Community meeting the Namibian Education Technology Policy with OLPC's XO laptops: is it a viable approach?
Bibliographic record
Abstract
Research problem There is a need in the literature to describe the implementation processes of technology integration in education through community involvement. In particular, there is limited research available about the mechanism or process behind the community technology trends in Namibia. Few cases explore community involvement in meeting educational technology policy needs. The ICT Policy for Education and the Tech/Na! Implementation policy plan aims to prepare learners to participate in new global economies of the 21st century. It also recognizes that presently, schools and other educational institutions are ill-prepared for the demands of the 21st century (ICT policy for Education, 2004). The policy also presupposes that integrating technology in the classroom is the appropriate vehicle to achieve the goal of knowledge, equity, quality and access for all. Although the Namibian Ministry of Education has focused on developing the technology infrastructure at secondary school level first, many educators and community activists has argued that technology integration would be more successful if implemented at primary school level. It is for this purpose that the Ngoma community explored ways in which to integrate technology in and outside of the classroom as a community effort. Key Findings Results in this case study reveals that despite the valiant efforts of community the educational approaches and understanding of the policy hampered further advancement of these XO computers in the schools for learning. Moreover, the OLPC model approach of ownership and alleged focus on constructivist education and 'digital utopianism appeared to be conflicting in the implementation and sustainability of the community project. Community members priorities changed as the project was implemented due to events of thefts, parent complaints which resulted in short-term ineffective solutions. The Itenge Development Foundation remains an integral part of the project, however with minimal community involvement and use of laptops.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".