arXiv subjects

Eva-Maria Schön

Publications and source records attributed to Eva-Maria Schön.

10 recordsLinked to original sources

arXiv2026

Operationalizing the EU AI Act in Agile Software Development: A Guideline-Based Approach

Context: The EU AI Act requires providers and deployers of Artificial Intelligence (AI) systems to implement documentation, risk management, and human oversight. Agile teams that ship AI features in short iterations lack specific artifacts to discharge these duties, since the regulation's abstract provisions do not map onto the Definition of Done, Sprint Reviews, or working agreements. Objective: We provide agile teams with an actionable compliance instrument: an evaluated guideline that operationalizes EU AI Act obligations as activities integrable into existing agile practice. We further document the translation method behind it so that the approach can be reused for adjacent regulations. Method: Following Design Science Research, we assessed each EU AI Act article along three dimensions. We subsequently classified the articles using a traffic-light scheme and mapped those deemed highly relevant to previously documented pain points of agile teams working with AI. We validated the resulting catalog with practitioners through a survey and 11 additional semi-structured expert interviews, analyzed via qualitative content analysis. Results: The guideline comprises 12 items covering roles and responsibilities, risk and quality management, transparency and traceability, monitoring, and regulatory sandboxes. Practitioners rated the catalog as understandable and relevant; feasibility varied with organizational maturity. Effective adoption towards EU AI Act compliance requires collective ownership across roles and integration into existing agile events rather than parallel compliance processes. Conclusions: The catalog gives agile teams a starting point to transform their delivery practices towards an EU AI Act compliance without dismantling agile practices.

cs.SE↗

arXiv2026

Overcoming Challenges in Agile and DevOps Integration: A Qualitative Study

In response to the growing reliance on Agile and DevOps methodologies for enhancing software delivery speed and quality, this study investigates the persistent challenges and viable solutions associated with their integration. Although Agile promotes iterative development and customer responsiveness, and DevOps emphasizes automation and operational efficiency, their convergence in practice often presents significant organizational, structural, and technical hurdles. This research employs a qualitative methodology grounded in semi-structured interviews with six seasoned industry professionals across Brazil and Germany, each with extensive experience in both Agile and DevOps domains. The study identifies four core categories of integration challenges: Cultural & Organizational Barriers, Structural Constraints, Process \& Method Complexity, and Technical Limitations. Additionally, it offers four major solution domains: Team Structure & Autonomy, Culture & Collaboration, Process & Change Management, and Automation & Infrastructure. The findings underscore the importance of cultural alignment, proactive monitoring, automation, and other practices in mitigating integration friction. The results contribute to a deeper understanding of the Agile-DevOps interface and offer practical insights for software organizations seeking to navigate this complex transition effectively.

cs.SE↗

arXiv2026

The 2nd Workshop on Agile Practice & Research: A Summary and Call For Research

Agile software development has been shaped by the interplay between academic research and industrial practice for over two decades, yet notable gaps persist between both domains. This paper focuses on three research-practice gaps: the theory gap, the time gap, and the transfer gap. To address these, the 2nd Agile Practice & Research Workshop was held at the International Conference on Agile Software Development (XP) 2026 in São Paulo, Brazil, bringing researchers and practitioners together to identify root causes and develop joint solutions. Building on two preceding sessions in which contributions of participants had been presented, participants engaged in a structured collaborative session, working in small groups on one of the three gaps and reflecting on possible causes and remedies. The organizers synthesized the results into four propositions for improving the research-practice intersection: (1) improving scientific communication, (2) aligning research more closely with emerging industrial needs, (3) creating stronger incentives for sustained collaboration, and (4) integrating educational approaches into research practice. From these, three calls for research were formulated: (a) broader adoption of open science practices for transparency, reproducibility, and cumulative evidence; (b) higher empirical quality standards through stronger theoretical grounding and rigorous design; and (c) more explicit, value-oriented contributions that clearly articulate their practical and scientific relevance. The paper offers both a summary of the workshop and a call to strengthen research-practice collaboration.

