相关论文: Navigating the Complexity of Generative AI Adoptio…
The adoption of large language models (LLMs) and autonomous agents in software engineering marks an enduring paradigm shift. These systems create new opportunities for tool design, workflow orchestration, and empirical observation, while…
Generative Artificial Intelligence (AI) tools are increasingly deployed across social media platforms, yet their implications for user behavior and experience remain understudied, particularly regarding two critical dimensions: (1) how AI…
Generative Artificial Intelligence (GenAI) is transforming how firms create, process, and apply knowledge, yet little is known about the heterogeneity of its productivity effects across users. We report results from a randomized controlled…
As generative AI (genAI) rapidly enters classrooms, accompanied by district-level policy rollouts and industry-led teacher trainings, it is important to rethink the canonical ``adopt and train'' playbook. Decades of educational technology…
The rapid emergence of generative AI tools is transforming the way software is developed. Consequently, software engineering education must adapt to ensure that students not only learn traditional development methods but also understand how…
The "Gen-AI-tecture" project embeds a locally executed, discipline-specific tool into a mixed-methods focus-group design, structured around three research objectives: (a) to evaluate how generative AI tools impact students' creativity in…
Although organizations increasingly position AI adoption as a pathway to competitiveness and innovation, organizations' perspectives on productivity and efficiency often clash with workers' perspectives on AI's economic and social value.…
Generative artificial intelligence (GenAI) is diffusing rapidly, yet its adoption is strikingly unequal. Using nationally representative UK survey data from 2023 to 2024, we show that women adopt GenAI substantially less often than men…
Generative AI (GenAI) is reshaping enterprise architecture work in agile software organizations, yet evidence on its effects remains scattered. We report a systematic literature review (SLR), following established SLR protocols of…
The advent of generative artificial intelligence (GenAI) technologies has been changing the research landscape and potentially has significant implications for Digital Humanities (DH), a field inherently intertwined with technologies. This…
The rapid evolution and inherent complexity of modern software requirements demand highly flexible and responsive development methodologies. While Agile frameworks have become the industry standard for prioritizing iteration, collaboration,…
This article presents the results and their discussion for the third wave (with n=23 participants) within a multinational longitudinal study that investigates the evolving paradigm of human-AI collaboration in problem-solving contexts.…
Software Testing is a well-established area in software engineering, encompassing various techniques and methodologies to ensure the quality and reliability of software systems. However, with the advent of generative artificial intelligence…
Empathy has been discussed as a relevant human capability in software engineering, particularly in activities that require understanding users, stakeholders, and the societal implications of technological systems. This relevance becomes…
Generative artificial systems (GenAI) have experienced exponential growth in the past couple of years. These systems offer exciting capabilities, such as generating programs, that students can well utilize for their learning. Among many…
Generative AI (genAI) tools (e.g., ChatGPT, Copilot) have become ubiquitous in software engineering (SE). As SE educators, it behooves us to understand the consequences of genAI usage among SE students and to create a holistic view of where…
AI-powered software tools are widely used to assist software engineers. However, there is still a need to understand the productivity benefits of such tools for software engineers. In addition to short-term benefits, there is a question of…
Context: The rise of Artificial Intelligence (AI) in software engineering has led to the development of AI-powered test automation tools, promising improved efficiency, reduced maintenance effort, and enhanced defect-detection. However, a…
While AI is often introduced into organizations to drive innovation and efficiency, many adoption efforts fail as workers resist and struggle to integrate these systems. These failures point to a deeper issue: workers, the very people…
As generative AI technologies are pressed into service in workplace settings, current approaches to account for the contexts in which such technologies are used fall short of users' expectations and needs. This paper empirically…