Sruti Narra
2026
Pedagogic Applications of Argument Maps to Enhance Critical Thinking: Thought Seeds, Argument Mapping, Collaborative Mapping
Sruti Narra
Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026)
Sruti Narra
Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026)
Argument maps are used extensively in Natural Language Processing (NLP), for training Large Language Models (LLMs) to analyze and generate arguments coherently. This paper discusses the pedagogic applications of the concept of argument mapping to enhance critical thinking in learning within educational contexts. The approach was found to be useful for shaping the thinking process during thesis writing and project courses and can be applied in higher education. In the age of rapid Gen AI advancement, it is important to embed critical thinking into education and such approaches can address challenges like AI overuse and potential loss of key skills and competences in learners. Argument mapping necessitates learners to visualize their thinking and while doing so, they not only achieve clarity of thought, but also make distinct connections between concepts in the form of arguments. Such clarity is at a much higher level compared to that achieved through concept or mind mapping as learners need to think in terms of well-formed claims and connections between them. In addition, collaborative argument mapping tasks could give learners opportunities for peer learning, and to concretize the abstract ideas through visualization and discussion.