cs.SE↗

arXiv2026

Knowing the Rules Is Not Enough: Student Regulatory Awareness and Use of GenAI in Higher Education

Context: Generative Artificial Intelligence (GenAI) tools such as ChatGPT are increasingly integrated into students learning practices. While previous research mainly examines adoption rates and attitudes, students awareness of institutional regulations and their perceived compliance remain unexplored. Understanding whether regulatory awareness influences student behavior is therefore important as higher education institutions create and apply AI policies. Objective: This study investigates how students awareness of GenAI regulations relates to their perceived compliance and actual usage behavior. Our research objective is to examine the association between regulatory knowledge, GenAI use, and perceived rule conformity among students in computer science related study programs. Method: A survey with 151 undergraduate students in Business Information Systems and E-Government programs at the University of Applied Sciences and Arts Hannover (Germany) collected data on GenAI usage, tools used, awareness of institutional regulations, and perceived compliance. Descriptive statistics, cross-tabulations, and correlation analyzes were applied. Results: Most students actively use GenAI tools, but over half are uncertain whether their usage complies with institutional regulations. Regulatory awareness shows only weak to moderate associations with actual usage behavior. Students primarily rely on privately accessed GenAI tools rather than institutionally provided solutions. Contributions: The study contributes empirical evidence on the relationship between regulatory awareness and GenAI usage in higher education. Our findings highlight a gap between institutional regulations and student practices and provide insights for educators and institutions on improving policy communication and integrating GenAI more effectively into teaching and learning contexts.

cs.CY↗

arXiv2026

From Real-World Projects to Research-Oriented Learning: Continuous Improvement of a Master-Level Course in Software Engineering Education

Problem: Despite growing interest in project-based learning, little is known about how a master-level course can be continuously evolved toward research-oriented approaches over several years and how students perceive this development. Method: We conducted a longitudinal mixed-methods study of a master-level course in Information Systems at the University of Applied Sciences and Arts Hannover (Germany). The analysis covers six years between 2019 and 2025 and draws on teaching evaluations, course documentation, and reflective teaching artifacts. Results: The course evolved from a practice-oriented project format toward a more explicitly research-oriented learning environment. Despite this change, students' perceived course quality remained positive. Authentic projects, external collaboration, lecturer support, structured scaffolding, and visible relevance supported positive student perceptions. Contribution: This paper shows how a master-level course can be continuously evolved toward research-oriented learning while maintaining positive student perceptions. It further identifies the course design decisions that supported this transition.

cs.CY↗

arXiv2026

A Systematic AI Adoption Framework for Higher Education: From Student GenAI Usage to Institutional Integration

The rapid development of GenAI technologies is transforming learning, assessment, and academic production in higher education. Despite increasing student adoption, many institutions lack operational mechanisms to systematically align regulations and curricula with evolving generative artificial intelligence practices, creating regulatory ambiguity and academic integrity risks. This study investigates how students utilize generative artificial intelligence tools in computer science-oriented disciplines and develops a structured, lightweight framework supporting institutional adaptation to pervasive GenAI usage. We conducted a case study at the University of Applied Sciences and Arts Hannover (Germany), combining document analysis with an online survey (N = 151) targeting Business Information Systems and E-Government students. Quantitative responses were analyzed statistically, while open-ended responses underwent thematic synthesis. Generative artificial intelligence adoption was widespread, with ChatGPT as the dominant tool. Students primarily used generative artificial intelligence for research assistance, programming support, and text processing. However, substantial policy uncertainty was observed: many students were unaware of or unsure about institutional generative artificial intelligence regulations. Document analysis revealed regulatory gaps, ambiguous terminology, and inconsistencies between formal rules and teaching practices. To address these shortcomings, we propose the AI Adoption Framework for Higher Education, an iterative and operational model integrating document analysis, empirical observation, synthesis of findings, and targeted updates of regulations and curricula. The framework addresses governance, assessment validity, and academic integrity under generative artificial intelligence conditions and provides practical guidance for institutional adaptation.

