Influencing factors in OER usage of adult learners in Korea
Bibliographic record
Abstract
Open Educational Resources (OER) is terminology that refers to educational resources (content and software) distributed through the Internet, free of charge and freely accessible, expanding learning opportunities for adult learners. This terminology first appeared around 2002, although its roots can be traced to the open architecture of the Internet. Until recently, OER development has focused more on quantity of contents rather than quality. In this study, we have examined the factors influencing the learning intention of adult learners in the OER context. Based on the relevant literature, we have identified a number of factors influencing a learner’s intention to use e-learning content. We have also developed a questionnaire for conducting a survey on such influencing factors. The survey results show that ease of use and relation to immediate workplace needs affect the intention of adult learners in using OER. The findings of this study can inform those developing and designing a learning environment that employs OER while also providing general guidance for developers and educators on how to design OER content.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".