Internet in schools: Socio-economic and political factors in Internet use in rural and urban schools in Thailand
Bibliographic record
Abstract
This study explored the influences of social, economic and political factors of Internet use in eight rural and urban schools in southern Thailand. The results of interviews and questionnaires indicated that most respondents in both rural and urban schools perceived IT as a beneficial medium for education and for daily life. However, most teachers lacked understanding and proficiency to use and apply IT in their teaching. Workloads, age and time constraints were highly related to the lack of IT proficiency in teachers and consequently limited IT manpower in schools. Most schools, especially rural ones, faced computer and IT budget constraints, low capacity equipment and inconvenient Internet connections. Most rural schools experienced unstable telephone signals leading to Internet connection difficulties. Finally, it was recommended that similar studies be undertaken in other parts of the country, and that further in-depth study of social factors influencing IT use for education be conducted. Recommendations were also made for applying adult learning approaches in providing IT skill and knowledge to teachers, for using school-based needs assessment for IT provision in schools, and for facilitating collaboration among different parties in promoting IT use.
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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 | 0.001 | 0.000 |
| 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".