Utilizing Digital Tabletops in Collocated Agile Planning Meetings
Bibliographic record
Abstract
In agile software development, planning meetings play a pivotal role in establishing a concrete under-standing of customerspsila requirements. Using tools to enhance the effectiveness of the planning meetings without affecting the agility of the practices or disturbing the traditional settings is a challenging task. In this paper, we propose the use of digital tabletops as a means of collaboration in agile planning meetings for collocated teams. To support this proposal, we introduce Agile Planner for Digital Tabletops, a planning tool that was specifically designed for use on large horizontal displays. A multipart study involving a variety of qualitative methodologies was conducted to evaluate this approach. The study involved 14 individual participants plus a five member agile team. The individual evaluation suggested that in general, the tool is usable with minor issues to be considered in future design revisions. The agile team evaluation revealed a significant interest in the tool and its added benefits to the agility of the planning meeting with some issues to be further enhanced.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".