Bibliographic record
Abstract
<P>Open and distance education has integrated quality assurance processes since its inception. Recently, the increased use of distance teaching systems, technologies, and pedagogies by universities without a distance education heritage has enabled them to provide flexible learning opportunities. They have done this in addition to, or instead of, face-to-face instruction, yet the practice of quality assurance processes as a fundamental component of distance education provision has not necessarily followed these changes. </P> <P>This paper considers the relationship between notions of quality assurance and open and distance education, between quality assurance and higher education more broadly, and between quality assurance and the implementation of recent quality audits in Australian universities. The paper compares quality portfolios submitted to the Australian Universities Quality Agency by two universities, one involved in distance education, the other not involved. This comparison demonstrates that the relationship is variable, and suggests that reasons for this have more to do with business drivers than with educational rationales. </P> <P><STRONG>Keywords: </STRONG>distance education, quality assurance, online learning, e-learning, audit, higher education</P>
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".