Summary
Argumentation is an omnipresent foundation of our daily communication and thinking. The ability of forming convincing arguments represents not only the basis for persuading an audience of novel ideas, but also plays a major role in strategic decision making and analyzing different standpoints. This has been recognized by the Organization for Economic Co‐operation and Development (OECD), which named these so‐called metacognition skills a major part of their Learning Framework 2030. However, due to steadily increasing lecture sizes, teachers and professors have difficulty providing ongoing and individualized feedback to students for training and improving their arguing skills. Therefore, students often suffer from a lack of support in their individual learners’ journey. A promising way to overcome this limitation and enable them to learn structured argumentation in large-scale scenarios is the usage of adaptive technology-enhanced applications. Within this research project, we explored the potential of argumentation feedback systems that provide continuous and personalized recommendations to actively support students in improving their ability to argue in a structured, logical and reflective way - autonomously and independently of an instructor, time and place. Accordingly, the project focused on the following two research questions: (i) How can we identify the key characteristics of arguments in student-written texts and use them to measure the quality of the reasoning presented in it?, and (ii) To what extent does a technology-enhanced feedback tool impact the development of students’ argumentation skills in the writing process?
- Topics: Argument Mining, Writing Support Systems, E-Learning
- Funding Period: 2019 - 2020 (18 months)
- Project Partners: Institute of Computer Science, University of St. Gallen (Lehrstuhl Prof. Dr. Handschuh), Institut für Wirtschaftsinformatik, University of St. Gallen (Lehrstuhl Prof. Dr. Leimeister)
