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Ken Koedinger, Conrad Borchers, Paulo Carvalho, Yumou (James) Wei, John Stamper, Vincent Aleven, Michael Asher, Christine Kwon, Amy Ogan, Danielle Thomas, Steven Moore, Carolyn Rosé, Marshall An, Alex Houk, Ruiwei Xiao, Ashish Gurung, Shivang (Shiv) Gupta, Erin Gatz, I-Sheng (Eason) Chen, Bruce M. McLaren, Leah Teffera, Hayden Stec, Aditi Haiman
What’s Next for AI and Education
HCII Researchers Present Work at 3 Co-Located Conferences in Italy
The Human-Computer Interaction Institute (HCII) had a large presence at three educational technology-focused conferences last month in Palermo, Sicily, Italy.
The three conferences – the International Conference on Educational Data Mining (EDM 2025), the Association of Computing Machinery (ACM) Conference on Learning at Scale (L@S 2025), and the International Conference on Artificial Intelligence in Education (AIED 2025) – started on successive days and ran concurrently with some joint sessions.
Notably, this is the first time these three learning sciences conferences have been hosted at the same location. By doing so, it fostered interdisciplinary collaboration and gave hundreds of attendees at the University of Palermo the opportunity to engage with others working with artificial intelligence (AI) in education and large-scale learning systems.
“It was definitely challenging choosing between so many great parallel sessions, but bringing AIED, EDM, and L@S together created a unique atmosphere with broader attendance, stronger industry presence, and notable cross-pollination of ideas. I’m excited to see this momentum continue next year in Seoul,” said Conrad Borchers, PhD student in human-computer interaction.
In addition to the increased attendance, the broader participation is also encouraging this year.
“For years, HCII faculty and students have been the biggest contributors of papers to the AI in Education (AIED) conference. What’s great about the huge growth in conference participation this year is how many others are now excited about this field that we’ve been long committed to,” said University Professor Ken Koedinger.
HCII researchers’ contributions spanned a wide range of topics including student engagement and motivation, the effectiveness of feedback and goal-setting, algorithmic fairness, and the role of large language models in clustering, assessment, and culturally responsive teaching.
Collectively, the papers used real-world classroom data and intelligent tutoring systems to understand and support learners through adaptive, data-informed interventions. They also explored how AI and learning analytics can enhance educational behavior, improve feedback, detect engagement, and support teachers and parents. Learn more about HCII authors’ contributions at the three conferences below.
EDM 2025
Educational Data Mining (EDM) took place July 21-23, 2025. The area of EDM utilizes data mining, machine learning and statistics to analyze information from various data sources in order to improve learning outcomes.
Carnegie Mellon University authors contributed to the following papers:
- Does Student Learning Rate Depend on Feedback Type and Prior Knowledge? – Hendrik Fleischer, Arne Noglik, Conrad Borchers and Sascha Schanze
- KCluster: An LLM-based Clustering Approach to Knowledge Component Discovery – Yumou Wei, Paulo Carvalho and John Stamper
- Predicting Teacher Interventions in K-12 Classrooms Using Disengagement, Struggle and Help-Seeking – Qiao Jin, Conrad Borchers, Stephen Fancsali and Vincent Aleven
- Starting Seatwork Earlier as a Valid Measure of Student Engagement – Ashish Gurung, Jionghao Lin, Zhongtian Huang, Conrad Borchers, Ryan Baker, Vincent Aleven and Kenneth Koedinger
- Toward Sufficient Statistical Power in Algorithmic Bias Assessment: A Test for ABROCA – Conrad Borchers
In addition, faculty Ken Koedinger and Paulo Carvalho were part of the organizing committee for the Educational Data Mining in Computer Science Education (CSEDM) Workshop, a workshop dedicated to facilitate a discussions around Educational Data Mining (EDM) and AI in Computer Science Education.
For more information, view the EDM 2025 Proceedings.
