Teaching Massive, Open, Online, Courses (MOOCs): Tales from the Front Line
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Very little research has been conducted about what it is like to teach a MOOC. Given this, a mixed methods study, involving a survey of 186 MOOC instructors and 15 follow-up interviews, was conducted to explore the motivation, experiences, and perceptions of instructors who have taught massive open online courses. Findings indicate that instructors were motivated to teach MOOCs for three main reasons: (1) interest and passion, (2) publicity and marketing, or (3) benefits and incentives. Most instructors had little online teaching experience prior to teaching their first MOOC, but were satisfied with the experience. The majority believed their own MOOC provided a high quality learning experience but thought that MOOCs overall might not be as good as face-to-face courses. Concerns were raised about the future of MOOCs for online learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.006 | 0.004 |
| 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 it