Abstract:

Problem:
The widespread availability of Artificial Intelligence (AI) tools has resulted in considerable uncertainty among both students and lecturers regarding the appropriate use of such tools in scientific work. To proactively address this uncertainty, the Faculty of Business and Management at the University of Applied Sciences Upper Austria implemented a comprehensive set of measures and a specific guideline für the valuable use of AI-tools in a scientific writing process.

Research Questions:
- Which patterns of AI tool usage are observable in student theses?
- What framework is needed for documenting the use of AI at a university?
- How can the quality of scientific work be improved by documenting the use AI tools?

Methodology:
A case study analysis is annually conducted as a longitudinal study. The cases are the documentations of AI use in final theses of students across the faculty. The documentation of AI use is collected in a structured way (type of use in each phase of the academic writing process, AI tools employed). The aim is to identify patterns in the use of AI tools over time, to to improve the quality of their application, and based on this, to develop and refine a university-wide standard for the transparent and competent use of AI tools in academic papers.

The faculty’s approach on promoting honest engagement with AI in student theses is based on three main pillars:
1. The provision of concrete, continuously evolving examples for the use of AI tools across different phases of scientific work, such as brainstorming, literature review, data analysis, and text generation.
2. The mandatory documentation of AI tool usage in all theses starting from the Summer Semester 2025, utilizing an adapted, structured declaration form. This formal requirement ensures a conscious and justifiable application of AI by students, while also providing faculty with valuable insights into usage patterns.
3. The provision of structured training for students, focusing on fundamental knowledge, tool competence, critical reflection, and the ethical-legal framework of AI use in academic contexts.

Results and Implications:
An entire cohort of student theses from the faculty has now been submitted under the mandatory AI documentation requirement, providing a quantifiable dataset on the actual application of AI tools in academic writing. Initial experiences in the academic year 2024/25 have yielded a positive response from both students and lecturers, suggesting a reduction in previous uncertainty. The documentation process itself has been identified as a key advantage, promoting a more conscious and accountable use of AI by students and establishing a clear commitment from both sides.
The next critical steps involve a structured evaluation of the data gathered from this first cohort’s documentation to gain a deeper understanding of actual AI application in scientific student work. Based on these findings, further development of the practical examples and the documentation form is planned, with the ultimate goal of expanding this successful, transparent, and competence-promoting AI governance framework to the entire University of Applied Sciences Upper Austria. This approach offers a model for other institutions seeking to foster academic integrity and prepare students for the reality of AI-supported academic and professional life.

Keywords:

Artificial Intelligence (AI), Scientific Work, Academic Integrity, AI Usage Documentation, Higher Education.