A comparison of learner intent and behaviour in live and archived MOOCs
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
The advent of massive open online courses (MOOCs) has created opportunities for learning that are clearly in high demand, but the direction in which MOOCs should evolve to best meet the interests and needs of learners is less apparent. Motivated by our interest in whether there are potential and purpose for archived MOOCs to be used as learning resources beyond and between instructor-led live-sessions, we examined the use of a statistics MOOC and a computer science MOOC, both of which were made available as archived-courses after a live-session and for which enrolment continued to grow while archived. Using data collected from surveys of learner demographics and intent, the course database of major learner activity, and the detailed clickstream of all learner actions, we compared the demographics, intent, and behaviour of live- and archived-learners. We found that archived-learners were interested in the live-MOOC and that their patterns of use of course materials, such as the number and sequence of videos they watched, the number of assessments they completed, their demonstration of self-regulatory behaviour, and their rate of participation in the discussion forums, were similar to the live-learners. In addition, we found evidence of learners drawing on an archived-MOOC for use as reference material. Anticipated areas of impact of this work include implications for the future development of MOOCs as resources for self-study and professional development, and in support of learner success in other courses.
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 | 0.004 | 0.002 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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