THERE AND BACK AGAIN: FROM RESEARCH METHODS TO PRINCIPLES OF LEARNING, AND EVERYTHING IN BETWEEN: CONSOLIDATED KNOWLEDGE USING THE COURSE WIKI
Bibliographic record
Abstract
A course wiki is an active environment in which students not only solve problems, but also find their own problems (Bransford, Brown, & Cocking, 1999). Wikis are novel, immersive environments requiring active participation, which enable students to build knowledge within a secure online setting (Hadjerrouit, 2011). This contribution traces a graduate student’s journey through a Master of Education program, using a course wiki as a repository for the knowledge and experiences he has gained over the course of three years. A chronological account of his progress throughout the program is showcased here as a capstone project.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.147 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.011 | 0.119 |
| Scholarly communication | 0.037 | 0.055 |
| Open science | 0.006 | 0.020 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".