Computer-Based Generation of Learner-Sensitive Feedback to Argumentative Learner Texts

Author(s):
Kilsbach, Sebastian; Michel, Nadine
Editor(s):
Boogaart, Ronny; Garssen, Bart; Jansen, Henrike; Van Leeuwen, Maarten; Pilgram, Roosmaryn; Reuneker, Alex
Published
2024
Publication type
Article / Letter to editor

Abstract

What is learner-sensitive feedback to argumentative learner texts when it is to be issued computer-based? Learning stages are difficult to quantify. The paper provides insight into the history of research since the 1980s and a preview of what this automated feedback might look like. These questions are embedded in a research project at the Universities of Paderborn and Hannover, Germany, from which a software (project name ArgSchool) emerges that will provide such feedback.

AIargumentation miningdiscourse history(automatedlearner-sensitive) feedback
Date issued
2024
Language
English
Is part of
Proceedings of the Tenth Conference of the International Society for the Study of Argumentation (2024), p. 501-508
hdl
1887/4107831

Conference

Meeting name
10th Conference of the International Society for the Study of Argumentation (ISSA 2023)
Meeting location
Leiden, The Netherlands
Meeting date
2023-07-04 - 2023-07-07