Warm Congratulations to All Authors!
Long Papers
- Aaron Haim, Robert Gyurcsan, Chris Baxter, Stacy Shaw and Neil Heffernan – How to Open Science: Debugging Reproducibility within the Educational Data Mining Conference.
- Afrizal Doewes, Nughthoh Arfawi Kurdhi and Akrati Saxena – Evaluating Quadratic Weighted Kappa as the Standard Performance Metric for Automated Essay Scoring.
- Antonette Shibani, Ratnavel Rajalakshmi, Faerie Mattins, Srivarshan Selvaraj and Simon Knight – Visual representation of co-authorship with GPT-3: Studying human-machine interaction for effective writing.
- Anup Shakya, Vasile Rus and Deepak Venugopal – Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data.
- Boxuan Ma, Gayan Prasad Hettiarachchi, Sora Fukui and Yuji Ando – Exploring the effectiveness of Vocabulary Proficiency Diagnosis Using Linguistic Concept and Skill Modeling.
- Hagit Gabbay and Anat Cohen – Unfolding Learners’ Response to Different Versions of Automated Feedback in a MOOC for Programming – A Sequence Analysis Approach.
- Hamid Karimi, Kaitlin Torphy Knake and Kenneth A. Frank – An Analysis of Diffusion of Teacher-curated Resources on Pinterest.
- Harshita Chopra, Yiwen Lin, Mohammad Amin Samadi, Jacqueline G. Cavazos, Renzhe Yu, Spencer Jaquay and Nia Nixon – Semantic Topic Chains for Modeling Temporality of Themes in Online Student Discussion Forums.
- Husni Almoubayyed, Stephen Fancsali and Steve Ritter – Generalizing Predictive Models of Reading Ability in Adaptive Mathematics Software.
- Janine Langebein, Till Massing, Jens Klenke, Natalie Reckmann, Michael Striewe, Michael Goedicke and Christoph Hanck – A Data Mining Approach for Detecting Collusion in Unproctored Online Exams.
- Jauwairia Nasir, Aditi Kothiyal, Haoyu Sheng and Pierre Dillenbourg – To speak or not to speak, and what to speak, when doing task actions collaboratively.
- Kerstin Wagner, Agathe Merceron, Petra Sauer and Niels Pinkwart – Can the Paths of Successful Students Help Other Students With Their Course Enrollments?
- Lea Cohausz, Andrej Tschalzev, Christian Bartelt and Heiner Stuckenschmidt – Investigating the Importance of Demographic Features for EDM-Predictions.
- Mélina Verger, Sébastien Lallé, François Bouchet and Vanda Luengo – Is Your Model “MADD”? A Novel Metric to Evaluate Algorithmic Fairness for Predictive Student Models.
- Muntasir Hoq, Peter Brusilovsky and Bita Akram – Analysis of an Explainable Student Performance Prediction Model in an Introductory Programming Course.
- Philip I. Pavlik Jr. and Luke G. Eglington – Automated Search for Logistic Knowledge Tracing Models.
- Preya Shabrina, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi and Tiffany Barnes – Learning Problem Decomposition-Recomposition with Data-driven Chunky Parsons Problem within an Intelligent Logic Tutor.
- Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes and Thomas Price – KC-Finder: Automated Knowledge Component Discovery for Programming Problems.
Short Papers
- Amir Zur, Isaac Applebaum, Jocelyn Nardo, Dory DeWeese, Sameer Sundrani and Shima Salehi – Meta-Learning for Better Learning: Using Meta-Learning Methods to Automatically Label Exam Questions with Detailed Learning Objectives.
- Amruth Kumar – Using Markov Matrix to Analyze Students’ Strategies for Solving Parsons Puzzles.
- Ayaz Karimov, Mirka Saarela and Tommi Kärkkäinen – Clustering to define interview participants for analyzing student feedback: a case of Legends of Learning.
- Ethan Prihar, Kirk Vanacore, Adam Sales and Neil Heffernan – Effective Evaluation of Online Learning Interventions with Surrogate Measures.
