Preliminary results of measuring flow experience in a software modeling tool
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
Weaknesses in the user experience (UX) provided by software modeling tools have been identified as important barriers reducing the uptake of such tools by developers. Emotional factors as essential parts of user experience have received little attention so far. Literature suggests that higher flow experience is associated with higher positive emotional state. Good flow experience means people feel they have clear goals and are focusing well on a task that they regard as enjoyable and are doing reasonably well at; furthermore, they do not feel a need to be concerned about time or what others are thinking and have a sense they are getting good feedback about their progress. Achieving flow is important for performance in creative tasks such as modeling. To learn more about flow we used a questionnaire-based empirical study to measure flow experience of UmpleOnline users. This paper reports preliminary results from 24 respondents, demonstrating a moderate experience of flow state in UmpleOnline. Our objective in this paper is to stimulate the research community to think about how flow can best be measured.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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