AMQuestioner: Training Critical Thinking with Question-Driven Interactive Argument Maps in Online Discussion
Qiyu Pan, Jianqiao Zeng, Jie Wang, Junyu Liu, Yihan Qiu, Kangyu Yuan, Zhenhui Peng
摘要
Critical thinking, which requires logical analyses on the problems and keeping open-minded to others' viewpoints, is a crucial skill when participating in online discussions. While existing works have explored visualizing the components of an argument in a map, i.e., argument map, to support critical thinking tasks, few of them have incorporated educational elements that aim at training critical thinking in online discussion. In this paper, based on a formative study (N = 57), we develop AMQuestioner, a critical thinking training tool that allows question-driven interactions with argument maps automatically extracted from a post thread. In AMQuestioner, users can explore others' claims with a chatbot via suggested questions and conduct critical thinking exercises by answering generated questions related to any claim in the map. A mixed-design study (N=24) reveals that, compared to a baseline tool without question-driven features, participants after training with AMQuestioner demonstrated significantly more improvements in independently writing arguments that are detailed, specific, and relevant to the topic. Participants with AMQuestioner also exhibited a stronger inclination toward open-mindedness to others' arguments during the three-days training process. We discuss design implications for future critical thinking training tools.
CCS Concepts: • Human-centered computing → Human computer interaction (HCI); Collaborative and social computing.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- DuoDrama: Supporting Screenplay Refinement Through LLM-Assisted Human ReflectionYuying Tang, Xinyi Chen, Haotian Li, Xing Xie 等CHI 2026 · 被引用 3 次
- InkIdeator: Supporting Chinese-Style Visual Design Ideation via AI-Infused Exploration of Chinese PaintingsShiwei Wu, Ziyao Gao, Zhendong He, Zongtan He 等CHI 2026 · 被引用 1 次
它引用的顶会 Paper15
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 被引用 64,255 次
- CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator NeedsMajeed Kazemitabaar, Runlong Ye, Xiaoning Wang, Austin Zachary Henley 等CHI 2024 · 被引用 246 次
- Sara, the Lecturer: Improving Learning in Online Education with a Scaffolding-Based Conversational AgentRainer Winkler, Sebastian Hobert, Antti Salovaara, Matthias Söllner 等CHI 2020 · 被引用 176 次
- ArgueTutor: An Adaptive Dialog-Based Learning System for Argumentation SkillsThiemo Wambsganss, Tobias Kueng, Matthias Söllner, Jan Marco LeimeisterCHI 2021 · 被引用 126 次
- AL: An Adaptive Learning Support System for Argumentation SkillsThiemo Wambsganss, Christina Niklaus, Matthias Cetto, Matthias Söllner 等CHI 2020 · 被引用 98 次
相关 Paper
- CriTrainer: An Adaptive Training Tool for Critical Paper ReadingKangyu Yuan, Hehai Lin, Shilei Cao, Zhenhui Peng 等UIST 2023 · 被引用 21 次
- Don't Just Tell Me, Ask Me: AI Systems that Intelligently Frame Explanations as Questions Improve Human Logical Discernment Accuracy over Causal AI explanationsValdemar Danry, Pat Pataranutaporn, Yaoli Mao, Pattie MaesCHI 2023 · 被引用 108 次
- CoArgue : Fostering Lurkers' Contribution to Collective Arguments in Community-based QA PlatformsChengzhong Liu, Shixu Zhou, Dingdong Liu, Junze Li 等CHI 2023 · 被引用 18 次
- CharacterCritique: Supporting Children's Development of Critical Thinking through Multi-Agent Interaction in Story ReadingZizhen Wang, Jiangyu Pan, Duola Jin, Jingao Zhang 等CHI 2025 · 被引用 11 次
- Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online DiscussionMeng Xia, Qian Zhu, Xingbo Wang, Fei Nie 等CSCW 2022 · 被引用 34 次
