{"id":582,"date":"2024-05-31T09:50:54","date_gmt":"2024-05-31T09:50:54","guid":{"rendered":"https:\/\/educationaldatamining.org\/edm2024\/?page_id=582"},"modified":"2024-07-03T18:41:15","modified_gmt":"2024-07-03T18:41:15","slug":"accepted-papers","status":"publish","type":"page","link":"https:\/\/educationaldatamining.org\/edm2024\/accepted-papers\/","title":{"rendered":"Accepted Papers"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Long Papers<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>DISTO: Evaluating Textual Distractors for Multiple Choice Questions using a Negative Sampling based Approach &#8211; Bilal Ghanem and Alona Fyshe<\/li>\n\n\n\n<li>Parametric Constraints for Bayesian Knowledge Tracing from First Principles &#8211; Denis Shchepakin, Sreecharan Sankaranarayanan and Dawn Zimmaro<\/li>\n\n\n\n<li>Predicting GRE Scores from Application Materials in Test-Optional Admissions &#8211; Yijun Zhao, Zhengxin Qi, Son Tung Do, John Grossi, Jee Hun Kang and Gary Weiss<\/li>\n\n\n\n<li>Grading and Clustering Student Programs That Produce Probabilistic Output &#8211; Yunsung Kim, Jadon Geathers and Chris Piech<\/li>\n\n\n\n<li>Reexamining Learning Curve Analysis in Programming Education: The Value of Many Small Problems &#8211; Mehmet Arif Demirtas, Max Fowler and Kathryn Cunningham<\/li>\n\n\n\n<li>Evaluating and Optimizing Educational Content with Large Language Model Judgments &#8211; Joy He-Yueya, Noah Goodman and Emma Brunskill<\/li>\n\n\n\n<li>Assessing the Promise and Pitfalls of ChatGPT for Automated CS1-driven Code Generation &#8211; Muhammad Fawad Akbar Khan, Max Ramsdell, Erik Falor and Hamid Karimi<\/li>\n\n\n\n<li>On the Selection of Positive and Negative Samples for Contrastive Math Word Problem Neural Solver &#8211; Yiyao Li, Lu Wang, Jung Jae Kim, Chor Seng Tan and Ye Luo<\/li>\n\n\n\n<li>GPT vs. Llama2: Which Comes Closer to Human Writing? &#8211; Fernando Martinez, Gary Weiss, Miguel Palma, Haoran Xue, Alexander Borelli and Yijun Zhao<\/li>\n\n\n\n<li>Combining Dialog Acts and Skill Modeling: What Chat Interactions Enhance Learning Rates During AI-Supported Peer Tutoring? &#8211; Conrad Borchers, Kexin Yang, Jionghao Lin, Nikol Rummel, Kenneth R. Koedinger and Vincent Aleven<\/li>\n\n\n\n<li>A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies &#8211; Md Mirajul Islam, Xi Yang, John Hostetter, Adittya Soukarjya Saha and Min Chi<\/li>\n\n\n\n<li>When Chatting Isn&#8217;t Cheating: Mining and Evaluating Student Use of Chatbots and Other Resources During Open-Internet Exams &#8211; David Joyner, Zoey Anne Beda, Michael Cohen, Melanie Duffin, Amy Garcia Fernandez, Liz Hayes-Golding, Jonathan Hildreth, Alex Houk, Rebecca Johnson, Kayla Matchek and Ana Santos<\/li>\n\n\n\n<li>Using Large Language Models to Detect Self-Regulated Learning in Think-Aloud Protocols &#8211; Jiayi Zhang, Conrad Borchers, Vincent Aleven and Ryan S. Baker<\/li>\n\n\n\n<li>Propositional Extraction from Natural Speech in Small Group Collaborative Tasks &#8211; Videep Venkatesha, Abhijnan Nath, Ibrahim Khebour, Avyakta Chelle, Mariah Bradford, Jingxuan Tu, James Pustejovsky, Nathaniel Blanchard and Nikhil Krishnaswamy<\/li>\n\n\n\n<li>Towards Generalizable Agents in Text-Based Educational Environments: A Study of Integrating RL with LLMs &#8211; Bahar Radmehr, Adish Singla