HOW DOES AWARENESS OF TASK CONFLICT MOTIVATE WIKI-BASED COLLABORATIVE LEARNING? A DESIGN SCIENCE APPROACH
Bibliographic record
Abstract
Lack of motivation is a serious problem in wiki-based collaboration process. The original wiki is designed to hide authorship information. Such design may hinder users from being aware of task conflict, resulting in undesired outcomes (e.g., lack of motivation, and suppressed knowledge exchange activities). This research-in-progress tries to motivate students to participate in wiki-based collaborative learning project by increasing awareness of task conflict. Two tools were proposed to solve problems caused by lack of task conflict clues, such as low level of motivation, content trust, knowledge exchange, and sense of audience. A field test was executed to evaluate new designs. We propose to invite active participants from the field test and use focus group interview to explain how awareness of task conflict motivates participation in collaborative learning. This research-inprogress has the potential to lead to various theoretical and practical implications. For example, the results will enhance the literature on task conflict and user motivation, help platforms design motivation mechanisms.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".