Factors Affecting Technology Integration in EFL Classrooms: The Case of Kuwaiti Government Primary Schools
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous Computer Assisted Language Learning (CALL) research has shown that technology is beneficial for promoting language learning, but some teachers neither use technology as an assisted tool nor integrate it into their language classrooms. It has also been argued that the integration of technology has been unsuccessful in Kuwait. This study aims to explore the factors influencing teachers’ use of technology in English as a foreign language (EFL) classroom in Kuwaiti government primary schools. More specifically, it aims to highlight factors promoting and hindering EFL teachers’ use of technology. For the purpose of this study, 55 questionnaire responses were collected from different primary school teachers in Kuwait, followed up with 15 semi-structured interviews. The study findings show that Kuwaiti primary school EFL teachers who participated in the current study demonstrated positive attitudes towards using technology and acknowledged the implementation of some cutting-edge technologies in their classrooms. Enhancing students’ language learning, innovation and school support were the main factors that encouraged the participating teachers to use technology. Other factors hindered the use of technology; particularly those related to lack of parental support, personal expenses and health problems, teachers’ lack of skills and training, poor classroom infrastructure, and time constraints/workload. The findings also reveal that the lack of professional development training workshops provided by the Ministry of Education led the Kuwaiti teachers to rely more on informal training in which they worked and learnt together with their colleagues in small sub-groups to improve their use of technology. The study findings have implications for policymakers and other stakeholders intending to integrate technology in Kuwaiti primary schools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 |
| 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 it