Development, Implementation and Acceptance of an AI-based Tutoring System: A Research-Led Methodology

This Design-Based Research (DBR) project aims to develop an intelligent tutoring system (ITS) for higher education. The system will collect teaching and learning materials in audio and video formats (e.g., podcasts, lecture recordings, screencasts, and explainer videos), and store them on a learning experience platform (LXP). Then, the ITS will process them with the help of speech recognition to gain data which, in turn, will be used to power further applications: Using artificial intelligence (AI), the platform will allow users to search the materials, automatically compiling them according to criteria like lesson subject, language, medium, or required prior knowledge. By the end of the last DBR cycle, the ITS will also provide a more active form of support: It will automatically generate exercises based on predefined patterns and teaching materials, thus allowing learners to check up on their learning progress autonomously. In order to closely match the ITS's features to the needs and learning habits of students in higher education, the development of this AI-based tutoring system is accompanied by an interdisciplinary team which will continuously re-evaluate and adapt the concept over the course of several DBR cycles. Our goal is to derive implications for the system's technical development by collecting and evaluating educational research data (mixed methods design; primary and secondary research methods).