Playing with some lights_edited_edited.j

THE RESEARCH PROJECTS

work program
Study socio-technical development in research and teaching

Structure of the research program into profiles and sub-projects
Analysis of organizational and interactional structures
Empirically, technologically and theoretically grounded doctoral projects

The interdisciplinary, organizational science-oriented research group investigates the social diffusion (introduction, dissemination and development) of artificial intelligence in the science and higher education system as the process social structuring . The projects are based on quantitative research methods such as data mining and social media monitoring, as well as qualitative approaches using interpretive analyses, interviews, focus groups and digital ethnography.

The research program is divided into three profiles: Research as a work process, Teaching and studies , as well as university management and governance . Six doctoral projects are being pursued within these profiles.

AI in the Humanities, Social Sciences, and Natural Sciences: Areas of Application, Usage Patterns, and Professional Implications in the Research Process

The practical application of AI in research is a subject of considerable debate. Previous research findings focus on assistance with literature searches and processing, support in developing research questions and analyzing data, and improvements to academic writing. Concerns are raised regarding transparency, data protection, and the provision of inaccurate and misleading information. It is particularly noteworthy that there is a lack of empirical knowledge about the practical application of AI in research, especially within the humanities and social sciences. Research in these disciplines appears essential, as their practitioners grapple with fundamental questions that directly impact these application settings. This includes human-machine interaction, which scientific knowledge acquisition as well as a special proficiency in language and text skills.

The use of AI tools in the management of university organizations: Institutional, personnel and technological measures

The reactions of universities and their administrations to the diffusion of AI are—as is to be expected with the introduction of new technological methods—multifaceted and associative. Currently, it can be observed that universities are establishing regulations and guidelines for their degree programs, qualification and research measures, as well as new organizational structures; they are also making curricular changes or independently developing AI-supported, tutorial-based teaching and assessment formats. Other universities are taking a more wait-and-see approach and (cautiously) adapting individual methods. The question arises as to how university organizations are reacting to the diffusion of AI, which AI applications are being implemented and how, and what conditions these reactions depend on.

AI and academic teaching: Student usage behavior, problem-solving skills and critical-constructive approach

Students' use of AI is influenced by individual preferences and established practices within their respective disciplines. It has been observed that students primarily utilize generative AI to support their learning, clarifying comprehension questions and working through learning content through quizzes. Furthermore, students employ generative AI for writing and editing texts and exam papers. Concerns regarding the quality and reliability of the generated content are discussed. There are also concerns that students may rely so heavily on AI output that their problem-solving abilities will decline. Currently, there is a lack of empirical knowledge regarding the use of AI to promote problem-solving skills and creative problem-solving, as well as regarding critical evaluation practices and how these vary across disciplines. The projects within this research profile investigate the extent to which AI influences study habits and learning, and what coping mechanisms are being developed.

As overarching theoretical framework (Especially in the social science-oriented sub-studies) the systems-theoretical approach to the analysis of decision-making structures – developed by Niklas Luhmann – was used as a basis. According to this approach, organizations can be distinguished into formal and informal structures. The formal organization is then the result of decision premises, i.e., stipulations about the principles of the organization.

Decision premises are formed in the form of decision programs, communication channels, and personnel. Together, they constitute the organizational decision-making structure . Informal organization, on the other hand, describes a compensatory or supplementary structure to the formal order. The sub-projects relate to decision premises with program-, communication-, and personnel-related issues.

Research work is already underway project-related in the context of Meetings, conferences and publications The research results are presented. The findings are ultimately published in the form of monographic and cumulative dissertations.

Updated: July 28, 2025

THE RESEARCH PROJECTS

work program
Study socio-technical development in research and teaching

Follow us!

Share this article

THE RESEARCH PROJECTS

work program Study socio-technical development in research and teaching

Follow us!

Share this article

work program
Study socio-technical development in research and teaching