Computational Support for Learning Argumentative Writing in Digital School Education

• Applicants: Professorin Dr. Sara Rezat; Professor Dr. Henning Wachsmuth
• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing ; General and Domain-Specific Teaching and Learning
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 453073654

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 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.Due to several studies, the integration of counter-argumentation is an enormous challenge in the developmental knowledge acquisition for argumentative writing. To support this computationally, we will develop analysis methods that mine the claims, reasons, and counter-considerations of arguments from German learner texts and that assess the learning stage of the learner on this basis. The output then serves as input to methods that synthesize learning stage-specific feedback, e.g., pointing a student to missing counter-considerations and potential positions for including it. The project has four core objectives: (1) We aim to establish a German corpus of about 1500 manually annotated learner texts from three age groups. (2) On this basis, we develop computational methods for mining and assessing arguments. (3) We acquire feedback on learner texts and evaluate this feedback. (4) We develop methods to synthesize learning stage-specific feedback. The empirical evaluation combines didactic knowledge with the developed methods, in order to qualitatively explore the capabilities and limitations of providing developmental feedback, both in technical and in social regards.

• DFG Programme: Research Grants