and Tanja K\u00e4ser<\/li>\n\n\n\n<li>Investigating Student Ratings with Features of Automatically Generated Questions: A Large-Scale Analysis using Data from Natural Learning Contexts &#8211; Benny Johnson, Jeff Dittel and Rachel Van Campenhout<\/li>\n\n\n\n<li>Beyond Accuracy: Embracing Meaningful Parameters in Educational Data Mining &#8211; Napol Rachatasumrit, Paulo Carvalho and Kenneth Koedinger<\/li>\n\n\n\n<li>Says Who? How different ground truth measures of emotion impact student affective modeling &#8211; Andres Felipe Zambrano, Nidhi Nasiar, Jaclyn Ocumpaugh, Alex Goslen, Jiayi Zhang, Jonathan Rowe, Jordan Esiason, Jessica Vandenberg and Stephen Hutt<\/li>\n\n\n\n<li>Multimodal Learning Analytics for Predicting Student Collaboration Satisfaction in Collaborative Game-Based Learning &#8211; Halim Acosta, Seung Lee, Bradford Mott, Haesol Bae, Krista Glazewski, Cindy Hmelo-Silver and James Lester<\/li>\n\n\n\n<li>How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses &#8211; Jionghao Lin, Eason Chen, Feifei Han, Ashish Gurung, Danielle R Thomas, Wei Tan, Ngoc Dang Nguyen and Kenneth Koedinger<\/li>\n\n\n\n<li>How Much Training is Needed? Reducing Training Time using Deep Reinforcement Learning in an Intelligent Tutor &#8211; Nazia Alam, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi and Tiffany Barnes<\/li>\n\n\n\n<li><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Industry &amp; Short Papers<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>An Evaluation of a Placement Assessment for an Adaptive Learning System &#8211; Jeffrey Matayoshi, Eric Cosyn, Christopher Lechuga and Hasan Uzun<\/li>\n\n\n\n<li>Non-Overlapping Leave Future Out Validation (NOLFO): Implications for Graduation Prediction &#8211; Lief Esbenshade, Jonathan Vitale and Ryan Baker<\/li>\n\n\n\n<li>Examining the Algorithmic Fairness in Predicting High School Dropouts &#8211; Chenguang Pan and Zhou Zhang<\/li>\n\n\n\n<li>Phone Use While Programming &#8211; Kaden Hart, Christopher Warren, Seth Poulsen and John Edwards<\/li>\n\n\n\n<li>Open Science and Educational Data Mining:&nbsp; Which Practices Matter Most? &#8211; Ryan S. Baker, Stephen Hutt, Christopher A. Brooks, Namrata Srivastava and Caitlin Mills<\/li>\n\n\n\n<li>Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming &#8211; Yang Shi, Min Chi, Tiffany Barnes and Thomas Price<\/li>\n\n\n\n<li>Promoting Theory-Building in Design-Based Research through Data-Based Models &#8211; Golnaz Arastoopour Irgens, Ibrahim Adisa, Deepika Sistla, Tolulope Famaye, Cinamon Bailey, Atefeh Behboudi and Adenike Adefisayo<\/li>\n\n\n\n<li>More, May not the Better: Insights from Applying Deep Reinforcement Learning for Pedagogical Policy Induction &#8211; Gyuhun Jung, Markel Sanz Ausin, Tiffany Barnes and Min Chi<\/li>\n\n\n\n<li>Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference &#8211; Owen Henkel, Zach Levonian, Chenglu Li and Millie Postle<\/li>\n\n\n\n<li>Navigating the Data-Rich Landscape of Online Learning: Insights and Predictions from ASSISTments &#8211; Aswani Yaramala, Soheila Farokhi and Hamid Karimi<\/li>\n\n\n\n<li>SingPAD: A&nbsp;Knowledge&nbsp;Tracing&nbsp;Dataset&nbsp;Based on Music Performance Assessment &#8211; Ying Zhang, Yan Zhang, Wei Xu, Zhifeng Wang and Jianwen Sun<\/li>\n\n\n\n<li>Large Language Models for In-Context