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17th EDM 2024: Atlanta, GA, USA
- David A. Joyner, Benjamin Paaßen, Carrie Demmans Epp:
Proceedings of the 17th International Conference on Educational Data Mining, EDM 2024, Atlanta, Georgia, USA, July 14-17, 2024. International Educational Data Mining Society 2024 - Introduction to the Proceedings.
Full Papers
- Bilal Ghanem, Alona Fyshe:
DISTO: Textual Distractors for Multiple Choice Reading Comprehension Questions using Negative Sampling. - Denis Shchepakin, Sreecharan Sankaranarayanan, Dawn Zimmaro:
Parametric Constraints for Bayesian Knowledge Tracing from First Principles. - Yijun Zhao, Zhengxin Qi, Son Tung Do, John Grossi, Jee Hun Kang, Gary M. Weiss:
Predicting GRE Scores from Application Materials in Test-Optional Admissions. - Yunsung Kim, Jadon Geathers, Chris Piech:
Grading and Clustering Student Programs That Produce Probabilistic Output. - Mehmet Arif Demirtas, Max Fowler, Kathryn Cunningham:
Reexamining Learning Curve Analysis in Programming Education: The Value of Many Small Problems. - Joy He-Yueya, Noah D. Goodman, Emma Brunskill:
Evaluating and Optimizing Educational Content with Large Language Model Judgments. - Muhammad Fawad Akbar Khan, Max Ramsdell, Erik Falor, Hamid Karimi:
Assessing the Promise and Pitfalls of ChatGPT for Automated CS1-driven Code Generation. - Yiyao Li, Lu Wang, Jung-Jae Kim, Chor Seng Tan, Ye Luo:
On the Selection of Positive and Negative Samples for Contrastive Math Word Problem Neural Solver. - Fernando Martinez, Gary M. Weiss, Miguel Palma, Haoran Xue, Alexander Borelli, Yijun Zhao:
GPT vs. Llama2: Which Comes Closer to Human Writing? - Conrad Borchers, Kexin Yang, Jionghao Lin, Nikol Rummel, Kenneth R. Koedinger, Vincent Aleven:
Combining Dialog Acts and Skill Modeling: What Chat Interactions Enhance Learning Rates During AI-Supported Peer Tutoring? - Md Mirajul Islam, Xi Yang, John Wesley Hostetter, Adittya Soukarjya Saha, Min Chi:
A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies. - David Joyner, Zoey Anne Beda, Michael Cohen, Melanie Duffin, Amy Garcia Fernandez, Liz Hayes-Golding, Jonathan Hildreth, Alex Houk, Rebecca Johnson, Kayla Matchek, Ana Santos:
When Chatting Isn't Cheating: Mining and Evaluating Student Use of Chatbots and Other Resources During Open-Internet Exams. - Jiayi Zhang, Conrad Borchers, Vincent Aleven, Ryan S. Baker:
Using Large Language Models to Detect Self-Regulated Learning in Think-Aloud Protocols. - Videep Venkatesha, Abhijnan Nath, Ibrahim Khebour, Avyakta Chelle, Mariah Bradford, Jingxuan Tu, James Pustejovsky, Nathaniel Blanchard, Nikhil Krishnaswamy:
Propositional Extraction from Natural Speech in Small Group Collaborative Tasks. - Bahar Radmehr, Adish Singla, Tanja Käser:
Towards Generalizable Agents in Text-Based Educational Environments: A Study of Integrating RL with LLMs. - Benny G. Johnson, Jeffrey S. Dittel, Rachel Van Campenhout:
Investigating Student Ratings with Features of Automatically Generated Questions: A Large-Scale Analysis using Data from Natural Learning Contexts. - Napol Rachatasumrit, Paulo Carvalho, Kenneth R. Koedinger:
Beyond Accuracy: Embracing Meaningful Parameters in Educational Data Mining. - Andres Felipe Zambrano, Nidhi Nasiar, Jaclyn Ocumpaugh, Alex Goslen, Jiayi Zhang, Jonathan P. Rowe, Jordan Esiason, Jessica Vandenberg, Stephen Hutt:
Says Who? How different ground truth measures of emotion impact student affective modeling. - Halim Acosta, Seung Y. Lee, Bradford W. Mott, Haesol Bae, Krista D. Glazewski, Cindy E. Hmelo-Silver, James C. Lester:
Multimodal Learning Analytics for Predicting Student Collaboration Satisfaction in Collaborative Game-Based Learning. - Jionghao Lin, Eason Chen, Zifei FeiFei Han, Ashish Gurung, Danielle R. Thomas, Wei Tan, Ngoc Dang Nguyen, Kenneth R. Koedinger:
How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses. - Nazia Alam, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes:
How Much Training is Needed? Reducing Training Time using Deep Reinforcement Learning in an Intelligent Tutor.
