Integrating ICT in Teacher Education: A Critical Analysis of Digital Tool Usage and Its Effect on Secondary School Students' Performance in Jharkhand
Bibliographic record
Abstract
Integrating information and communication technology (ICT) into teacher education is considered vital for improving secondary classroom practice and student outcomes. In Jharkhand, ICT infrastructure in schools has expanded, but concerns remain about how far ICT-related teacher education has led to meaningful digital tool use and measurable gains in student performance. This study examined the extent of ICT integration by secondary school teachers who had received ICT-related training and analysed its perceived effect on students’ academic achievement. A descriptive survey was conducted with 50 secondary school teachers from government and private schools in rural, semi-urban and urban areas of Jharkhand. A researcher-developed questionnaire gathered data on demographics, frequency and type of digital tool use, self-rated level of ICT integration, and teachers’ perceived and estimated impact of ICT on students’ test and examination scores. Data were analysed using frequencies and percentages. Most teachers reported regular use of digital tools: 64% used them at least three to four times per week and 22% once or twice weekly. Presentation software and educational videos were most frequently used, followed by educational apps and learning management systems. Half rated their ICT integration as “moderate” and about one-third as “high”. Seventy-two per cent perceived a positive or strongly positive effect on students’ performance, and around two-thirds estimated average class scores had risen by 6–15%, though about one quarter reported no clear change or were unsure. The findings suggest ICT-oriented teacher education is promoting regular digital tool use and perceived gains in achievement, but practice remains dominated by presentations and videos. Strengthening ongoing professional development in student-centred digital pedagogy and addressing constraints in rural, resource-poor schools is essential for realising ICT’s full potential.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".