Student Modeling: Synthesizing Student&#8217;s Behavior in Visual Programming &#8211; Manh Hung Nguyen, Sebastian Tschiatschek and Adish Singla<\/li>\n\n\n\n<li>Early Prediction of Student Dropout in Higher Education using Machine Learning Models &#8211; Or Goren, Liron Cohen and Amir Rubinstein<\/li>\n\n\n\n<li>Speaker Diarization in the Classroom: How Much Does Each Student Speak in Group Discussions? &#8211; Jiani Wang, Shiran Dudy, Xinlu He, Zhiyong Wang, Rosy Southwell and Jacob Whitehill<\/li>\n\n\n\n<li>A page jump recommendation model and result interpretation based on structured annotation methods &#8211; Wenhao Wang, Etsuko Kumamoto and Chengjiu Yin<\/li>\n\n\n\n<li>LOOL: Towards Personalization with Flexible &amp; Robust Estimation of Heterogeneous Treatment Effects &#8211; Duy Pham, Kirk Vanacore, Adam Sales and Johann Gagnon-Bartsch<\/li>\n\n\n\n<li>Problem-Solving Types and EdTech Effectiveness: A Model for Exploratory Causal Analysis &#8211; Adam Sales, Kirk Vanacore, Hyeon-Ah Kang and Tiffany Whittaker<\/li>\n\n\n\n<li>Investigating Student Interest in a Minecraft Game-Based Learning Environment: A Changepoint Detection Analysis &#8211; Yiqiu Zhou and Luc Paquette<\/li>\n\n\n\n<li>Feeling the Difficulty of Mathematics &#8211; Bledar Fazlija<\/li>\n\n\n\n<li>Generative AI for Peer Assessment Helpfulness Evaluation &#8211; Chengyuan Liu, Jialin Cui, Ruixuan Shang, Qinjin Jia, Parvez Rashid and Edward Gehringer<\/li>\n\n\n\n<li>Replicating an \u201cAstonishing Regularity in Student Learning Rates\u201d &#8211; Mary Ann Simpson, Kole Norberg and Stephen Fancsali<\/li>\n\n\n\n<li>Are You an Early Dropper or Late Shopper? Mining Enrollment Transaction Data to Study Procrastination in Higher Education &#8211; Conrad Borchers, Yinuo Xu and Zachary A. Pardos<\/li>\n\n\n\n<li>E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems &#8211; Yuma Miyazaki, Valdemar \u0160v\u00e1bensk\u00fd, Yuta Taniguchi, Fumiya Okubo, Tsubasa Minematsu and Atsushi Shimada<\/li>\n\n\n\n<li>Investigation of Behavioural Differences: Uncovering Behavioral Sources of Demographic Bias in Educational Algorithms &#8211; Jade Ma\u00ef Cock, Hugues Saltini, Haoyu Sheng, Riya Ranjan, Richard Davis and Tanja K\u00e4ser<\/li>\n\n\n\n<li>Principals&#8217; use of data analytics in Finnish schools &#8211; Ayaz Karimov, Mirka Saarela, Tommi K\u00e4rkk\u00e4inen and Sabina Aghayeva<\/li>\n\n\n\n<li>Automatic Matchmaking in two-versus-two sports &#8211; S\u00f6ren R\u00fcttgers, Ulrike Kuhl and Benjamin Paa\u00dfen<\/li>\n\n\n\n<li>Power Calculations for Randomized Controlled Trials with Auxiliary Observational Data &#8211; Jaylin Lowe, Charlotte Mann, Jiaying Wang, Adam Sales and Johann Gagnon-Bartsch<\/li>\n\n\n\n<li>Plagiarism Detection Using Keystroke Logs &#8211; Scott Crossley, Yu Tian, Joon Suh Choi, Langdon Holmes and Wesley Morris<\/li>\n\n\n\n<li>Who Should I Help Next? Simulation of Office Hours Queue Scheduling Strategy in a CS2 Course &#8211; Zhikai Gao, Gabriel Silva de Oliveira, Damilola Babalola, Collin Lynch and Sarah Heckman<\/li>\n\n\n\n<li>On Assessing the Faithfulness of LLM-generated Feedback on Student Assignments &#8211; Qinjin Jia, Jialin Cui, Ruijie Xi, Chengyuan Liu, Parvez Rashid, Ruochi Li and Edward Gehringer<\/li>\n\n\n\n<li>Analyzing Large Language Models for Classroom