Short Papers
- Chenguang Pan, Zhou Zhang:
Examining the Algorithmic Fairness in Predicting High School Dropouts. - Kaden Hart, Christopher M. Warren, Seth Poulsen, John Edwards:
Phone Use While Programming. - Ryan Shaun Baker, Stephen Hutt, Christopher A. Brooks, Namrata Srivastava, Caitlin Mills:
Open Science and Educational Data Mining: Which Practices Matter Most? - Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming. - Golnaz Arastoopour Irgens, Ibrahim Oluwajoba Adisa, Deepika Sistla, Tolulope Famaye, Cinamon Bailey, Atefeh Behboudi, Adenike Omolara Adefisayo:
Supporting Theory Building in Design-Based Research through Large Scale Data-Based Models. - Gyuhun Jung, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
More, May not the Better: Insights from Applying Deep Reinforcement Learning for Pedagogical Policy Induction. - Owen Henkel, Zachary Levonian, Chenglu Li, Millie-Ellen Postle:
Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference. - Aswani Yaramala, Soheila Farokhi, Hamid Karimi:
Navigating the Data-Rich Landscape of Online Learning: Insights and Predictions from ASSISTments. - Ying Zhang, Yan Zhang, Wei Xu, Zhifeng Wang, Jianwen Sun:
SingPAD: A Knowledge Tracing Dataset Based on Music Performance Assessment. - Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla:
Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming. - Or Goren, Liron Cohen, Amir Rubinstein:
Early Prediction of Student Dropout in Higher Education using Machine Learning Models. - Jiani Wang, Shiran Dudy, Xinlu He, Zhiyong Wang, Rosy Southwell, Jacob Whitehill:
Speaker Diarization in the Classroom: How Much Does Each Student Speak in Group Discussions? - Wenhao Wang, Etsuko Kumamoto, Chengjiu Yin:
A page jump recommendation model and result interpretation based on structured annotation methods. - Duy M. Pham, Kirk P. Vanacore, Adam C. Sales, Johann Gagnon-Bartsch:
LOOL: Towards Personalization with Flexible \& Robust Estimation of Heterogeneous Treatment Effects. - Adam C. Sales, Kirk P. Vanacore, Hyeon-Ah Kang, Tiffany A. Whittaker:
Problem-Solving Behavior and EdTech Effectiveness: A Model for Exploratory Causal Analysis. - Yiqiu Zhou, Luc Paquette:
Investigating Student Interest in a Minecraft Game-Based Learning Environment: A Changepoint Detection Analysis. - Bledar Fazlija:
Feeling the Difficulty of Mathematics. - Chengyuan Liu, Jialin Cui, Ruixuan Shang, Qinjin Jia, M. Parvez Rashid, Edward F. Gehringer:
Generative AI for Peer Assessment Helpfulness Evaluation. - Mary Ann Simpson, Kole A. Norberg, Stephen E. Fancsali:
Replicating an "Astonishing Regularity in Student Learning Rate". - Conrad Borchers, Yinuo Xu, Zachary A. Pardos:
Are You an Early Dropper or Late Shopper? Mining Enrollment Transaction Data to Study Procrastination in Higher Education. - Yuma Miyazaki, Valdemar Svábenský, Yuta Taniguchi, Fumiya Okubo, Tsubasa Minematsu, Atsushi Shimada:
E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems. - Jade Maï Cock, Hugues Saltini, Haoyu Sheng, Riya Ranjan, Richard Davis, Tanja Käser:
