Artificial Intelligence in Sports: Insights from a Quantitative Survey among Sports Students in Germany about their Perceptions, Expectations, and Concerns regarding the Use of AI Tools [Artificial Intelligence in Sports: Insights from a Quantitative Survey among Sports Students in Germany about their Perceptions, Expectations, and Concerns regarding the Use of AI Tools]

Krämer, Dennis; Bosold, Anja; Minarik, Martin; Schyvinck, Cleo; Hajek, André

Zusammenfassung

Generative Artificial Intelligence (AI) tools such as ChatGPT, Copilot, or Gemini have a crucial impact on academic research and teaching. However, empirical data on how students perceive the increasing influence of AI, which different types of tools they use, what they expect from them in their daily academic tasks, and their concerns regarding to the use of AI in their studies are still limited. The project “Artificial Intelligence in Sports” (AIS) aims to address this empirical gap through a quantitative study. The manuscript presents findings from a quantitative survey conducted among sports students of all semesters in Germany using an online questionnaire. It explores aspects such as students’ usage behavior, motivational factors, and uncertainties regarding the potential impact of AI tools on academia in the future. Furthermore, the social climate in sports studies is being investigated to provide a general overview of the current situation of the students in Germany. Data collection took place between August and November 2023, addressing all sports departments at German universities, with a total of 262 students participating. Our Findings indicate that students have a strong interest in using AI tools in their studies, expecting them to improve their overall academic performance, understand the complexity of scientific approaches, and save time. They express confidence that the proliferation of AI will not compromise their critical thinking skills. Moreover, students are positive about integrating more AI-related topics into the curriculum and about lecturers adopting more AI-based teaching methods. However, our findings also show that students have concerns about plagiarism, lecturer preparedness and their own skills and future skill development. ​​​​​​​ In light of our empirical findings, we suggest that universities address this ambivalent situation by educating students on how to generate reliable information with AI and avoid misinformation. It is imperative that students have both practical and critical knowledge about the use and implications of a new technology that is rapidly spreading in academia. This will enable them to better understand the impact and also the limitations of a technology that only emerges through its practical use.