Discussion Assessment &#8211; Nhat Tran, Richard Correnti, Lindsay Clare Matsumura, Benjamin Pierce and Diane Litman<\/li>\n\n\n\n<li>Investigating the relations between students\u2019 affective states and the coherence in their activities in Open-Ended Learning Environments &#8211; Celestine Akpanoko, Ashwin T S, Grayson Cordell and Gautam Biswas<\/li>\n\n\n\n<li>Using Publicly Available Auxiliary Data to Improve Precision of Treatment Effect Estimation in a Randomized Efficacy Trial &#8211; Charlotte Mann, Jiaying Wang, Adam Sales and Johann Gagnon-Bartsch<\/li>\n\n\n\n<li>Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Train-ing Sequences on Category Learning &#8211; Meng Cao, Philip Pavlik Jr., Wei Chu and Liang Zhang<\/li>\n\n\n\n<li>Math in Motion: Analyzing Real-Time Student Collaboration in Computer-Supported Learning Environments &#8211; Hongming Li, Shan Zhang, Seiyon Lee, Ji-Eun Lee, Zirui Zhong, Erik Weitnauer and Anthony F. Botelho<\/li>\n\n\n\n<li>This Paper Was Written with the Help of ChatGPT: Exploring the Consequences of AI-Driven Academic Writing on Scholarly Practices &#8211; Hongming Li, Seiyon Lee and Anthony F. Botelho<\/li>\n\n\n\n<li>Enhancing Multimodal Learning Analytics: A Comparative Study of Facial Feature Capture Using Traditional vs 360-Degree Cameras in Collaborative Learning &#8211; Robin Jephthah Rajarathinam, Christian Palaguachi and Jina Kang<\/li>\n\n\n\n<li>De-Identifying Student Personally Identifying Information with GPT-4 &#8211; Shreya Singhal, Andres Felipe Zambrano, Maciej Pankiewicz, Xiner Liu, Chelsea Porter and Ryan S. Baker<\/li>\n\n\n\n<li>From Reaction to Anticipation: Predicting Future Affect &#8211; Andres Felipe Zambrano, Ryan S. Baker, Sami Baral, Neil Heffernan and Andrew Lan<\/li>\n\n\n\n<li>What metrics of participation balance predict outcomes of collaborative learning with a robot? &#8211; Yuya Asano, Diane Litman, Quentin King-Shepard, Tristan Maidment, Tyree Langley, Teresa Davison, Timothy Nokes-Malach, Adriana Kovashka and Erin Walker<\/li>\n\n\n\n<li>Building Learner Activity Models From Log Data Using Sequence Mapping and Hidden Markov Models &#8211; Paras Sharma, Angela E.B. Stewart, Qichang Li, Krit Ravichander and Erin Walker<\/li>\n\n\n\n<li>Multimodal, Multi-Class Bias Mitigation for Predicting Speaker Confidence &#8211; Andrew Emerson, Arti Ramesh, Patrick Houghton, Vinay Basheerabad, Navaneeth Jawahar and Chee Wee Leong<\/li>\n\n\n\n<li>Empowering Predictions of the Social Determinants of Mental Health through Large Language Model Augmentation in Students&#8217; Lived Experiential Essays &#8211; Mohammad Arif Ul Alam, Madhavi Pagare, Susan Davis, Geeta Verma, Ashis Biswas and Justin Barber<\/li>\n\n\n\n<li><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Posters &amp; Demos<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Mining Epistemic Actions of&nbsp; Programming Problem Solving with Chat-GPT &#8211; Rwitajit Majumdar, Prajish Prasad and Aamod Sane<\/li>\n\n\n\n<li>Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning &#8211; Elena Grazia Gado, Tommaso Martorella, Luca Zunino, Paola Mejia-Domenzain, Vinitra Swamy, Jibril Frej and Tanja K\u00e4ser<\/li>\n\n\n\n<li>Connecting Blinks to Constructs: How are We Arguing for Validity in Multimodal Learning Analytics? &#8211; Gahyun Sung and Hanall