Investigation of behavioral Differences: Uncovering Behavioral Sources of Demographic Bias in Educational Algorithms. - Ayaz Karimov, Mirka Saarela, Tommi Kärkkäinen, Sabina Aghayeva:
Principals' use of data analytics in Finnish schools. - Sören Rüttgers, Ulrike Kuhl, Benjamin Paaßen:
Automatic Matchmaking in Two-Versus-Two Sports. - Jaylin Lowe, Charlotte Z. Mann, Jiaying Wang, Adam Sales, Johann A. Gagnon-Bartsch:
Power Calculations for Randomized Controlled Trials with Auxiliary Observational Data. - Scott A. Crossley, Yu Tian, Joon Suh Choi, Langdon Holmes, Wesley Morris:
Plagiarism Detection Using Keystroke Logs. - Zhikai Gao, Gabriel Silva de Oliveira, Damilola Babalola, Collin F. Lynch, Sarah Heckman:
Who Should I Help Next? Simulation of Office Hours Queue Scheduling Strategy in a CS2 Course. - Qinjin Jia, Jialin Cui, Ruijie Xi, Chengyuan Liu, M. Parvez Rashid, Ruochi Li, Edward F. Gehringer:
On Assessing the Faithfulness of LLM-generated Feedback on Student Assignments. - Nhat Tran, Benjamin Pierce, Diane J. Litman, Richard Correnti, Lindsay Clare Matsumura:
Analyzing Large Language Models for Classroom Discussion Assessment. - Celestine E. Akpanoko, Ashwin T. S., Grayson Cordell, Gautam Biswas:
Investigating the Relations between Students' Affective States and the Coherence in their Activities in Open-Ended Learning Environments. - Charlotte Z. Mann, Jiaying Wang, Adam Sales, Johann A. Gagnon-Bartsch:
Using Publicly Available Auxiliary Data to Improve Precision of Treatment Effect Estimation in a Randomized Efficacy Trial. - Meng Cao, Philip I. Pavlik Jr., Wei Chu, Liang Zhang:
Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Train-ing Sequences on Category Learning. - Hongming Li, Shan Zhang, Seiyon Lee, Ji-Eun Lee, Zirui Zhong, Erik Weitnauer, Anthony F. Botelho:
Math in Motion: Analyzing Real-Time Student Collaboration in Computer-Supported Learning Environments. - Hongming Li, Seiyon Lee, Anthony F. Botelho:
This Paper Was Written with the Help of ChatGPT: Exploring the Consequences of AI-Driven Academic Writing on Scholarly Practices. - Robin Jephthah Rajarathinam, Christian Palaguachi, Jina Kang:
Enhancing Multimodal Learning Analytics: A Comparative Study of Facial Features Captured Using Traditional vs 360-Degree Cameras in Collaborative Learning. - Shreya Singhal, Andres Felipe Zambrano, Maciej Pankiewicz, Xiner Liu, Chelsea Porter, Ryan S. Baker:
De-Identifying Student Personally Identifying Information with GPT-4. - Andres Felipe Zambrano, Ryan S. Baker, Sami Baral, Neil T. Heffernan, Andrew S. Lan:
From Reaction to Anticipation: Predicting Future Affect. - Yuya Asano, Diane J. Litman, Quentin King-Shepard, Tristan Maidment, Tyree Langley, Teresa Davison:
What metrics of participation balance predict outcomes of collaborative learning with a robot? - Paras Sharma, Angela E. B. Stewart, Qichang Li, Krit Ravichander, Erin Walker:
Building Learner Activity Models From Log Data Using Sequence Mapping and Hidden Markov Models.