cs.CY↗

arXiv2026

Teaching Agile Requirements Engineering: A Stakeholder Simulation with Generative AI

Context: The active involvement of users and customers in agile software development remains a persistent challenge in practice. For this reason, it is important that students in higher education become familiar with good practices in Agile Requirements Engineering during their studies. Objective: Our objective is to enable students to learn how to interact with Generative Artificial Intelligence (GenAI) through the use of a stakeholder simulation with AI Personas, while also developing an understanding of the limitations of AI tools in practical contexts. Method: In our courses, we employ a stakeholder simulation using GenAI, in which students conduct interviews with AI Personas through a provided meta-prompt. Based on the outcomes of these interviews, students apply agile practices (e.g., story mapping or impact mapping) to document requirements. The use of GenAI is subsequently reflected upon in a structured group discussion. Results: Through this approach, students gain practical experience by applying state-of-the art agile practices for requirements elicitation and documentation while simultaneously developing an understanding of the technical and ethical limitations associated with the use of generative AI. Conclusion: We have applied this approach over several terms and found that using a meta-prompt provides flexibility, allowing us to remain independent of specific large language model providers.

cs.SE↗

arXiv2025

Towards a Closer Collaboration Between Practice and Research in Agile Software Development Workshop: A Summary and Research Agenda

Agile software development principles and values have been widely adopted across various industries, influencing products and services globally. Despite its increasing popularity, a significant gap remains between research and practical implementation. This paper presents the findings of the first international workshop designed to foster collaboration between research and practice in agile software development. We discuss the main themes and factors identified by the workshop participants that contribute to this gap, strategies to bridge it, and the challenges that require further research attention.

cs.SE↗

arXiv2024

Agile Culture Clash: Unveiling Challenges in Cultivating an Agile Mindset in Organizations

Context: In agile transformations, there are many challenges such as alignment between agile practices and the organizational goals and strategies or issues with shifts in how work is organized and executed. One very important challenge but less considered and treated in research are cultural challenges associated with an agile mindset. Although research shows that cultural clashes and general organizational resistance to change are part of the most significant agile adoption barriers. Objective: We identify challenges that arise from the interplay between agile culture and organizational culture. In doing so, we tackle this field and come up with important contributions for further research regarding a problem that practitioners face today. Method: This is done with a mixed-method research approach. First, we gathered qualitative data among our network of agile practitioners and derived in sum 15 challenges with agile culture. Then, we conducted quantitative data by means of a questionnaire study with 92 participants. Results: We identified 7 key challenges out of the 15 challenges with agile culture. These key challenges refer to the technical agility (doing agile) and the cultural agility (being agile). The results are presented in type of a conceptual model named the Agile Cultural Challenges (ACuCa). Conclusion: Based on our results, we started deriving future work aspects to do more detailed research on the topic of cultural challenges while transitioning or using agile methods in software development and beyond.

cs.SE↗

arXiv2022

Key Challenges with Agile Culture -- A Survey among Practitioners

Context: Within agile transformations, there are a lot of different challenges coming up. One very important but less considered and treated in research are cultural challenges. Although research shows that cultural clashes and general organizational resistance to change are part of the most significant agile adoption barriers. Objective: Thus, our objective is to tackle this field and come up with important contributions for further research. To this end, we want to identify challenges that arise from the interplay between agility and organizational culture. Method: This is done based on an iterative research approach. On the one hand, we gathered qualitative data among our network of agile practitioners. Then, we derived in sum 15 challenges with agile culture. On the other hand, we gathered quantitative data by means of a questionnaire study with 92 participants. Results: We identified 7 key challenges out of the 15 challenges with agile culture. The results that are presented in a conceptual model show a focus on human aspects that we need to deal with more in future. Conclusion: Based on our results, we started deriving future work aspects to do more detailed research on the topic of cultural challenges while transitioning or using agile methods in software development and beyond.

cs.SE↗