Abstract
A growing number of students enrolls at universities, while capacities – above all in terms of teachers – to support their learnings stay limited. In particular, individualised feedback for students is not feasible in many courses. How can universities close this gap with the help of Artificial Intelligence (AI)?
This paper presents a use case for an AI-aided learning scenario that is expected to achieve high learning effectiveness: the acquisition of argumentation competence in the disciplines of law and economics. Emphasis is placed on good comprehensibility for the target group of students, despite the complexity of the setting. Also for this reason, the use case has been given a descriptive name, The Argueniser - Organise Your Arguments.
The focus of this paper is placed on the use case. Flanking topics are also highlighted: the concept of argumentation competence within the project, the role of feedback, and mutual learning between learners, teachers and AI. A preliminary study design illustrates the approach to measure learning effectiveness of the AI-aided learning situation. A notable aspect of the project is the involvement of the instructional design perspective already in the training phase of the AI.
DEEP WRITE is a project funded by the German Federal Ministry of Education and Research (BMBF) that aims to improve university teaching using AI. This paper is developed in the context of this project and it is based on thoughts developed within the team.
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Hackl, V., Müller, C. (2023). AI-Supported Acquisition of Argumentation Skills: Use Case ‘The Argueniser’. In: Brooks, E., Sjöberg, J., Møller, A.K., Edstrand, E. (eds) Design, Learning, and Innovation. DLI 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 493. Springer, Cham. https://doi.org/10.1007/978-3-031-31392-9_4
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