Posters
- Rwitajit Majumdar, Prajish Prasad, Aamod Sane:
Mining Epistemic Actions of Programming Problem Solving with Chat-GPT. - Elena Grazia Gado, Tommaso Martorella, Luca Zunino, Paola Mejia-Domenzain, Vinitra Swamy, Jibril Frej, Tanja Käser:
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning. - Hyun Jeong, Gary M. Weiss, Audrey Leung, Daniel D. Leeds:
The Construction and Analysis of Course Grades Across Public Universities. - Blake Castleman, Mehmet Kerem Türkcan:
Examining the Influence of Varied Levels of Domain Knowledge Base Inclusion in GPT-based Intelligent Tutors. - Tianyuan Yang, Baofeng Ren, Boxuan Ma, Md. Akib Zabed Khan, Tianjia He, Shin'ichi Konomi:
Making Course Recommendation Explainable: A Knowledge Entity-Aware Model using Deep Learning. - Subhankar Maity, Aniket Deroy, Sudeshna Sarkar:
How Ready Are Generative Pre-trained Large Language Models for Explaining Bengali Grammatical Errors? - Shiyao Wei, Ran Bi:
Uncovering the Evolution of Topics about AI Painting: Dynamic Topic Modeling of 180k Discourse Data in an Online Community. - Xinlu He, Jiani Wang, Viet Anh Trinh, Andrew A. McReynolds, Jacob Whitehill:
Tracking Classroom Movement Patterns with Person Re-ID. - Zifeng Liu, Xinyue Jiao, Chenglu Li, Wanli Xing:
Fair Prediction of Students' Summative Performance Changes Using Online Learning Behavior Data. - Alexandra List:
Automated Scoring of Students' Annotations When Learning from Multiple Texts. - Xiaoyi Tian, Amogh Mannekote, Carly E. Solomon, Yukyeong Song, Christine Fry Wise, Tom McKlin, Joanne Barrett, Kristy Elizabeth Boyer, Maya Israel:
Examining LLM Prompting Strategies for Automatic Evaluation of Learner-Created Computational Artifacts. - Yiqiu Zhou, Philo Wang, Jina Kang:
Navigating the Sky Together: Investigating Collaboration Dynamics through Annotation in an Immersive Learning Environment. - Boris Thome, Friederike Hertweck, Stefan Conrad:
Determining Perceived Text Complexity: An Evaluation of German Sentences Through Student Assessments. - Sutapa Dey Tithi, Behrooz Mostafavi, Arun Kumar Ramesh, Tiffany Barnes:
Strategic Interface Design Can Improve Learning Efficiency in an Intelligent Tutoring System. - Chak Li, Scott Crossley, Meghan Burke, Zach Rossetti:
Relation of Linguistic Indicators to Civic Engagement in Special Education. - Sami Baral, Eamon Worden, Wen-Chiang Lim, Zhuang Luo, Christopher Santorelli, Ashish Gurung:
Automated Assessment in Math Education: A Comparative Analysis of LLMs for Open-Ended Responses. - Shiyao Wei, Ran Bi:
Social Network and Self-representation in Megathread: Group Formation in a Data Science Crowdsourcing Community. - Valdemar Svábenský, Mélina Verger, Maria Mercedes T. Rodrigo, Clarence James G. Monterozo, Ryan S. Baker, Miguel Zenon Nicanor Lerias Saavedra, Sébastien Lallé, Atsushi Shimada:
Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students. - Umesh Kumar, Haimanti Banerji:
Prioritizing the Indicators of Effective Inclusive Education Assessment Framework using TOPSIS Analysis for children with Disabilities: A Case of Delhi. - Seyed Parsa Neshaei, Richard Lee Davis, Adam Hazimeh, Bojan Lazarevski, Pierre Dillenbourg, Tanja Käser:
Towards Modeling Learner Performance with Large Language Models. - Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steve Ritter, Andrew S. Lan:
Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions? - Yu-Chia Kao, Anthony Botelho:
Be back in 5 minutes: Exploring correlations between short breaks with student performance. - Minghao Cai, Carrie Demmans Epp:
Predicting Cognitive Load Using Sensor Data in a Literacy Game. - Langdon Holmes, Scott A. Crossley, Jiahe Wang, Weixuan Zhang:
The Cleaned Repository of Annotated Personally Identifiable Information. - Jessica Boyle, Scott A. Crossley:
Semantic Similarity of Teacher and Student Discourse Linked to Quality Ratings from Classroom Observations. - Andreea-Nicoleta Dutulescu, Stefan Ruseti, Mihai Dascalu, Danielle McNamara:
How Hard can this Question be? An Exploratory Analysis of Features Assessing Question Difficulty using LLMs. - Jeanne McClure, Daria Smyslova, Amanda Hall, Shiyan Jiang:
Deductive Coding's Role in AI vs. Human Performance. - Nidhi Nasiar, Ryan S. Baker, Juliana. Ma. Alexandra L. Andres, Namrata Srivastava:
Same Learning Platform, Different Types of Research: A National-Level Analysis. - Mohammad Amin Samadi, Nia Nixon:
Cultural Diversity in Team Conversations: A Deep Dive into its Effects on Cohesion and Team Performance. - Jing Zhang, Luc Paquette:
An Exploratory Analysis of Students' Problem-Solving Strategies in the Water Cycle Game. - Ananya Ganesh, Chelsea Chandler, Sidney D'Mello, Martha Palmer, Katharina Kann:
Prompting as Panacea? A Case Study of In-Context Learning Performance for Qualitative Coding of Classroom Dialog. - Matthew A. Emery, David Laing, Philip Simmons, Jacob Seybert, Katrina Yu, Erica L. Snow, Jack Buckley:
Identifying Off-Task Users in a Large-Scale, Game-Based Practice Assessment. - Oliver Holl, Filipe Szolnoky Cunha, David Streuli, Timothé Laborie:
EduQuest: Lecture Texts and Questions for Higher Education. - Pamela Buñay-Guisñan, Juan Alfonso Lara, Alberto Cano, Rebeca Cerezo, Cristóbal Romero:
Easing the Prediction of Student Dropout for everyone integration AutoML and Explainable Artificial Intelligence. - Qinjin Jia, Jialin Cui, Haoze Du, M. Parvez Rashid, Ruijie Xi, Ruochi Li, Edward F. Gehringer:
LLM-generated Feedback in Real Classes and Beyond: Perspectives from Students and Instructors. - Carol M. Forsyth, Diego Zapata-Rivera, Edith Aurora Graf, Yang Jiang:
Complex Conversations: LLM vs. Knowledge Engineering Conversation-based Assessment. - Masaki Koike, Hirokazu Kohama, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi:
Enhancing the Accuracy of Predicting Students Grades in Open-Ended Questions through Adjustments to Attention Weights. - Luyao Peng:
Predicting Response Time of Questions Using Linear Mixed-effects Model. - Antonio R. Anaya, Pablo M. Gómez, Ariel Lutenberg:
Tailored analysis of dropout in UBA distance postgraduate courses: first results. - Sachini Gunasekara, Mirka Saarela:
Explainability in Educational Data Mining and Learning Analytics: An Umbrella Review. - Luyao Peng:
Comparing Clustering Methods in Group-level Test Collusion Detection. - Ayaz Karimov, Mirka Saarela, Tommi Kärkkäinen:
Ethical Educational Data Processing Differences of Students with Special Needs in Post-Soviet Countries. - S. Thomas Christie, Baptiste Moreau-Pernet, Yu Tian, John Whitmer:
FlexEval: a customizable tool for chatbot performance evaluation and dialogue analysis. - S. Thomas Christie, Carson Cook, Anna N. Rafferty:
Uncertainty-preserving deep knowledge tracing with state-space models. - Thomas Trask, Nick Lytle, Michael Boyle, David Joyner, Ahmed Mubarak:
A Comparative Analysis of Student Performance Predictions in Online Courses using Heterogeneous Knowledge Graphs. - Shan Zhang, Hai Li, Hongming Li, Anthony F. Botelho, Maya Israel:
Investigating the Dynamic Change of Pre- and In-service Teachers' Experiences, Attitudes, and Perceptions through CS Autobiography Using Topic Modeling. - Siqian Zhao, Sherry Sahebi:
Exploring Simultaneous Knowledge and Behavior Tracing. - Nigel Fernandez, Andrew S. Lan:
Interpreting Latent Student Knowledge Representations in Programming Assignments. - Jaewook Lee, Digory Smith, Simon Woodhead, Andrew S. Lan:
Math Multiple Choice Question Generation via Human-Large Language Model Collaboration. - Hasnain Heickal, Andrew Lan:
Generating Feedback-Ladders for Logical Errors in Programming using Large Language Models. - Aubrey Condor, Zachary A. Pardos:
Auditing an Automatic Grading Model with deep Reinforcement Learning.