Sung<\/li>\n\n\n\n<li>The Construction and Analysis of Course Grades Across Public Universities &#8211; Hyun Jeong, Gary M. Weiss, Audrey Leung and Daniel D. Leeds<\/li>\n\n\n\n<li>Examining the Influence of Varied Levels of Domain Knowledge Base Inclusion in GPT-based Intelligent Tutors &#8211; Blake Castleman and Mehmet Kerem Turkcan<\/li>\n\n\n\n<li>Making Course Recommendation Explainable: A Knowledge Entity-Aware Model using Deep Learning &#8211; Tianyuan Yang, Baofeng Ren, Boxuan Ma, Md Akib Zabed Khan, Tianjia He and Shin&#8217;Ichi Konomi<\/li>\n\n\n\n<li>How Ready Are Generative Pre-trained Large Language Models for Explaining Bengali Grammatical Errors? &#8211; Subhankar Maity, Aniket Deroy and Sudeshna Sarkar<\/li>\n\n\n\n<li>Uncovering the Evolution of Topics about AI Painting: Dynamic Topic Modeling of 180k Discourse Data in an Online Community &#8211; Shiyao Wei and Ran Bi<\/li>\n\n\n\n<li>Tracking Classroom Movement Patterns with Person Re-Id &#8211; Xinlu He, Jiani Wang, Viet Anh Trinh, Andrew McReynolds and Jacob Whitehill<\/li>\n\n\n\n<li>Fair Prediction of Students&#8217; Summative Performance Changes Using Online Learning Behavior Data &#8211; Zifeng Liu, Xinyue Jiao, Chenglu Li and Wanli Xing<\/li>\n\n\n\n<li>AUTOMATED SCORING OF LEARNERS\u2019 ANNOTATIONS OF MULTIPLE DIGITAL TEXTS &#8211; Alexandra List<\/li>\n\n\n\n<li>Examining LLM Prompting Strategies for Automatic Evaluation of Learner-Created Computational Artifacts &#8211; Xiaoyi Tian, Amogh Mannekote, Carly E. Solomon, Yukyeong Song, Christine Fry Wise, Tom Mcklin, Joanne Barrett, Kristy Elizabeth Boyer and Maya Israel<\/li>\n\n\n\n<li>Navigating the Sky Together: Investigating Collaboration Dynamics through Annotation in an Immersive Learning Environment &#8211; Yiqiu Zhou, Philo Wang and Jina Kang<\/li>\n\n\n\n<li>Determining Perceived Text Complexity: An Evaluation of German Sentences Through Student Assessments &#8211; Boris Thome, Friederike Hertweck and Stefan Conrad<\/li>\n\n\n\n<li>Strategic Interface Design Can Improve Learning Efficiency in an Intelligent Tutoring System &#8211; Sutapa Dey Tithi, Behrooz Mostafavi, Arun Kumar Ramesh and Tiffany Barnes<\/li>\n\n\n\n<li>Relation of Linguistic Indicators to Civic Engagement in Special Education &#8211; Chak Li, Scott Crossley, Meghan Burke and Zach Rossetti<\/li>\n\n\n\n<li>Automated Assessment in Math Education: A Comparative Analysis of LLMs for Open-Ended Responses &#8211; Sami Baral, Eamon Worden, Wen-Chiang Lim, Zhuang Luo, Christopher Santorelli, Ashish Gurung and Neil Heffernan<\/li>\n\n\n\n<li>Social Network and Self-representation in Megathread:&nbsp; Group Formation in a Data Science Crowdsourcing Community &#8211; Shiyao Wei and Ran Bi<\/li>\n\n\n\n<li>Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students &#8211; Valdemar \u0160v\u00e1bensk\u00fd, M\u00e9lina Verger, Maria Mercedes T. Rodrigo, Clarence James G. Monterozo, Ryan S. Baker, Miguel Zenon Nicanor Lerias Saavedra, S\u00e9bastien Lall\u00e9 and Atsushi Shimada<\/li>\n\n\n\n<li>Prioritizing the Indicators of Effective Inclusive Education Assessment Framework using TOPSIS Analysis for children with Disabilities: A Case of Delhi. &#8211; Umesh Kumar and Haimanti Banerji<\/li>\n\n\n\n<li>Towards Modeling Learner Performance with Large Language Models &#8211; Seyed Parsa