Going the Distance: Distance education in 2010 and beyond
Bibliographic record
Abstract
An Observatory on Borderless Higher Education report on distance higher education was published this past February to classify types of distance education delivery from around the world. Over 700 distance education institutions were identified by purpose using data collected by the International Association of Universities (WHED 2007). While the unique characteristics among types of institutions identified has led to define current key concepts related to distance education delivery, the report has helped map and interpret worldwide trends in distance education. This includes viewing distance education as another form of cross-border higher education as well as recognising that distance education has increased the proportion of female authors and material coming from or about developing countries. Another resulting effect of distance education, however, is an emerging proliferation of quality assurance agencies and accreditation of which are particularly concerned in the increasing role of cross-border higher education delivery.\nA second part of the report involved a case study analysis undertaken between 2006-07 to investigate distance education delivery in Australia, Canada, New Zealand and the United States. The results found that there were differences in educational policies at all levels (international, national, institutional) and that infrastructure was overwhelmingly the largest challenge to overcome.\nThe ODLAA 2009 keynote presentation aims to discuss that while distance education offers new opportunities to utilise new technology to enhance pedagogy, institutions must weigh issues of financial accountability and sustainability in order to develop sound and respectable distance education programmes that will 'go the distance'. Secondary data collected on projected enrolment patterns in the Asia/Pacific and Internet usage will also be used to identify emerging regional issues and challenges in higher education from 2010 and beyond.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".