Doctoral Consortium
- Subhankar Maity, Aniket Deroy, Sudeshna Sarkar:
Exploring the Capabilities of Prompted Large Language Models in Educational and Assessment Applications. - Mehmet Arif Demirtas:
Identifying and Evaluating Novel Knowledge Component Models for Programming Skills. - Samuel Girard, Jill-Jênn Vie, Françoise Tort, Amel Bouzeghoub:
Optimizing Human Learning using Reinforcement Learning. - Nidia Guadalupe López Flores, Víctor Uc-Cetina, Anna Sigridur Islind, María Óskarsdóttir:
Threads of Complexity: Lessons learnt from Predicting Student Failure through Discussion Forums' Social-Temporal Dynamics. - Juan D. Pinto, Luc Paquette, Nigel Bosch:
Intrinsically Interpretable Artificial Neural Networks for Learner Modeling. - Paras Sharma, Qichang Li:
Designing Simulated Students to Emulate Learner Activity Data in an Open-Ended Learning Environment. - Yanping Pei, Adam Sales, Johann Gagnon-Bartsch:
Boosting Precision in Educational A/B Tests Using Auxiliary Information and Design-Based Estimators. - Seiyon M. Lee, Anthony F. Botelho:
The Challenge of Challenges: Examining the Impact of Difficulty Dynamics on Mastery Learning in Math. - Hongming Li, Anthony F. Botelho:
Developing Explainable AI Systems to Support Feedback for Students. - Zhikai Gao, Collin Lynch:
Building Predictive Models for CS Students Help-Seeking Behaviors with Coding Log Data.
Tutorials
- Philip I. Pavlik Jr., Luke G. Eglington, Meng Cao, Wei Chu:
Logistic Knowledge Tracing Tutorial: Practical Educational Applications. - Yang Shi, Peter Brusilovsky, Bita Akram, Thomas W. Price, Juho Leinonen, Kenneth R. Koedinger, Andrew S. Lan:
8th Educational Data Mining in Computer Science Education (CSEDM) Workshop. - Aaron Haim, Stephen Hutt, Stacy T. Shaw, Neil T. Heffernan:
Promoting Open Science in Educational Data Mining: An Interactive Tutorial on Licensing, Data, and Containers. - Lea Cohausz:
Thinking Causally in EDM: A Hands-On Tutorial for Causal Modeling Using DAGs. - David G. Cooper:
Beyond Tutor Logs: Utilizing sensor data for measuring student behavior. - Adam C. Sales, Johann A. Gagnon-Bartsch, Duy M. Pham:
Tools for Planning and Analyzing Randomized Controlled Trials and A/B Tests. - Juan Pinto, Luc Paquette, Vinitra Swamy, Tanja Käser, Qianhui Liu, Lea Cohausz:
Human-Centric eXplainable AI in Education (HEXED) Workshop. - Anthony F. Botelho, Avery Harrison Closser, Adam C. Sales, Neil T. Heffernan, Kirk P. Vanacore:
Causal Inference in Educational Data Mining. - Neil T. Heffernan, Rose E. Wang, Christopher MacLellan, Arto Hellas, Chenglu Li, Candace Walkington, Joshua Littenberg-Tobias, David Joyner, Steven Moore, Adish Singla, Zach A. Pardos, Maciej Pankiewicz, Juho Kim, Shashank Sonkar, Clayton Cohn, Anthony Botelho, Andrew Lan, Lan Jiang, Mingyu Feng, Tanja Käser, Eamon Worden:
Leveraging Large Language Models for Next-Generation Educational Technologies. - Collin Lynch, Paul Deane, Piotr Mitros, Zhikai Gao, Damilola Babalola:
Educational Data Mining in Writing and Literacy Instruction.
Industry Track
- Jeffrey Matayoshi, Eric Cosyn, Christopher Lechuga, Hasan Uzun:
An Evaluation of a Placement Assessment for an Adaptive Learning System. - Lief Esbenshade, Jonathan Vitale, Ryan S. Baker:
Non-Overlapping Leave Future Out Validation (NOLFO): Implications for Graduation Prediction. - Andrew Emerson, Arti Ramesh, Patrick Houghton, Vinay Basheerabad, Navaneeth Jawahar, Chee Wee Leong:
Multimodal, Multi-Class Bias Mitigation for Predicting Speaker Confidence. - Mohammad Arif Ul Alam, Madhavi Pagare, Susan Davis, Geeta Verma, Ashis Kumer Biswas, Justin Barbern:
Empowering Predictions of the Social Determinants of Mental Health through Large Language Model Augmentation in Students' Lived Experiential Essays.
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