@incollection{HeltenSchmohlSchellingetal.2023,
  author    = {Anne-Kathrin Helten and Tobias Schmohl and Kathrin Schelling and Stefanie Go and Carolin Freier and Marianne Hunger and Franziska Hoffmann and Florian Richter},
  title     = {Combining NLP, Speech Recognition, and Indexing},
  series = {Conference proceedings. 13th international conference \"The future of education\". Hybrid edition, 29-30 June 2023},
  publisher = {Filodiritto Editore},
  address   = {Bologna},
  doi       = {10.25656/01:27908},
  year      = {2023},
  abstract  = {This paper presents the ongoing development of HAnS (Hochschul-Assistenz-System), an Intelligent Tutoring System (ITS) designed to support self-directed digital learning in higher education. Initiated by twelve collaborating German universities and research institutes, HAnS is developed 2021–2025 with the goal of utilizing artificial intelligence (AI) and Big Data in academic settings to enhance technology-based learning. The system employs AI for speech recognition and the indexing of existing learning resources, enabling users to search and compile these materials based on various parameters. Here, we provide an overview of the project, showcasing how iterative design and development processes contribute to innovative educational research in the evolving field of AI-based ITS in higher education. Notwithstanding the potential of HAnS, we also deliberate upon the challenges associated with ensuring a suitable dataset for training the AI, refining complex algorithms for personalization, and maintaining data privacy.},
  language  = {en}
}