Promoting digital literacy in African education: ICT innovations in a Ugandan primary teachers' college
Bibliographic record
Abstract
This research entitled “Promoting digital literacy in African education: ICT innovations in a Ugandan primary teachers’ college” was guided by two research questions: (1) What role can digital technology and digital literacy play in improving teacher education in a rural Ugandan primary teacher’s college? (2) How has ICT policy impacted curriculum development in Ugandan education and classroom practice in two rural Ugandan primary schools? It took the form of a qualitative case study in which data were collected using classroom observations, individual interviews, focus group discussions, semi-structured questionnaires, artefacts and document analyses. Findings of the study suggest that technology has a major role to play in improving teacher education in a rural Ugandan primary teachers’ college. These included: enhancing the tutors’ identities; increasing the tutors’ resourcefulness; promoting team work among the tutors; promoting the integration of the local with the global to facilitate teaching and learning; and promoting teamwork and team spirit among the tutors. Further, the study found that the ICT policy had positively impacted curriculum development and classroom practices in the two rural Ugandan primary schools. However, the study revealed that the positive impact of ICT policy on curriculum development and classroom practices were being undermined by multiple factors, including: fragile ICT infrastructure in the villages; inadequate supply of electricity; lack of access to the Internet; and inadequate digital literacy skills among teachers. It therefore concludes that government should take appropriate measures to address these challenges for digital literacy to sustainably take root in Ugandan education. Further studies will need to be carried out to identify appropriate strategies through which these challenges can be addressed in order to achieve meaningful educational change in Uganda.
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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 | 0.000 | 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".