- Jean Vassoyan, Jill-Jênn Vie and Pirmin Lemberger – Towards Scalable Adaptive Learning with Graph Neural Networks and Reinforcement Learning
- Machi Shimmei and Noboru Matsuda – Can’t Inflate Data? Let the Models Unite and Vote: Data-agnostic Method to Avoid Overfit with Small Data.
- Md Akib Zabed Khan and Agoritsa Polyzou – Session-based Course Recommendation Frameworks using Deep Learning.
- Mengxue Zhang, Neil Heffernan and Andrew Lan – Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions.
- Morgan P Lee, Ethan Croteau, Ashish Gurung, Anthony F. Botelho and Neil T. Heffernan – Knowledge Tracing Over Time: A Longitudinal Analysis.
- Narjes Rohani, Kobi Gal, Michael Gallagher and Areti Manataki – Early Prediction of Student Performance in a Health Data Science MOOC.
- Regina Kasakowskij, Joerg M. Haake and Niels Seidel – Self-Assessment Task Processing Behavior of Students in Higher Education.
- Sami Baral, Anthony F. Botelho, Abhishek Santhanam, Ashish Gurung, Li Cheng and Neil Heffernan – Auto-scoring Student Responses with Images in Mathematics.
- Stav Tsabari, Avi Segal and Kobi Gal – Predicting Bug Fix Time in Students’ Programming with Deep Language Models.
- Stephen Hutt, Sanchari Das and Ryan Baker – The Right To Be Forgotten and Educational Data Mining: Challenges and Paths Forward.
- Tianze Shou, Conrad Borchers, Shamya Karumbaiah and Vincent Aleven – Optimizing Parameters for Accurate Position Data Mining in Diverse Classrooms Layouts.
- Tung Phung, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla and Gustavo Soares – Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models.
- Valdemar Švábenský, Ryan S. Baker, Andrés Zambrano, Yishan Zou and Stefan Slater – Towards Generalizable Detection of Urgency of Discussion Forum Posts.
- Vishal Kuvar, Lauren Flynn, Laura Allen and Caitlin Mills – Partner Keystrokes can Predict Attentional States during Chat-based Conversations.
- Wei Chu and Philip I. Pavlik Jr. – The Predictiveness of PFA is Improved by Incorporating the Learner’s Correct Response Time Fluctuation.
- Yinuo Xu and Zach Pardos – Mining Detailed Course Transaction Records for Semantic Information.
- Yunsung Kim, Sree Sankaranarayanan, Chris Piech and Candace Thille – Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency.
- Zilin Dai, Andrew McReynolds and Jacob Whitehill – In Search of Negative Moments: Multi-Modal Analysis of Teacher Negativity in Classroom Observation Videos.
Posters
- Anan Schütt, Tobias Huber, Ilhan Aslan and Elisabeth André – Fast Dynamic Difficulty Adjustment for Intelligent Tutoring Systems with Small Datasets.
- Anirban Roy Chowdhury, Nandagopal K S, Vijay Prakash and Syaamantak Das – A comparative analysis of the cognitive levels of Science and Mathematics secondary school board examination questions in India.
- Antonette Shibani, Ratnavel Rajalakshmi, Srivarshan Selvaraj, Faerie Mattins and Dhivya Chinnappa – Explainable models for feedback design: An argumentative writing example.
- Ayaz Karimov, Mirka Saarela and Tommi Kärkkäinen – Improving learning in under-resourced communities by using online educational platforms: the case of Khan Academy.
- Brad Din, Yael Feldman-Maggor, Tanya Nazaretsky and Giora Alexandron – Automated Identification and Validation of the Optimal Number of Knowledge Profiles in Student Response Data.
- Colton Botta, Avi Segal and Kobi Gal – Sequencing Educational Content Using Diversity Aware Bandits.
- Conrad Borchers, Lennart Klein, Hayden Johnson and Christian Fischer – Timing Matters: Inferring Educational Twitter Community Switching from Membership Characteristics.
- Deliang Wang, Dapeng Shan, Yaqian Zheng, Kai Guo, Gaowei Chen and Yu Lu – Can ChatGPT Detect Student Talk Moves in Classroom Discourse? A Preliminary Comparison with Bert.