Neshaei, Richard Davis, Adam Hazimeh, Bojan Lazarevski, Pierre Dillenbourg and Tanja K\u00e4ser<\/li>\n\n\n\n<li>Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions? &#8211; Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steve Ritter and Andrew Lan<\/li>\n\n\n\n<li>Be back in 5 minutes: Exploring correlations between short breaks with student performance &#8211; Yu-Chia Kao and Anthony Botelho<\/li>\n\n\n\n<li>Predicting Cognitive Load Using Sensor Data in a Literacy Game &#8211; Minghao Cai and Carrie Demmans Epp<\/li>\n\n\n\n<li>The Cleaned Repository of Annotated Personally Identifiable Information &#8211; Langdon Holmes, Scott Crossley, Jiahe Wang and Weixuan Zhang<\/li>\n\n\n\n<li>Semantic Similarity of Teacher and Student Discourse Linked to Quality Ratings from Classroom Observations &#8211; Jessica Boyle and Scott Crossley<\/li>\n\n\n\n<li>How Hard can this Question be? An Exploratory Analysis of Features Assessing Question Difficulty using LLMs &#8211; Andreea Dutulescu, Stefan Ruseti, Mihai Dascalu and Danielle Mcnamara<\/li>\n\n\n\n<li>It&#8217;s All About the Prompt:&nbsp; Deductive Coding&#8217;s Role in AI vs. Human Performance &#8211; Jeanne McClure, Daria Smyslova, Amanda Hall and Shiyan Jiang<\/li>\n\n\n\n<li>The Early Bird Gets the Grade: Student Use of Class Time for Ed-Tech Practice Predicts Learning &#8211; Ashish Gurung, Jionghao Lin, Zhongtian Huang, Ryan S. Baker, Vincent Aleven and Kenneth Koedinger<\/li>\n\n\n\n<li>Same Learning Platform, Different Types of Research: A National-Level Analysis &#8211; Nidhi Nasiar, Ryan S. Baker, J. M. Alexandra Andres and Namrata Srivastava<\/li>\n\n\n\n<li>Cultural Diversity in Team Conversations: A Deep Dive into its Effects on Cohesion and Team Performance &#8211; Mohammad Amin Samadi and Nia Nixon<\/li>\n\n\n\n<li>An Exploratory Analysis of Students\u2019 Problem-Solving Strategies in the Water Cycle Game &#8211; Jing Zhang and Luc Paquette<\/li>\n\n\n\n<li>Prompting as Panacea? A Case Study of In-Context Learning Performance for Qualitative Coding of Classroom Dialog &#8211; Ananya Ganesh, Chelsea Chandler, Sidney D&#8217;Mello, Martha Palmer and Katharina Kann<\/li>\n\n\n\n<li>Identifying Off-Task Users in a Large-Scale, Game-Based Practice Assessment &#8211; Matthew Emery, David Laing, Philip Simmons, Jacob Seybert, Katrina Yu, Erica Snow and Jack Buckley<\/li>\n\n\n\n<li>EduQuest: Lecture Texts and Questions for Higher Education &#8211; Oliver Holl, Filipe Szolnoky Cunha, David Streuli and Timoth\u00e9 Laborie<\/li>\n\n\n\n<li>Easing the Prediction of Student Dropout for everyone by integrating AutoML and Explainable Artificial Intelligence &#8211; Pamela Bu\u00f1ay-Guis\u00f1an, Juan Alfonso Lara, Alberto Cano, Rebeca Cerezo and Crist\u00f3bal Romero<\/li>\n\n\n\n<li>LLM-generated Feedback in Real Classes and Beyond: Perspectives from Students and Instructors &#8211; Qinjin Jia, Jialin Cui, Haoze Du, Parvez Rashid, Ruijie Xi, Ruochi Li and Edward Gehringer<\/li>\n\n\n\n<li>Complex Conversations: LLMs vs. Knowledge Engineered Conversation-based Assessment &#8211; Carol Forsyth, Diego Zapata-Rivera, Edith Aurora Graf and Yang Jiang<\/li>\n\n\n\n<li>Enhancing the Accuracy of Predicting Students Grades in Open-Ended Questions through Adjustments to Attention Weights &#8211; Masaki Koike, Hirokazu