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Our interdisciplinary research project “SIDDATA”, BMBF funded 2018 – 2022 (applied until 10/2024), examines how today’s students can be digitally supported to achieve individual study goals. Student self-regulation and motivation is necessary to set goals and to check their achievements with self-monitoring. We discuss our Digital, Data-Driven Assistant: Requirements engineering based on interviews and status quo analyses, system architecture (Python backend system, Stud.IP frontend, interfaces, personal data protection) and LUH go-live and test of Prototype 2 in January 2021. We use data from student life cycle and learning management systems (HIS-QIS/LSF, Stud.IP) and from individual, structured dialogues with a student. E.g., we recommend lectures including OER and imports from other universities, study finance and career opportunities, learning teams, semesters abroad or second and third level human support. Thus, our Digital, Data-Driven Assistant enables efficient first-level student support with automation and digital transformation of support processes. Finally, we discuss our research agenda for Prototype 3 (to be introduced 2021) and Prototype 4 (to be introduced 2023, if funded), which, e.g., will use Natural Language Processing (NLP) in an advanced chatbot and advanced data analytics tools. We further will suggest similar student assistant applications, e.g., in the LUH international office supporting incoming students. |