Learning@Scale 2025
Learning@Scale (L@S) was held July 22-23, 2025. This part of the field explores the study and design of learning environments that can effectively teach a very large number of students. Broadly, it looks at how technology, data, intelligent tutoring systems and new teaching methods can support learning in very large or global classrooms.
CMU authors contributed to the following papers and were involved with running three workshops at Learning@Scale:
- 🏆 Best Paper Award Validating a New Approach for Measuring Student Engagement in Remote, Resource-Limited Learning Environments – Michael Asher, Christine Kwon, John Stamper, Amy Ogan and Paulo Carvalho
- Advancing the Science of Teaching with Tutoring Data: A Collaborative Workshop with the National Tutoring Observatory - Danielle R. Thomas, Dorottya Demszky, Kenneth R. Koedinger, Joshua Marland, Doug Pietrzak, Justin Reich, Rachel Slama, Amalia Toutziaridi and René F. Kizilcec
- Sixth Annual Workshop on A/B Testing and Platform-Enabled Learning Engineering (PELE) - April Murphy, Stephen E. Fancsali, Steve Ritter, Neil Heffernan, Debshila Basu Mallick, Jeremy Roschelle, Danielle McNamara, Joseph Jay Williams, John Stamper, Norman Bier, Jeff Carver
- Advancing the Science of Teaching with Tutoring Data: A Collaborative Workshop with the National Tutoring Observatory (website) - Danielle R. Thomas, Dorottya Demszky, Kenneth R. Koedinger, Joshua Marland, Doug Pietrzak, Justin Reich, Rachel Slama, Amalia Toutziaridi, René F. Kizilcec
- Learnersourcing: Student-generated Content @ Scale: 3rd Annual Workshop - Steven Moore, Anjali Singh, Xinyi Lu, Hyoungwook Jin, Hassan Khosravi, Paul Denny, Christopher Brooks, Xu Wang, Juho Kim, John Stamper
For more information, view the Learning@Scale 2025 Proceedings.
AIED 2025
Artificial Intelligence in Education (AIED) took place July 22-26, 2025. AIED aims to advance the science and engineering of intelligent human-technology ecosystems that support learning.
The theme of AIED 2025 was, “AI as a Catalyst for Inclusive, Personalised, and Ethical Education: Empowering Teachers and Students for an Equitable Future.”
CMU authors contributed to the following papers and workshops at AIED 2025:
- 🏅Best Paper Nomination Who’s Got the Power? Data Feminism as a Lens for Designing AIED Engagement Systems - Angela E. B. Stewart, Jaemarie Solyst, Xinyi Bao, Paras Sharma, Amanda Buddemeyer, Tara Nkrumah, Amy Ogan, and Erin Walker
- 🏅Best Paper Nomination Epistemic Curiosity in K-12 AI education: A Trajectory Analysis - Min Zhuang, Shiyan Jiang, Daria Smyslova, Carolyn Rose and Jie Chao
- AI Knows Best? The Paradox of Expertise, AI-Reliance, and Performance in Educational Tutoring Decision-Making Tasks - Eason Chen, Jeffrey Li, Scarlett Huang, Xinyi Tang, Jionghao Lin, Paulo Carvalho and Kenneth Koedinger
- Can Large Language Models Match Tutoring System Adaptivity? A Benchmarking Study - Conrad Borchers and Tianze Shou
- Comparing a Human’s and a Multi-Agent System’s Thematic Analysis: Assessing Qualitative Coding Consistency - Sebastian Simon, Elham Tajik, Conrad Borchers, Bahar Shahrokhian, Sreecharan Sankaranarayanan, Francesco Balzan, Sebastian Strauss, Sree Aurovindh Viswanathan, Amine Hatun Ataş, Mia Čarapina, Li Liang and Berkan Celik
- Detecting Informal Reasoning Errors in Spoken Arguments: A Difficulty Factors Assessment of Distracted Reasoning - Nicholas Diana and John Stamper
- Deceptive Overgeneralization in Adaptive Learning - Marshall An and John Stamper
