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Large language models (LLMs) can empower teachers to build pedagogical conversational agents (PCAs) customized for their students.
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Pedagogical Agents for Fostering Question-Asking Skills in Children. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20) . Association for Computing Machinery, New York, NY, USA, 1–13
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Creating a Chatbot for and with Migrants: Chatbot Personality Drives Co-Design Activities. In Proceedings of the 2020 ACM Designing Interactive Systems Conference (Eindhoven, Netherlands) (DIS ’20) . Association for Computing Machinery, New York, NY, USA, 219–230
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ProtoChat: Supporting the Conversation Design Process with Crowd Feedback
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Heuristic Evaluation of Conversational Agents. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21) . Association for Computing Machinery, New York, NY, USA, Article 632, 15 pages
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Immigrant Students and English Learners: Challenges Faced in High School and Postsecondary Education
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Struggling to keep tabs on capstone projects: a chatbot to tackle student procrastination
Juanan Pereira and Óscar Díaz. 2021 · 2021
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Chatbots to support mental wellbeing of people living in rural areas: can user groups contribute to co-design?
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“Can you clarify what you said?”: Studying the impact of tutee agents’ follow-up questions on tutors’ learning. In Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part I 22 . Springer International Publishing, Cham, 395–407
Tasmia Shahriar and Noboru Matsuda. 2021 · 2021
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Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 437, 21 pages
J.D. Zamfirescu-Pereira, Richmond Y. Wong, Bjoern Hartmann, and Qian Yang. 2023b · 2023
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ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing. In Proceedings of the CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’24) . Association for Computing Machinery, New York, NY, USA, Article 304, 18 pages
Ian Arawjo, Chelse Swoopes, Priyan Vaithilingam, Martin Wattenberg, and Elena L. Glassman. 2024 · 2024
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The Skill Code: How to Save Human Ability in an Age of Intelligent Machines
Matt Beane. 2024 · 2024
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Towards Educator-Driven Tutor Authoring: Generative AI Approaches for Creating Intelligent Tutor Interfaces. In Proceedings of the Eleventh ACM Conference on Learning @ Scale (Atlanta, GA, USA) (L@S ’24) . Association for Computing Machinery, New York, NY, USA, 305–309
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Let’s talk it out: A chatbot for effective study habit behavioral change
Xiaoyi Tian, Zak Risha, Ishrat Ahmed, Arun Balajiee Lekshmi Narayanan, and Jacob Biehl. 2021 · 2021
Cited alongside, same era.
Pedagogical Agents for Interactive Learning: A Taxonomy of Conversational Agents in Education.. In ICIS . International Conference on Information Systems, Austin, Texas, USA
Florian Weber, Thiemo Wambsganss, Dominic Rüttimann, and Matthias Söllner. 2021 · 2021
Cited alongside, same era.
Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, et al · 2022
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Unveiling Practices of Customer Service Content Curators of Conversational Agents
Heloisa Candello, Claudio Pinhanez, Michael Muller, and Mairieli Wessel. 2022 · 2022
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Modeling and predicting students’ engagement behaviors using mixture Markov models
Rabia Maqsood, Paolo Ceravolo, Cristóbal Romero, and Sebastián Ventura. 2022 · 2022
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Adaptive Testing and Debugging of NLP Models. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, Dublin, Ireland, 3253–3267
Marco Tulio Ribeiro and Scott Lundberg. 2022 · 2022
Cited alongside, same era.
Chain–of–Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems , Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho (Eds.)
