The Pedagogic Architecture of MOOC: A Research Project on Educational Courses in Spanish
Bibliographic record
Abstract
<p>This study has been carried out within the context of the ECO European Project (E-learning, Communication Open-Data: Massive Mobile, Ubiquitous, and Open Learning) which is being financed by the European Union over four years (2014-17). It analyses the pedagogic architecture of MOOC on pedagogic/educational subjects in Spanish over one academic year (September 2015-June 2016). The analysis focuses on five major dimensions from a qualitative perspective: subjects and the promoting institution, methodology, resources, type of videos, and evaluation. The results demonstrate the hegemony of subjects linked to the Society of Knowledge, such as the widespread use of traditional methodology based on video lessons (the “talking head” model). Communication tools are clearly underused and evaluation based on the use of questionnaires is dominant. The findings show the need for further research into MOOC based on a pedagogic approach such as the one adopted here.</p>
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.002 |
| 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".