Learning and collaboration technologies : third international conference, LCT 2016, held as part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016, proceedings
Bibliographic record
Abstract
This book constitutes the refereed proceedings of the Third International Conference on Learning and Collaboration Technologies, LCT 2016, held as part of the 18th International Conference on Human-Computer Interaction, HCII 2016, in Toronto, Canada, in July 2016, in conjunction with 14 thematically similar conferences. The 1287 papers presented at the HCII 2016 conferences were carefully reviewed and selected from 4354 submissions. The papers cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The papers included in this volume are organized in the following thematic sections: instructional design; interaction techniques and platforms for learning; learning performance; web-based, mobile and ubiquitous learning; intelligent learning environments; learning technologies; collaboration technologies; and cultural and social aspects of learning and collaboration technologies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.064 | 0.036 |
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".