ArgSchool: Computational Support for Learning Argumentative Writing in Digital School Education

Funding Agency

In this project, we aim to study how to support German school students in learning to write argumentative texts through computational methods that provide developmental feedback. These methods will assess and explain which aspects of a text are good, which need to be improved, and how to improve them, adapted to the student’s learning stage. We seek to provide answers to three main research questions: (1) How to robustly mine the structure of German argumentative learner texts? (2) How to effectively assess the learning stage of a student based on a given argumentative text? (3) How to provide developmental feedback to an argumentative text adapted to the learning stage? The motivation behind this DFG-funded project is that digital technology is more and more transforming our culture and forms of learning. While vigorous efforts are made to implement digital technologies in school education, software for teaching German is so far limited to simple multiple-choice tests and the like, not providing any formative, let alone individualized, feedback. Argumentative writing is one the most standard tasks in school education, taught incrementally at different ages. Due to its importance across school subjects, it defines a suitable starting point for more “intelligent” computational learning support. We focus on the structural composition of argumentative texts, leaving their content and its relation to underlying sources to future work.

 

Lead at LUHAI: Prof. Wachsmuth

Funding program: DFG

Project period: 2021–2024

Project website: https://kw.uni-paderborn.de/institut-fuer-germanistik-und-vergleichende-literaturwissenschaft/germanistische-sprachdidaktik/rezat/forschung/dfg-projekt-computergestuetztes-lernen