Information and Communication Technology among Excellent Islamic Education Teachers in Selangor Malaysia
Bibliographic record
Abstract
The development of technology in the era of the borderless world has grown rapidly in the entire field of human life, including in the field of education. The rapid development in science and technology led to the dissemination of information and knowledge through classroom also changed. Teachers as educators cannot refrain from directly involved in all activities related to information technology. These challenges provide an opportunity for educators to modify the teaching and learning process to become to become more active and more student-centred. This study draws to this issue by investigating the knowledge, skills, and the use of ICT and attitudes of Excellent Islamic Education teachers towards ICT. The participants were 70 Excellent Islamic Education teachers in Selangor, Malaysia. Data is collected using a questionnaire and the findings are analysed by using SPSS software 19.0. The results of the descriptive analysis involving the mean and standard deviation indicate that the knowledge and teachers’ attitudes towards ICT to be at the high level. While the skills and the use of ICT among the teachers at a moderate level. The result also revealed that there is a significant relationship between ICT knowledge and teachers’ attitude towards ICT. However, the strength of the relationship is very weak. There is also a significant relationship between ICT skills and teachers’ attitude towards ICT and the strength of the relationship is also weak. Finding also shows there is a significant relationship between the use of ICT and teachers’ attitude and the strength of the relationship is at moderate level. In conclusion, the use of ICT in teaching and learning of Excellent Islamic Education teachers is very important to determine the objectives achieved. Excellent teachers should consider that ICT only act as a complement, additional tools or aids to teachers who play the key role in delivering information using teaching methods that are more dynamic and efficient; rather than take the place or role of the teacher.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".