Cross-Cultural Delivery of e-Learning Programmes: Perspectives from Hong Kong
Bibliographic record
Abstract
The growing popularity of e-learning may pose one of the greatest challenges currently facing traditional educational institutions. The questions often asked are how, rather than whether, to embrace this new form of instructional delivery and how to create an appropriate learning environment for the learners. Educational institutions in Hong Kong have the option of adopting programmes or learning materials developed in other parts of the world for local learners, or not. Such an approach of acquiring learning materials is not without risks in terms of the suitability of materials embedded with cultural contents ‘foreign’ to local learners, or in terms of the suitability of assumptions in the communication context. What are the issues involved in the globalization of education through e-learning? This paper explores – from a critical-dialectical perspective – the implications of globalization on educational policy through cross-border delivery of educational programmes by e-learning, with particular attention given to the threat of cultural imperialism. The paper concludes that Hong Kong seems to be coping with ‘cultural imperialism’ rather well because of its unique history of being a cross-road for East and West, and also with some recommendations to e-learning providers to mitigate the potential damage of cross-cultural delivery of e-learning.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".