaching and learning at the University of Botswana. Although technology was available and accessible, adopters of technology at the University of Botswana find it hard to use technology in teaching and learning, little research has been done on faculty experiences from a micro level (Instrumentalist) Product Utilization theoryâs perspective based on diffusion of innovation theory. The study explores faculty demographic information finding the technologies, artifacts and teaching methods they used. Nine participants took part in the study from the Department of Adult Education, Faculty of Education, at the University of Botswana by means of responding to an interview based on interview guide. The findings from the study shows that the majority of faculty use teacher-centered as compared to student centered approach, they used specific compatible technologies relevant to their teaching experiences in responds to the university systems mandates, and distance education using technology ultimately to online learning was very low due to lack of infrastructure in rural areas. The university administration should take into consideration understanding faculty from a bottom-up level as core effective implementers driving change. Keywords: ICT, e-learning, educational technology, higher education, University of Botswana, Micro level, Instrumentalist theory, Diffusion of Innovation theory, teaching and learning
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".