6.4HCMay 14
Usable but Conventional: An Empirical Study on the UX of AI-Generated Interface PrototypesKaroline Romero, Igor Wiese, Renato Balancieiri et al.
This paper investigates User Experience (UX) with prototypes generated by Generative Artificial Intelligence (GenAI) tools. An empirical survey with 92 participants evaluated AI-generated and human-created prototypes without prior identification of authorship. We measured UX using the UEQ-S, covering pragmatic and hedonic dimensions. Results indicate positive evaluations in pragmatic aspects, such as usability and efficiency, and neutral or negative evaluations in hedonic aspects, including originality and innovation. We concluded that GenAI can produce functional interfaces but tends to reinforce visual and structural patterns that affect perceptions of originality.
6.9SEJun 17
No Two Developers Think Alike: How Problem-Solving Styles and Experience Shape Needs in Conversational Interaction with CopilotJonan Richards, Bruno Alves de Oliveira, Iury Oliveira et al.
Conversational LLM-based ``programming assistants'' provide a range of benefits to developers. However, recent studies demonstrate the variety in individual developers' needs regarding programming assistants, and challenges encountered by only specific groups of developers. In this study, we explore the role of cognitive diversity in shaping interactions with GitHub Copilot chat. Through a mixed-methods think aloud study with 27 professional developers and students, we characterize 5 distinct ``interaction modes'' and 10 underlying needs in developers' interactions, forming a conceptual model. We characterize links between these modes, needs, and developers' problem-solving styles and experience profiles, showing how cognitive diversity may shape developers' interactions. We provide insights and recommendations for researchers and practitioners on how to design, research, and employ programming assistants to better account for diverse developer needs.