Strengthening Sustainability in Agile Education: Using Client-Sponsored Projects to Cultivate Agile Talents
Bibliographic record
Abstract
The success of agile in software development (SD) has sparked the application of agile in non-SD domains such as business management to improve operational efficiency and innovation. Despite the rising industry demands for agile talents in the non-SD domains, agile education falls short of client-sponsored projects, calling into question the sustainability of agile education. This study makes up for the gap and illustrates an eight-month endeavor where scrum practices and values were imbued in a client-sponsored project. The analysis of qualitative and quantitative data gathered throughout the eight-month project illustrates a large disparity among students in their scrum application, reveals top challenges faced by students in their scrum application, and suggests the impact of the scrum application on the quality of student work. The findings of the study set a solid foundation based on which future agile education could be enhanced to strengthen the sustainability of agile education to meet industries’ rising demands for agile talents in non-SD domains.
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How this classification was reachedexpand
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".