Utilizing Digital Tabletops in Collocated Agile Planning Meetings
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
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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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 | 0.001 |
| Science and technology studies | 0.000 | 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