Exploring the Digital Divide in Open Education: A Comparative Analysis of Undergraduate Students
Bibliographic record
Abstract
In the 21st century, the widespread use of information technologies has made access to technology, technology usage skills, and the quality of technology services increasingly important. However, the digital divide—defined as a lack of access to telecommunications—remains a significant issue that separates developed countries from developing countries. This study aimed to explore the digital divide in open education by comparing the digital divide levels of first term and last term or graduate students enrolled in the Anadolu University Open Education System. The study also examined how factors such as gender, age, income level, and employment status impact digital competency by comparing the digital divide scores of participants in these groups. The findings of the study suggest that first-term students have higher levels of digital competency than final-term students. The study also found that males, people aged 30–40, those with high incomes, and those working in the private sector had the highest digital competency scores. These results can be used to inform the development and implementation of open and distance learning programs to reduce the digital divide, as well as to identify specific groups that may be at a disadvantage in terms of digital competency.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.003 |
| 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".