Massive open online courses (MOOCS) for university education: a study on students’ experiences at the University of Ghana
Bibliographic record
Abstract
The objective of this study was to examine students’ experiences in participating in MOOCs (Massive Open Online Courses) at the University of Ghana. The study employed the qualitative research method. All the 12 students of the University of Ghana’s Department of Adult Education and Human Resource Studies who enrolled in a MOOC course participated in the study. The study revealed that students are mostly attracted to Coursera and edx than other available MOOC platforms. Students view MOOC as affordable, accessible and of quality. MOOC challenge mostly cited by students is intermittent internet connectivity. In anticipation of the increase in enrollment in Ghanaian Universities in 2020 and beyond due to the Free Senior High School programme of the government, the study recommended that Universities and other tertiary institutions convert some of their study courses registered by students into MOOCs to create more lecture spaces for prospective students.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".