Introduction to the Sage Handbook of E-learning Research, 2nd ed.
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 publication of the second edition of the SAGE Handbook of E-learningResearch attests to the continued need for study and understanding of learningpractices in contemporary technology-supported and technology-enabled educational, work and social settings. In preparing the first edition (Andrews &Haythornthwaite, 2007a), we found that while there had been considerabledevelopment in teaching and learning online, and in learning design, there wasno coherent view of what constituted research in the field. Writing for this 2016edition, we find there has been much progress in research, but it has taken many new directions, each wrestling with how to analyze and represent learning in an era of continuing change in technologies, learning practices, and knowledge distribution. This volume, like the last, takes stock of progress in e-learning research, highlighting advances as well as new directions in studies and methods for approaching and keeping up with changes in learning in an e-society.
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 it