At the LEARNTEC congress, the FernUniversität Hagen’s Prof. Dr. Claudia de Witt will discuss the IMPACT project’s approach and link it to experience gained from the AI.Edu Research Lab. Her talk will draw on the two endeavors to offer a scientific perspective regarding the criteria that determine success in the design of "recommender systems" and feedback that promotes learning, as well as possibilities that exist for integrating them into digital learning environments.

Responsible handling of student data

In the various phases of their university careers (as prospective and new students, during the course of their studies, and at the end of their studies), project participants are to receive what is known as "highly informative and personalized feedback" (HIF), a concept based on the work of the renowned New Zealand educationalist John Hattie. According to Hattie, the ingenuity of feedback is linked to being able to give and receive feedback simultaneously.

Prof. Hendrik Drachsler is Professor of Computer Science with a focus on Educational Technologies at the Leibniz Institute for Research and Information in Education (DIPF) and at Frankfurt am Main’s Goethe Universität. In regard to the basic principle of learning analytics, he explains, "Within the framework of learning analytics, student data is collected and analyzed in order to support them in achieving their academic goals and to contribute to the improvement of teaching. However, learning analytics is rarely deployed at German universities, so it is necessary to create an understanding of the added value it has to offer within German higher education."

The ChatBot knows the answers

Drachsler commented that in the IMPACT project, open source software solutions and preliminary work done at the participating universities have been combined and already put to use. In this process, AI is deployed in analyzing the rapidly growing data assets and converting them into personalized "highly informative personalized feedback." For example, during the student orientation and entrance period (SOEP), students can be given low-threshold advice as needed, providing them with far greater benefits from the previously analyzed volumes of data than would be possible in the context of personal mentoring.

He further declared his belief that "In the future, Chatbots will constitute helpful support systems and provide relevant information about both individual universities and the various academic programs. GUDI, for example, is a chatbot developed by the Goethe Universität that can provide a wide range of basic information, such as semester deadlines and schedules, names of contact persons, and data about university-offered services. Users’ questions constantly contribute to the ChatBot’s 'learning' process and the expansion of its 'knowledge'."