CONVERGENCE OF DATA SOURCES IN THE ANALYSIS OF COMPLEX LEARNING ENVIRONMENTS
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
Learning in technology mediated learning environments is a complex process that varies across individual and group contexts. Complex learning environments that are medi- ated by technology require distinct concurrent methodologies that reveal when and where learning may occur. This paper describes the analysis of two technology-mediated problem-solving environments, one that uses concurrent methods to identify expertise, and the other that examines the influence of technology in a collaborative learning situ- ation. The first example examines individual problem solving in the context of a stand- alone environment, BioWorld, whereas the second example examines the joint production of medical decisions with traditional and interactive whiteboard technology in a medical classroom. These examples demonstrate how concurrent methods add to our understand- ing of individual learning as well as the co-construction of knowledge in the context of clinical reasoning using technology.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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