- Engagement and Learning Benefits of Goal Setting with Rewards in Human-AI Tutoring - Conrad Borchers, Alex Houk, Vincent Aleven and Kenneth R. Koedinger
- Exploring GenAI’s Role in Instructional Design: An A/B Experiment on Learning and Self-Efficacy - Steven Moore, Lydia Eckstein, Christine Kwon and John Stamper
- Exploring How LLMs Empower K-12 Teachers in Culturally Relevant Pedagogy - Jiayi Wang, Ruiwei Xiao, Xinying Hou, Hanqi Li, Ying Jui Tseng, John Stamper and Ken Koedinger
- From First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation - Jie Cao, Chloe Qianhui Zhao, Xian Chen, Shuman Wang, Christian Schunn, Kenneth R. Koedinger and Jionghao Lin
- Human Tutoring Increases AI Tutor Use, Leading to Better Learning Outcomes - Ashish Gurung, Jionghao Lin, Jordan Gutterman, Danielle R Thomas, Alex Houk, Shivang Gupta, Emma Brunskill, Lee Branstetter, Kenneth Koedinger and Vincent Aleven
- Improving Open-Response Assessment with LearnLM - Danielle R Thomas, Conrad Borchers, Shambhavi Bhushan, Sanjit Kakarla, Alex Houk, Ralph Abboud, Erin Gatz, Shivang Gupta and Kenneth R Koedinger
- Involving Parents and Caregivers in Intelligent Tutoring Systems: A Design Probe Study - Conrad Borchers, Ha Tien Nguyen, Paulo F. Carvalho, Kenneth R. Koedinger and Vincent Aleven
- PromptPair: A Personalized Multi-Agent Learning System for Developing Prompt Engineering Literacy in K-12 Educators - Cindy Peng, Hainuo Chen, Michael C. Sutton, and Steven Moore
- SlideItRight: Using AI to Find Relevant Slides and Provide Feedback for Open-Ended Questions - Chloe Qianhui Zhao, Jie Cao, Eason Chen, Kenneth R. Koedinger and Jionghao Lin
- Student Perceptions of Adaptive Goal Setting Recommendations: A Design Prototyping Study - Conrad Borchers, Cindy Peng, Qianru Lyu, Paulo F. Carvalho, Kenneth R. Koedinger and Vincent Aleven
- Utilizing Log-based and Neurophysiological Measures to Understand Engagement and Learning with Intelligent Tutoring Systems - Yushuang Liu, Ido Davidesco, Bruce M. McLaren, J Elizabeth Richey, Xiaorui Xue, Leah Teffera, Hayden Stec, Jiayi Zhang, Suyi Liu and Elana Golumbic
HCI PhD student Ruiwei Xiao was the lead organizer of AI Literacy for All, the first international workshop on AI literacy education at AIED. The inaugural ALIT4ALL Workshop aimed to foster a global community dedicated to advancing AI Literacy Education for learners worldwide of all ages and shaping a future with AI-literate generations.
Professor Bruce McLaren was a co-chair of the Blue Sky track at the conference, which presents papers about the possible future areas of impact in AI and Education.
Two HCII PhD students participated in the AIED 2025 Doctoral Consortium. Aditi Haiman presented a paper titled “Comparing the Effectiveness of Digital Game-Based Learning and Embodied Learning,” co-authored with advisor McLaren and external committee member Ivon Arroyo. Haiman hopes that this work will be a start on her PhD dissertation. Conrad Borchers presented “Intelligent Support for Practice Goal Setting to Enhance Learning,” advised by HCII faculty Vincent Aleven and Ken Koedinger. This work is a precursor to Borchers’ thesis proposal this September.
Steven Moore, postdoc, was also part of the organizing committee for the workshop Applications of Generative AI to Support Teaching and Learning in Higher Education.
For more information, view the AIED 2025 Proceedings.
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