PersonaGen: A Tool for Generating Personas from User Feedback
Xishuo Zhang, Lin Liu, Yi Wang, Xiao Liu, Hailong Wang, Anqi Ren,, Chetan Arora
TL;DR
PersonaGen is a novel tool leveraging GPT-4 and knowledge graphs to automatically generate user personas from feedback, aiding requirement analysis in agile software development.
Contribution
It introduces a new approach combining GPT-4 and knowledge graphs for automated persona generation from user feedback in agile contexts.
Findings
Mixed evaluation results from a student project study.
Highlights challenges in persona-based education and non-functional requirements.
Demonstrates potential of AI tools in requirement analysis.
Abstract
Personas are crucial in software development processes, particularly in agile settings. However, no effective tools are available for generating personas from user feedback in agile software development processes. To fill this gap, we propose a novel tool that uses the GPT-4 model and knowledge graph to generate persona templates from well-processed user feedback, facilitating requirement analysis in agile software development processes. We developed a tool called PersonaGen. We evaluated PersonaGen using qualitative feedback from a small-scale user study involving student software projects. The results were mixed, highlighting challenges in persona-based educational practice and addressing non-functional requirements.
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Taxonomy
TopicsPersona Design and Applications · Educational Games and Gamification · Software Engineering Techniques and Practices