From Perspective to Practice: Gauging the Awareness and Integration Level of ICT in Teaching Process at Secondary Level in District Shaheed Benazirabad, Pakistan
Bibliographic record
Abstract
Pakistan, in the last 10 years, has witnessed a fast and deep penetration of computers, internet, and android cell phones in the everyday lives of the teachers. The education process has yet to enjoy the full benefits of this technology despite the implementation of 3g/4g technologies and a surge of android cell phones. Therefore, teachers being an integral and vital part of the education process need to be well aware of the importance and should be trained at incorporating ICT in their daily teaching processes. This survey-based descriptive study gauged the familiarity of High School Teachers with ICT and its level of incorporation in the teaching process at the secondary level. The population of this study was 617 (N=617) High School Teachers belonging to 61 secondary schools of the district. About 245 teachers who participated in this study were randomly selected from 24 secondary schools. A self-developed questionnaire was distributed to these teachers. All the questionnaires were filled and returned. About 8 of these questionnaires were incomplete and therefore were deemed unusable. Therefore, only 237 questionnaires were used for data analysis. The findings of this study indicated that only 15% of the participants knew about ICT and its uses in the teaching process. Internet browsing, e-mailing and operating a CD Rom device as well-known aspects and simulations, problem-solving software, and graphics were some of the ICT aspects which the participants appeared to be familiar with. Findings about the level of incorporation in the teaching process revealed that computer labs were available in about 15% of the schools; about 55% of the participants owned android cell phones; 45% had self-access to the internet and these android phones were mostly used for communication with other teachers and parents. About 2% used ICT for teaching specific subjects; out of the 2% that used ICT for teaching, only 0.5 % used it as an essential part of daily instruction. The results also show that 0.25% of participants were formally trained in ICT. ICT was mostly used for finding and accessing and downloading educational materials. Less frequently used of ICT included making lectures, drills, and practice, preparing lesson plans, and video lecturing.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".