When Students Can Choose: Online Self-Study or In-College Learning of English for Academic Purposes
Bibliographic record
Abstract
This study aimed to better understand what motivations drive students to select a self-study massive open online course (MOOC) or an in-college course with an instructor. The students were enrolled in one of three level courses of English for Academic Purposes (EAP), which was an accredited course required for the completion of their Bachelor's Degree, at three teacher education colleges in Israel. The study applied a mainly quantitative data collection method, with a qualitative component. The researchers distributed a survey to 236 students studying in one of the two conditions. They compared survey results between the two groups to examine student background, motivations, and perceptions in relation to choice of preferred learning style. Findings indicated that demographic factors had little effect on the students’ choice. In terms of student motivations, while some differences were found between the two groups in learning preferences, the greatest motivations for selecting a MOOC were extrinsic, with more students driven by financial and time constraints rather than a preference for autonomous learning. The perceptions of students who chose a MOOC indicated low learner readiness to study independently and, as such, a higher risk of not passing the required course. Despite claims that MOOCs represent the democratization of education – providing access to all, regardless of age, gender, financial resources, or other barriers, our findings reveal inequality between students learning English for Academic Purposes in higher education based primarily on financial resources.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| 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".