Factors That Influence English Teachers’ Acceptance and Use of E-Learning Technologies
Bibliographic record
Abstract
The world has witnessed a major pandemic that has threatened the status of education across the globe. Such a crisis highlights the importance of education technology, which has not been an influential part of Kuwait’s education until the onset of COVID-19. Delays and interruptions of the academic year disrupted the lives of many students around the world, including Kuwait. Since e-learning technologies are not traditionally used in Kuwaiti higher education, this study aims to investigate the acceptance of technology and whether that has changed with the pandemic. It seeks to find useful strategies that could assist teachers in effectively using electronic distance-learning digital resources. The Unified Theory of Acceptance and Use of Technology (UTAUT) has been developed to investigate the degrees of usage and acceptance of technology. This paper adopts an improved model that also includes the educational experience of teachers, in an attempt to understand the context of Kuwaiti higher education. Therefore, this quantitative study examines the use and acceptance of educational technologies of English language instructors in higher education. The study uses an online survey among 33 English language instructors at the Public Authority for Applied Education and Training (PAAET) to also account for the perceptions and experiences of the teachers. The results revealed an overall high acceptance level of educational technology, with varying degrees of implementation.
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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 | 0.000 | 0.030 |
| 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 | 0.000 |
| 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".