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ORCID18th EDM 2025: Palermo, Italy
- Caitlin Mills, Giora Alexandron, Davide Taibi, Giosuè Lo Bosco, Luc Paquette:
Proceedings of the 18th International Conference on Educational Data Mining, EDM 2025, Palermo, Italy, July 20-23, 2025. International Educational Data Mining Society 2025
Full Papers
- Rohit Murali, Cristina Conati, David Poole:
A Comparison of Real-Time User Classification Methods using Interaction Data for Open-ended Learning. - Juan D. Pinto, Luc Paquette:
A Constraints-Based Approach to Fully Interpretable Neural Networks for Detecting Learner Behaviors. - Yucheng Chu, Hang Li, Kaiqi Yang, Harry Shomer, Yasemin Copur-Gencturk, Leonora Kaldaras, Kevin C. Haudek, Joseph Krajcik, Namsoo Shin, Hui Liu, Jiliang Tang:
A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization. - Halim Acosta, Seung Y. Lee, Daeun Hong, Wookhee Min, Bradford W. Mott, Cindy E. Hmelo-Silver, James C. Lester:
A Multi-View Predictive Student Modeling Framework with Interpretable Causal Graph Discovery for Collaborative Learning Analytics. - Ahmad Slim, Chaouki T. Abdallah, Ameer Slim:
An Efficient Linearized Optimization Framework for Designing Balanced and Efficient Degree Plans. - Idir Saidi, Nicolas Durand, Frédéric Flouvat:
Analysis of Students' Attempts Trajectories in Learning Programming. - Leonidas Zotos, Hedderik van Rijn, Malvina Nissim:
Are You Doubtful? Oh, It Might Be Difficult Then! Exploring the Use of Model Uncertainty for Question Difficulty Estimation. - Muntasir Hoq, Ananya Rao, Reisha Jaishankar, Krish Piryani, Nithya Janapati, Jessica Vandenberg, Bradford W. Mott, Narges Norouzi, James C. Lester, Bita Akram:
Automated Identification of Logical Errors in Programs: Advancing Scalable Analysis of Student Misconceptions. - Efe Bozkir, Christian Kosel, Tina Seidel, Enkelejda Kasneci:
Automated Visual Attention Detection using Mobile Eye Tracking in Behavioral Classroom Studies. - Seyed Parsa Neshaei, Richard Lee Davis, Paola Mejia-Domenzain, Tanya Nazaretsky, Tanja Käser:
Bridging the Data Gap: Using LLMs to Augment Datasets for Text Classification. - Wan-Chong Choi, Chan-Tong Lam, António José Mendes:
Comparison of Data Imputation Performance in Deep Generative Models for Educational Tabular Missing Data. - Hanke Vermeiren, Abe D. Hofman, Maria Bolsinova:
Evaluating multidimensional extensions of the Elo rating systems for tracking ability in online learning environments. - Süleyman Özdel, Can Sarpkaya, Efe Bozkir, Hong Gao, Enkelejda Kasneci:
Examining the Role of LLM-Driven Interactions on Attention and Cognitive Engagement in Virtual Classrooms. - Frank Stinar, Haejin Lee, Clara Belitz, Nidhi Nasiar, Stephen Fancsali, Steve Ritter, Husni Almoubayyed, Ryan Baker, Jaclyn Ocumpaugh, Nigel Bosch:
Fairness of Bayesian Knowledge Tracing for Math Learners of Different Reading Ability. - Yanping Pei, Adam Sales, Hyeon-Ah Kang, Tiffany A. Whittaker:
Fully Latent Principal Stratification with Misspecified Measurement Models in Intelligent Tutoring Systems. - Liang Tang, Nigel Bosch:
Human-crafted Features in Machine Learning Increase Trust but Risk Over-reliance. - Jiawei Li, Qianru Lyu, Wei Qiu, Andy W. H. Khong:
Improving Course Recommendation Systems with Explainable AI: LLM-Based Frameworks and Evaluations. - Chelsea Chandler, Rohit Raju, Jason G. Reitman, William R. Penuel, Monlin Monica Ko, Jeffrey B. Bush, Quentin Biddy, Sidney K. D'Mello:
Improving the Generalizability of Models of Collaborative Discourse. - Yumou Wei, Paulo Carvalho, John C. Stamper:
KCluster: An LLM-based Clustering Approach to Knowledge Component Discovery. - Ruikun Hou, Babette Bühler, Tim Fütterer, Efe Bozkir, Peter Gerjets, Ulrich Trautwein, Enkelejda Kasneci:
Multimodal Assessment of Classroom Discourse Quality: A Text-Centered Attention-Based Multi-Task Learning Approach. - Abubakir Siedahmed, Jaclyn Ocumpaugh, Zelda Ferris, Dinesh Kodwani, Neil T. Heffernan, Eamon Worden:
Nonstandard English and the Automated Scoring of Open-Ended Math Problems. - Anca O. Muresan, Mihaela Cardei, Ionut Cardei:
Predicting Student Success with Heterogeneous Graph Deep Learning and Machine Learning Models. - Anurata Prabha Hridi, Muntasir Hoq, Zhikai Gao, Collin Lynch, Rajeev Sahay, Seyyedali Hosseinalipour, Bita Akram:
Privacy-Preserving Distributed Link Predictions Among Peers in Online Classrooms Using Federated Learning. - Shunsuke Yoneda, Valdemar Svábenský, Gen Li, Daisuke Deguchi, Atsushi Shimada:
Ranking-Based At-Risk Student Prediction Using Federated Learning and Differential Features. - Ashish Gurung, Jionghao Lin, Zhongtian Huang, Conrad Borchers, Ryan Baker, Vincent Aleven, Kenneth R. Koedinger:
Starting Seatwork Earlier as a Valid Measure of Student Engagement. - Andres Felipe Zambrano, Jaclyn Ocumpaugh, Ryan S. Baker, Kirk Vanacore, Jordan Esiason, Jessica Vandenberg:
The Half-Life of Epistemic Emotions: How Motivation Influences Affective Chronometry. - Jannatun Naim, Jie Cao, Fareen Tasneem, Jennifer Jacobs, Brent Milne, James H. Martin, Tamara Sumner:
Towards Actionable Pedagogical Feedback: A Multi-Perspective Analysis of Mathematics Teaching and Tutoring Dialogue. - Hyeongdon Moon, Richard Lee Davis, Seyed Parsa Neshaei, Pierre Dillenbourg:
Using Large Multimodal Models to Extract Knowledge Components for Knowledge Tracing from Multimedia Question Information. - Grace D. Jaiyeola, Aaron Y. Wong, Richard L. Bryck, Caitlin Mills, Stephen Hutt:
Using Webcam-Based Eye Tracking during a Learning Task to Understand Neurodivergence.
Short Papers
- Rafael Alves da Silva, Lucas N. Ferreira:
A Holistic Recommendation System for Higher Education Academic Activities. - Francisco Ortin, Alonso Gago, José Quiroga, Miguel García:
Assistant for the detection of potential cheating behavior in synchronous online programming exams. - Eric Rudolph, Philipp Steigerwald, Jens Albrecht:
Comparing Human Roleplayers and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns. - Ting Cai, Qingyuan Tang, Yu Xiong, Lu Zhang:
Data-Knowledge-Driven Automatic Discovery of Teacher Classroom Teaching Behavior Indicator Categories. - Yucheng Chu, Peng He, Hang Li, Haoyu Han, Kaiqi Yang, Yu Xue, Tingting Li, Joseph Krajcik, Jiliang Tang:
Enhancing LLM-Based Short Answer Grading with Retrieval-Augmented Generation. - Philip I. Pavlik Jr., Luke Eglington:
Evolutionary Features for Mitigating Cold Starts in Logistic Knowledge Tracing. - Seehee Park, Danielle Shariff, Mohammad Amin Samadi, Nia Nixon, Sidney D'Mello:
From Discourse to Dynamics: Understanding Team Interactions Through Temporally Sensitive NLP. - Aylin Ozturk, Robin Schmucker, Tom M. Mitchell, Alper Tolga Kumtepe:
Heterogeneous Treatment Effects of Learning Analytics Dashboards: Do All Learners Benefit Equally? - Jiayi Zhang, Kirk Vanacore, Ryan S. Baker, Nabil Ch, Caitlin Mills, Owen Henkel:
How Much Mastery is Enough Mastery? The Relationship between Mastery in a Lesson and the Performance on the Subsequent Lesson. - Victor-Alexandru Padurean, Tung Phung, Nachiket Kotalwar, Michael Liut, Juho Leinonen, Paul Denny, Adish Singla:
Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback. - Juliette Woodrow, Chris Piech, Sanmi Koyejo:
Improving Generative AI Student Feedback: Direct Preference Optimization with Teachers in the Loop. - Ahmad Slim, Chaouki T. Abdallah, Elisha Allen, Ameer Slim:
Integrated Curriculum Analytics: Bridging Structure, Pass Rates, and Student Outcomes. - Kole Norberg, Husni Almoubayyed, Stephen Fancsali:
Linguistic Features Predicting Math Word Problem Readability Among Less-Skilled Readers. - Pranjli Khanna, Kaleb Mathieu, Kole Norberg, Husni Almoubayyed, Stephen Fancsali:
Math Content Readability, Student Reading Ability, and Behavior Associated with Gaming the System in Adaptive Learning Software. - Ali Sartaz Khan, Tolúlopé Ògúnrèmí, Ahmed Adel Attia, Dorottya Demszky:
Multi-Stage Speaker Diarization for Noisy Classrooms. - Yu Xiong, Shengyi Chen, Ting Cai, Lulu Chen, Jun Li:
Natural Language-Driven Teacher Gesture Recognition. - Haoze Du, Richard Li, Edward F. Gehringer:
Objective Metrics for Evaluating Large Language Models Using External Data Sources. - Andreea-Nicoleta Dutulescu, Stefan Ruseti, Mihai Dascalu, Danielle S. McNamara:
One Model to Score Them All: Unified Scoring of Learning Strategies with LLMs. - Michel C. Desmarais, Arman Bakhtiari, Ovide Kuichua, Samira Chiny Folefack Temfack, Chahé Nerguizian:
Short answer grading with sentence similarity and a few given grades. - Conrad Borchers:
Toward Sufficient Statistical Power in Algorithmic Bias Assessment: A Test for ABROCA. - Yunxuan Tang, Emma Harvey, Chengyuan Yao, Renzhe Yu, René F. Kizilcec, Christopher Brooks:
Understanding Predictive Models of Student Success with a Multiverse Analysis. - Genghu Shi, Shun Peng, Daphne Greenberg, Jan C. Frijters, Arthur C. Graesser:
Using Survival Analysis to Identify the Factors that Mitigate Attrition among Adult Learners with Low Literacy Skills in an ITS-based Literacy Program. - Jesper Dannath, Alina Deriyeva, Benjamin Paassen:
What is a Step? A User Study on How to Sub-divide the Solution Process of Introductory Python Tasks. - Maciej Pankiewicz, Yang Shi, Ryan S. Baker:
srcML-DKT: Enhancing Deep Knowledge Tracing with Robust Code Representations from srcML.
Posters and Demos
- Woorin Hwang, Hongming Li, Anna Pauline Aguinalde, Yilin Zhang, Jinnie Shin, Kent J. Crippen, Bruce F. Carroll:
Building Explainable Recommender System for Engineering Students Work-Integrated Learning (WIL). - Shreya Bhandari, Zach A. Pardos:
Can Language Models Grade Algebra Worked Solutions? Evaluating LLM-Based Autograders Against Human Grading. - Farshid Farzan, Israt Naiyer, Shaeekh Al Jahan, Brandon M. Booth:
Choosing to Learn: Achievement Goals, Immersion, and Competition in Non-Educational Gaming Contexts. - Sihan Jian, Saptarshi Bhowmik, K. Bret Staudt Willet:
Coping with ADHD in College: Topic Modeling and Sentiment Analysis of Online Peer Discussions on Reddit. - Hendrik Fleischer, Arne Noglik, Conrad Borchers, Sascha Schanze:
Does Student Learning Rate Depend on Feedback Type and Prior Knowledge? - Adam Sales, Charlotte Z. Mann, Johann Gagnon-Bartsch, Neil T. Heffernan:
Effect estimates using publicly available school-level data in a cluster-randomized educational experiment. - Kyosuke Takami, Satoshi Sekine, Yusuke Miyao:
Evaluating Local LLMs on Japanese National University Entrance Examination Dataset in Comparison with Student Performance. - Kevin Hong, Kia Karbasi, Gregory J. Pottie:
Extracting Causal Relations in Deep Knowledge Tracing. - Myrthe Braam, Maarten van der Velde, Hedderik van Rijn:
Generating Competitive Distractors from Student Error Data. - Songhee Han, Hunhui Na, Chaewon Kim:
Implementation, Not Capabilities: How Chatbot Utilization Shapes Learners' Navigation Patterns in MOOCs. - Arisha Khan, Nathaniel Li, Tori Shen, Anna N. Rafferty:
Just Read the Question: Enabling Generalization to New Assessment Items with Text Awareness. - Chaewon Kim, Fengfeng Ke, Nuodi Zhang, Alex Barrett:
LLM-supported Thematic Analysis: Evaluating GATOS Workflow on Complex Qualitative Data. - Aytaj Ismayilzada, Mirka Saarela, Ayaz Karimov:
Mining for Knowledge, Not Trouble: GDPR's Impact on Educational Data Mining. - Kia Karbasi, Kevin Hong, Mohammad Amin Samadi, Gregory J. Pottie:
Multi-Agent Collaborative Framework For Math Problem Generation. - Anika Kabir, Chandan Tankala, Daniel Lowd:
On the Practicality of Differential Privacy for Knowledge Tracing. - Mark Kim, Shreyas Raghuraman, Arno Puder, Craig Hayward, Hui Yang:
Predicting Course Transferability Using Deep Embeddings and Traditional Classifiers. - Vijay Prakash, Rishabh Bansal, Sanjay Sharma:
Quest-Genius: An AI-Driven Personalised Learning Platform Bridging Educational Gaps for Secondary Students - A Quasi-Experimental Study on Academic Performance, Engagement, and Equity. - Tomoki Takada, Saburo Higuchi, Yasuyuki Nakamura:
Visualization of Solution Processes to Reach the Correct Answer in Online Math Tests. - Qiao Jin, Conrad Borchers, Stephen Fancsali, Vincent Aleven:
Who to Help? A Time-Slice Analysis of K-12 Teachers' Decisions in Classes with AI-Supported Tutoring.
Doctoral Consortium
- Xinyi He:
Accelerating Practical Knowledge Sharing in Teachers' Communities with Human-aware Artificial Intelligence. - Morgan P. Lee, Neil T. Heffernan:
Concept Drift Detection for Knowledge Tracing. - Kabyashree Khanikar:
Investigating Cognitive Strategies in a Mental Rotation Task using Eye Tracking Heat Maps. - Shan Zhang, Anthony F. Botelho:
Scaffolding AI Literacy Through Student-AI Collaboration in Chatbot Development. - Marlene Steinbach, Shreya Bhandari, Jennifer Meyer, Zach A. Pardos:
When LLMs Hallucinate: Examining the Effects of Erroneous Feedback in Math Tutoring Systems.
Workshops and Tutorials
- Collin Lynch, Paul Deane, Piotr Mitros, Zhikai Gao, Damilola Babalola:
2nd Workshop on Educational Data Mining in Writing and Literacy Instruction. - Bita Akram, Yang Shi, Peter Brusilovsky, Thomas W. Price, Ken Koedinger, Paulo Carvalho, Shan Zhang, Andrew S. Lan, Juho Leinonen:
9th Educational Data Mining in Computer Science Education (CSEDM) Workshop. - Jade Cock, Frank Stinar, René F. Kizilcec, Tanja Käser:
Applying DebiasEd: A Package for Mitigating Unfairness in Educational Data. - Hang Li, Kaiqi Yang, Yucheng Chu, Jiliang Tang:
Bringing Generative Artificial Intelligence (GenAI) to Education. - Kirk Vanacore, Anthony F. Botelho, Avery Closser, Adam Sales, Neil T. Heffernan:
CausalEDM: Linking Innovations in Instructional Design and the Complex Behaviors that Underlie Learning Processes and Outcomes. - Peter W. Foltz, Gautam Biswas, Sidney D'Mello:
Interactive Workshop: Multimodal, Multiparty Learning Analytics (MMLA). - Daniil Karol, Ilya Vlasov, Katsiaryna Dzialets, Anna Potriasaeva, Anastasiia Birillo:
Leveraging KOALA for Programming Data Collection: A Half-Day Tutorial for Research Application. - Vinitra Swamy, Jakub Kuzilek, Juan D. Pinto, Luc Paquette, Tanja Käser, Qianhui Liu, Lea Cohausz:
The 2nd Human-Centric eXplainable AI in Education (HEXED) Workshop.
Industry Track
- Mohammad Arif Ul Alam, Geeta Verma, Eumie Jhong, Justin Otto Barber, Ashis Kumer Biswas:
A Bias-Aware Deep Learning Framework for Hierarchical Microcredential Classification. - Bogdan Yamkovenko, Charles Hogg, Maya Miller-Vedam, Phillip Grimaldi, Walt Wells:
Practical Evaluation of Deep Knowledge Tracing Models for use in Learning Platforms. - Maarten van der Velde, Malte Krambeer, Hedderik van Rijn:
Preserving the integrity of study behaviour in online retrieval practice using quantified learner dynamics.
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