Kohama, Tsubasa Hirakawa, Takayoshi Yamashita and Hironobu Fujiyoshi<\/li>\n\n\n\n<li>Predicting Response Time of Questions Using Linear Mixed-effects Model &#8211; Luyao Peng<\/li>\n\n\n\n<li>Tailored analysis of dropout in UBA distance postgraduate courses: first results &#8211; Antonio R. Anaya, Pablo M. G\u00f3mez and Ariel Lutenberg<\/li>\n\n\n\n<li>Explainability in Educational Data Mining and Learning Analytics: An Umbrella Review &#8211; Sachini Gunasekara and Mirka Saarela<\/li>\n\n\n\n<li>Comparing Clustering Methods in Group-level Test Collusion Detection &#8211; Luyao Peng<\/li>\n\n\n\n<li>Ethical Educational Data Processing Differences of Students with Special Needs in Post-Soviet Countries &#8211; Ayaz Karimov, Mirka Saarela and Tommi K\u00e4rkk\u00e4inen<\/li>\n\n\n\n<li>FlexEval: a customizable tool for chatbot performance evaluation and dialogue analysis &#8211; S. Thomas Christie, Baptiste Moreau-Pernet, Yu Tian and John Whitmer<\/li>\n\n\n\n<li>Uncertainty-preserving deep knowledge tracing with state-space models &#8211; Thomas Christie, Carson Cook and Anna Rafferty<\/li>\n\n\n\n<li>Comparative Analysis of Student Performance Predictions in Online Courses using Heterogeneous Knowledge Graphs &#8211; Thomas Trask, Michael Boyle, Ahmed Ali Abdo Abdullah Mubarak, David Joyner and Nick Lytle<\/li>\n\n\n\n<li>Investigating the Dynamic Change of Pre- and In-service Teachers&#8217; Experiences, Attitudes, and Perceptions through CS Autobiography Using Topic Modeling &#8211; Shan Zhang, Hai Li, Hongming Li, Anthony F. Botelho and Maya Israel<\/li>\n\n\n\n<li>Exploring Simultaneous Knowledge and Behavior Tracing &#8211; Siqian Zhao and Sherry Sahebi<\/li>\n\n\n\n<li>Interpreting Latent Student Knowledge Representations in Programming Assignments &#8211; Nigel Fernandez and Andrew Lan<\/li>\n\n\n\n<li>Math Multiple Choice Question Generation via Human-Large Language Model Collaboration &#8211; Jaewook Lee, Digory Smith, Simon Woodhead and Andrew Lan<\/li>\n\n\n\n<li>Generating Feedback-Ladders for Logical Errors in Programming using Large Language Models &#8211; Hasnain Heickal and Andrew Lan<\/li>\n\n\n\n<li>Auditing an Automatic Grading Model with Reinforcement Learning &#8211; Aubrey Condor and Zachary Pardos<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Long Papers Industry &amp; Short Papers Posters &amp; Demos<\/p>\n","protected":false},"author":23,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[],"class_list":["post-582","page","type-page","status-publish","hentry","category-program"],"acf":[],"_links":{"self":[{"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/pages\/582","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/users\/23"}],"replies":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/comments?post=582"}],"version-history":[{"count":10,"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/pages\/582\/revisions"}],"predecessor-version":[{"id":808,"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/pages\/582\/revisions\/808"}],"wp:attachment":[{"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/media?parent=582"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/categories?post=582"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2024\/wp-json\/wp\/v2\/tags?post=582"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}