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IMPACT - Implementation of AI-based feedback and assessment with trusted learning analytics in higher education institutions
Supporting academic teaching staff in creating more accessible learning environments
Contents and objectives of the project:
The IMPACT joint project promotes the improvement of higher education through the scalable use of artificial intelligence (AI) methods for the (partially) automated analysis of texts. Throughout the student life cycle, prospective students, new students, and current students receive text-based, highly informative, and personalized feedback during the orientation and introductory phase, during the course of their studies (formative assessment), and at the end of their studies (summative assessment). This not only helps students meet paracurricular study requirements, promotes individual learning goals and self-regulation strategies for future learning, and reduces uncertainty and overload among students, but also relieves the burden on teachers and encourages active engagement with AI-generated feedback by students and teachers.
At five German universities, text-based AI processes such as chatbots and personalized feedback systems for formative and summative assessment are being widely implemented, accompanied by change management based on the SHEILA process model. The interdisciplinary consortium uses internationally proven open-source software solutions (Rasa X, OnTask, las2peer), common standards, and interoperability in university teaching with learning management systems (Moodle, Stud.IP, ILIAS), online study choice assistants, and assessment systems (LPLUS). Media-didactic concepts and adaptations are being developed for the goal-oriented integration of AI applications.
A prerequisite for the sustainable implementation of AI applications in studies and teaching is data ethics change management, which is developed and applied in all participating universities to enable continuous cooperation with committees, teachers, and students. The project results are made available throughout Germany through workshops and according to open science principles.
Contact
Contact:
impact@uni-bremen.de
Adrian Roeske (Projektkoordination)
Management of project
Prof. Dr. Andreas Breiter
Dept. 3, University of Bremen
The joint project consists of teams at Goethe University Frankfurt (project leader), Humboldt University Berlin, Free University Berlin, Hagen Distance Learning University, and the University of Bremen. For more information about the joint project, please visit:
https://impact.studiumdigitale.uni-frankfurt.de/projektteam/
The IMPACT-Team at the University of Bremen
Förderkennzeichen: 16DHBKI046
Project schedule
The joint project is being implemented in accordance with the SHEILA framework, which takes particular account of aspects of “Trusted Learning Analytics” (TLA). TLA provides for the ethically responsible and transparent use of data. The pilot and evaluation studies therefore take into account the requirements arising from the diversity of the target groups.
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Data protection
In order to operate AI applications, various data must be collected and processed. It is particularly important to us to provide information about what data we collect for what purpose in the project, and how we use and store it.
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Ethical, Legal and Social Implications (ELSI)
In addition to legal issues, ethical and social questions also play an important role in the development and use of AI applications: How well can we avoid bias or discrimination in our AI applications? What social or societal impacts do our LA & AI have?
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