Task analysis for groupware usability evaluation
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
Researchers in Computer Supported Cooperative Work have recently developed discount evaluation methods for shared-workspace groupware. Most discount methods rely on some understanding of the context in which the groupware systems will be used, which means that evaluators need to model the tasks that groups will perform. However, existing task analysis schemes are not well suited to the needs of groupware evaluation: they either do not deal with collaboration issues, do not use an appropriate level of analysis for concrete assessment of usability in interfaces, or do not adequately represent the variability inherent in group work. To fill this gap, we have developed a new modeling technique called Collaboration Usability Analysis. CUA focuses on the teamwork that goes on in a group task rather than the taskwork. To enable closer links between the task representation and the groupware interface, CUA grounds each collaborative action in a set of group work primitives called the mechanics of collaboration . To represent the range of ways that a group task can be carried out, CUA allows variable paths through the execution of a task, and allows alternate paths and optional tasks to be modeled. CUA's main contribution is to provide evaluators with a framework in which they can simulate the realistic use of a groupware system and identify usability problems that are caused by the groupware interface.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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