arXiv subjects

Maria Rauschenberger

Publications and source records attributed to Maria Rauschenberger.

6 recordsLinked to original sources

arXiv2026

Neurodiversity in Agile Teams: Obstacles and Inclusion Barriers

Context: Neurodiversity is increasingly recognized as a valuable dimension of workplace diversity. However, in agile software development teams, the interplay between teamwork practices and the inclusion of neurodivergent employees remains underexplored. Objective: The study aims to explore how teamwork quality in agile software development is currently practiced and discussed in the context of neurodiversity, and to identify organizational barriers that hinder the effective inclusion of neurodivergent developers. Method: We applied a mixed-method approach combining a web content analysis covering Reddit and LinkedIn with 11 semi-structured expert interviews from a corporate neurodiversity network in a German organization. Results: The analysis shows that teamwork practices are highly fragmented and shaped by individual adaptation rather than a shared standard. While agile practices and supportive tools can enable neurodivergent participation, rigid structures, stereotypes, and one-size-fits-all approaches often undermine inclusion. Organizational awareness and tailored adjustments remain insufficient. Conclusion: Agile practices can promote inclusive teamwork, yet their benefits are constrained by rigid organizational structures and limited awareness of neurodiversity. Harnessing neurodiverse strengths demands flexible organizational conditions and tailored support.

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 S\~ao 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

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

Between Policy and Practice: GenAI Adoption in Agile Software Development Teams

Context: The rapid emergence of generative AI (GenAI) tools has begun to reshape various software engineering activities. Yet, their adoption within agile environments remains underexplored. Objective: This study investigates how agile practitioners adopt GenAI tools in real-world organizational contexts, focusing on regulatory conditions, use cases, benefits, and barriers. Method: An exploratory multiple case study was conducted in three German organizations, involving 17 semi-structured interviews and document analysis. A cross-case thematic analysis was applied to identify GenAI adoption patterns. Results: Findings reveal that GenAI is primarily used for creative tasks, documentation, and code assistance. Benefits include efficiency gains and enhanced creativity, while barriers relate to data privacy, validation effort, and lack of governance. Using the Technology-Organization-Environment (TOE) framework, we find that these barriers stem from misalignments across the three dimensions. Regulatory pressures are often translated into policies without accounting for actual technological usage patterns or organizational constraints. This leads to systematic gaps between policy and practice. Conclusion: GenAI offers significant potential to augment agile roles but requires alignment across TOE dimensions, including clear policies, data protection measures, and user training to ensure responsible and effective integration.

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↗