ArgueTutor: An Adaptive Dialog-Based Learning System for Argumentation Skills
Abstract
Techniques from Natural-Language-Processing offer the opportunities to design new dialog-based forms of human-computer interaction as well as to analyze the argumentation quality of texts. This can be leveraged to provide students with adaptive tutoring when doing a persuasive writing exercise. To test if individual tutoring for students’ argumentation will help them to write more convincing texts, we developed ArgueTutor, a conversational agent that tutors students with adaptive argumentation feedback in their learning journey. We compared ArgueTutor with 55 students to a traditional writing tool. We found students using ArgueTutor wrote more convincing texts with a better quality of argumentation compared to the ones using the alternative approach. The measured level of enjoyment and ease of use provides promising results to use our tool in traditional learning settings. Our results indicate that dialog-based learning applications combined with NLP text feedback have a beneficial use to foster better writing skills of students.
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Students using the chatbot (treatment group) to conduct a writing exercise wrote more convincing texts with a better formal argumentation quality than the traditional approach (control group).
“The result showed that students using the chatbot (treatment group) to conduct a writing exercise wrote more convincing texts with a better formal argumentation quality than the traditional approach (control group).”
From Interacting with educational chatbots: A systematic review (2023) · cites this paper as Wambsganss et al., 2021
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- Authors
- Wambsganss, T., Kueng, T., Soellner, M., & Leimeister, J. M.
- Affiliations
- University of St.Gallen (CH)
- Information Systems and Systems Engineering University of Kassel, Germany
- Venue
- Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2021-05-06
- Pages
- 1-13
- OpenAlex
- W3128904553
- Cited by
- 138
- References
- 10
- Citations by year
- 2026: 19 · 2025: 38 · 2024: 31 · 2023: 31 · 2022: 16 · 2021: 2 · 2017: 1
- FWCI
- 8.92
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Alexandria (UniSG) (University of St.Gallen) (acceptedVersion)
- Alexandria (UniSG) (University of St.Gallen) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- adaptive tutoring, argumentation skills, argumentative writing, chatbots, argument quality, writing skills, student enjoyment, ease of use
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