Factors Affecting School Administrators’ Choices in Adopting ICT Tools in Schools – The Case of Malaysian Schools
Bibliographic record
Abstract
The Malaysian Government has introduced various initiatives to facilitate the greater adoption and diffusion of ICT to improve capacities in the education system. Due to the extensive investment, schools are expected to utilize and integrate ICTs in administrative tasks, teaching and learning and general running of schools. This study was set out to examine the various factors that influence the use of ICT tools by the school administrators, to identify the process used to select adequate and suitable hardware and software to be utilized in schools and to identify the barriers to technology integration. The findings show the factors that influence the use of ICT tools in schools are willingness of teachers, high level of knowledge and skills, cooperation among teachers, easier and more effective completion of task, high level of trust and confidence placed on the teachers and importantly the good and regular maintenance of hardware and on-site support. This study also finds that lack of facilities, insufficient time to master and apply knowledge due to heavy teaching hours and attitudes of teachers who are not willing to change are the barriers to technology integration.
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.
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 | 0.009 |
| 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".