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed H. Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
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AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22) . Association for Computing Machinery, New York, NY, USA, Article 385, 22 pages
Tongshuang Wu, Michael Terry, and Carrie Jun Cai. 2022 · 2022
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Tommaso Calo and Christopher Maclellan. 2024 · 2024
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Proxona: Leveraging LLM-Driven Personas to Enhance Creators’ Understanding of Their Audience
Yoonseo Choi, Eun Jeong Kang, Seulgi Choi, Min Kyung Lee, and Juho Kim. 2024 · 2024
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Simulating Opinion Dynamics with Networks of LLM-based Agents
Yun-Shiuan Chuang, Agam Goyal, Nikunj Harlalka, Siddharth Suresh, Robert Hawkins, Sijia Yang, Dhavan Shah, Junjie Hu, and Timothy T. Rogers. 2024 · 2024
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CogBench: a large language model walks into a psychology lab
Julian Coda-Forno, Marcel Binz, Jane X. Wang, and Eric Schulz. 2024 · 2024
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A Complete Survey on LLM-based AI Chatbots
Sumit Kumar Dam, Choong Seon Hong, Yu Qiao, and Chaoning Zhang. 2024 · 2024
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On LLM Wizards: Identifying Large Language Models’ Behaviors for Wizard of Oz Experiments
Jingchao Fang, Nikos Arechiga, Keiichi Namaoshi, Nayeli Bravo, Candice Hogan, and David A. Shamma. 2024 · 2024
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Evaluating and Optimizing Educational Content with Large Language Model Judgments
Joy He-Yueya, Noah D Goodman, and Emma Brunskill. 2024 · 2024
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A Piece of Theatre: Investigating How Teachers Design LLM Chatbots to Assist Adolescent Cyberbullying Education. In Proceedings of the CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’24) . Association for Computing Machinery, New York, NY, USA, Article 668, 17 pages
Michael A. Hedderich, Natalie N. Bazarova, Wenting Zou, Ryun Shim, Xinda Ma, and Qian Yang. 2024 · 2024
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Generating Educational Materials with Different Levels of Readability using LLMs
Chieh-Yang Huang, Jing Wei, and Ting-Hao ’Kenneth’ Huang. 2024 · 2024
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PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits
Hang Jiang, Xiajie Zhang, Xubo Cao, Cynthia Breazeal, Deb Roy, and Jad Kabbara. 2024 · 2024
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Teach AI How to Code: Using Large Language Models as Teachable Agents for Programming Education. In Proceedings of the CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’24) . Association for Computing Machinery, New York, NY, USA, Article 652, 28 pages
Hyoungwook Jin, Seonghee Lee, Hyungyu Shin, and Juho Kim. 2024 · 2024
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Towards responsible development of generative AI for education: An evaluation-driven approach
Irina Jurenka, Markus Kunesch, Kevin R McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine Hermann, Daniel Kasenberg, Avishkar Bhoopchand, et al · 2024
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EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteria. In Proceedings of the CHI Conference on Human Factors in Computing Systems (, Honolulu, HI, USA,) (CHI ’24) . Association for Computing Machinery, New York, NY, USA, Article 306, 21 pages
Tae Soo Kim, Yoonjoo Lee, Jamin Shin, Young-Ho Kim, and Juho Kim. 2024 · 2024
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ChatGPT in education: A discourse analysis of worries and concerns on social media
Lingyao Li, Zihui Ma, Lizhou Fan, Sanggyu Lee, Huizi Yu, and Libby Hemphill. 2024c · 2024
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Guesses and Slips as Proficiency-Related Phenomena and Impacts on Parameter Invariance
Xiangyi Liao and Daniel M Bolt. 2024 · 2024
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PeerGPT: Probing the Roles of LLM-based Peer Agents as Team Moderators and Participants in Children’s Collaborative Learning. In Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems (CHI EA ’24) . Association for Computing Machinery, New York, NY, USA, Article 263, 6 pages
Jiawen Liu, Yuanyuan Yao, Pengcheng An, and Qi Wang. 2024a · 2024
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Xinyi Lu and Xu Wang. 2024 · 2024
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ChEdBot: Designing a Domain-Specific Conversational Agent in a Simulational Learning Environment Using LLMs
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Implicit bias in large language models: Experimental proof and implications for education
Nicole Jakubczyk Oster Melissa Warr and Roger Isaac. 2024 · 2024
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Using LLMs to Model the Beliefs and Preferences of Targeted Populations
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ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. In Proceedings of the 29th International Conference on Intelligent User Interfaces (Greenville, SC, USA) (IUI ’24) . Association for Computing Machinery, New York, NY, USA, 853–868
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Ruffle&Riley: From Lesson Text to Conversational Tutoring. In Proceedings of the Eleventh ACM Conference on Learning @ Scale (Atlanta, GA, USA) (L@S ’24) . Association for Computing Machinery, New York, NY, USA, 547–549
Robin Schmucker, Meng Xia, Amos Azaria, and Tom Mitchell. 2024 · 2024
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PATIENT- { \{ \ \backslash Psi } \} : Using Large Language Models to Simulate Patients for Training Mental Health Professionals
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Improving Collaborative Learning Performance Based on LLM Virtual Assistant. In 2024 13th International Conference on Educational and Information Technology (ICEIT) . 1–6
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Simulating Classroom Education with LLM-Empowered Agents
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