- Erwin Daniel López Zapata, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo and Atsushi Shimada – LECTOR: An attention-based model to quantify e-book lecture slides and topics relationships.
- Gyanesh Jain, Aditya Sharma, Nirmal Patel and Amit Nanavati – Tool Usage and Efficiency in an Online Test.
- Ikenna Osakwe – Using reinforcement learning for automatic detection of effective strategies for self-regulated learning.
- Luca Mouchel, Thiemo Wambsganss, Paola Mejia and Tanja Käser – Understanding Revision Behavior in Adaptive Writing Support Systems for Education.
- M Parvez Rashid, Divyang Doshi, Edward F. Gehringer, Sai Venkata Vinay Kumar Samudrala and Qinjin Jia – “Can we reach agreement?”: A context- and semantic-based clustering approach with semi-supervised text-feature extraction for finding disagreement in peer-assessment formative feedback.
- Mayank Sahu, Daevesh Singh, Deepak Pathak, Chandan Dasgupta and Ramkumar Rajendran – Boredom and Frustration detection in TELE for Engineering Design Problem.
- Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee, Hunter McNichols, Aritra Ghosh and Andrew Lan – A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing.
- Olivier Allègre, Amel Yessad and Vanda Luengo – Discovering prerequisite relationships between knowledge components from an interpretable learner model.
- Ran Bi and Shiyao Wei – Exploring the Implementation of NLP Topic Modeling for Understanding the Dynamics of Informal Learning in an AI Painting Community
- Sylvio Rüdian, Clara Schumacher, Jakub Kužílek and Niels Pinkwart – Pre-selecting Text Snippets to provide formative Feedback in Online Learning
- Tanya Nazaretsky, Hacı Hasan Yolcu, Moriah Ariely and Giora Alexandron – Towards Automated Assessment of Scientific Explanations in Turkish using Language Transfer
- Yo Ehara – Course Concepts: How Readable Are They for ESL Learners?
- Yo Ehara – Measuring Similarity between Manual Course Concepts and ChatGPT-generated Course Concepts
Doctoral Consortium
- Antony Prakash – Exploring students’ learning processes by logging and analyzing their interaction behavior in a Virtual Reality learning environment.
- Debarshi Nath, Dragan Gasevic and Ramkumar Rajendran– A Trace-Based Multimodal Generalized SRL Framework for Reading-Writing Tasks.
- Guanyu Chen and Yan Liu – Response Process Data in Educational and Psychological Assessment: A Scoping Review of Empirical Studies.
- Jyoti Shaha and Ramkumar Rajendran– Analyzing the impact of metacognition prompts on learning in CBLE.
- Meera Pawar and Sahana Murthy– Understanding Learners Alternate Conceptions through Interaction Patterns During analogical reasoning.
- Nisumba Soodhani K – Analyzing Team Cognition and Combined Efficacy In Makerspaces Using Multimodal Data.
- Pratiksha Patil, Ashwin T S and Ramkumar Rajendran – Fostering Interaction in Computer-Supported Collaborative Learning Environment.
- Ram Das Rai – Designing a Learning Environment to Foster Critical Thinking.
- Suprabha Jadhav – Data Driven Online Training Program for Education Robotics Competition.
- Vishwas Badhe, Chandan Dasgupta and Ramkumar Rajendran – Investigating teams’ Socially Shared Metacognitive Regulation (SSMR) and trans-activity in project-based computer supported collaborative learning environment.
Demos
- Jinglei Yu, Zitao Liu, Mi Tian, Deliang Wang and Yu Lu – A Multimodal Language Learning System for Chinese Character Using Foundation Model
- Arun Balajiee Lekshmi Narayanan, Khushboo Thaker, Peter Brusilovsky and Jordan Barria-Pineda – Help Me Read! Expanding Student’s Reading with Wikipedia Articles
- Haoyu Liu, Fan-Yun Sun, Frieda Rong, Kumi Nakajima, Nicholas Haber and Shima Salehi – Characterizing Learning Progress of Problem-Solvers Using Puzzle-Solving Log Data