Unveiling Scholarly Insights: Quality Assurance in Open and Distance Education
Bibliographic record
Abstract
Open and distance education (ODE) has continuously evolved, significantly influencing educational, daily, and professional spheres, thereby prompting interest in its sustainability and quality. This study explored global scientific perspectives on quality assurance in ODE using the science mapping method. Search terms centred on open education, distance education, and quality assurance; data was gathered from 4,224 scientific texts in the Web of Science Core Collection. Analyses were conducted using VOSviewer software. Co-authorship analyses explored scientific collaboration structures at the country level. Globally shared concepts of interest to the scientific community were addressed using co-occurrence analyses. A detailed examination of co-occurrence outputs led to classification related to general and emerging key concepts. Results depicted a widespread global interest in quality assurance in ODE, fostering connections based on new cultural similarities. The concept of quality assurance in ODE continues to be enriched and developed, gravitating towards focused learning and instruction, establishing strong ties with various components of regular education as well as human elements. However, the prevailing view of quality assurance has yet to encompass this diversity. Rather than consider the nature and current potential of ODE, it has maintained an externalized and technical perspective.
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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 | 0.010 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".