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12th EDM 2019: Montréal, Canada
- Michel C. Desmarais, Collin F. Lynch, Agathe Merceron, Roger Nkambou:
Proceedings of the 12th International Conference on Educational Data Mining, EDM 2019, Montréal, Canada, July 2-5, 2019. International Educational Data Mining Society (IEDMS) 2019
Full Papers
- Tanya Nazaretsky, Sara Hershkovitz, Giora Alexandron:
Kappa Learning: A New Item-Similarity Method for Clustering Educational Items from Response Data. - Tsung-Yen Yang, Ryan S. Baker, Christoph Studer, Neil T. Heffernan, Andrew S. Lan:
Active Learning for Student Affect Detection. - Rafael Wampfler, Severin Klingler, Barbara Solenthaler, Victor R. Schinazi, Markus Gross:
Affective State Prediction in a Mobile Setting using Wearable Biometric Sensors and Stylus. - Shamya Karumbaiah, Jaclyn Ocumpaugh, Ryan S. Baker:
The Influence of School Demographics on the Relationship Between Students' Help-Seeking Behavior and Performance and Motivational Measures. - Niki Gitinabard, Tiffany Barnes, Sarah Heckman, Collin F. Lynch:
What will you do next? A sequence analysis on the student transitions between online platforms in blended courses. - Han Jiang, Matthew Iandoli, Steven Van Dessel, Shichao Liu, Jacob Whitehill:
Measuring students' thermal comfort and its impact on learning. - Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala:
Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. - Atsushi Shimada, Kousuke Mouri, Yuta Taniguchi, Hiroaki Ogata, Rin-Ichiro Taniguchi, Shin'ichi Konomi:
Optimizing Assignment of Students to Courses based on Learning Activity Analytics. - Ye Mao, Rui Zhi, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi:
One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks. - Josh Gardner, Yuming Yang, Ryan S. Baker, Christopher Brooks:
Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective. - Stephen Hutt, Margo Gardner, Angela Lee Duckworth, Sidney K. D'Mello:
Evaluating Fairness and Generalizability in Models Predicting On-Time Graduation from College Applications. - Joseph M. Reilly, Bertrand Schneider:
Predicting the Quality of Collaborative Problem Solving Through Linguistic Analysis of Discourse. - Benoît Choffin, Fabrice Popineau, Yolaine Bourda, Jill-Jênn Vie:
DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills. - Andrew Emerson, Andy Smith, Cody Smith, Fernando J. Rodríguez, Wookhee Min, Eric N. Wiebe, Bradford W. Mott, Kristy Elizabeth Boyer, James C. Lester:
Predicting Early and Often: Predictive Student Modeling for Block-Based Programming Environments. - Markel Sanz Ausin, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System. - Lovenoor S. Aulck, Dev Nambi, Nishant Velagapudi, Joshua Blumenstock, Jevin West:
Mining University Registrar Records to Predict First-Year Undergraduate Attrition. - Rémi Venant, Mathieu d'Aquin:
Towards the Prediction of Semantic Complexity Based on Concept Graphs. - Guanliang Chen, David Lang, Rafael Ferreira, Dragan Gasevic:
Predictors of Student Satisfaction: A Large-scale Study of Human-Human Online Tutorial Dialogues. - Rui Zhi, Samiha Marwan, Yihuan Dong, Nicholas Lytle, Thomas W. Price, Tiffany Barnes:
Toward Data-Driven Example Feedback for Novice Programming. - Qian Hu, Huzefa Rangwala:
Academic Performance Estimation with Attention-based Graph Convolutional Networks. - Huy Anh Nguyen, Yeyu Wang, John C. Stamper, Bruce M. McLaren:
Using Knowledge Component Modeling to Increase Domain Understanding in a Digital Learning Game. - Tanja Käser, Daniel L. Schwartz:
Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments.
Short Papers
- Antoine Pigeau, Olivier Aubert, Yannick Prié:
Success prediction in MOOCs: A case study. - Jacob Whitehill, Cecilia Aguerrebere, Benjamin Hylak:
Do Learners Know What's Good for Them? Crowdsourcing Subjective Ratings of OERs to Predict Learning Gains. - Fangzhe Ai, Yishuai Chen, Yuchun Guo, Yongxiang Zhao, Zhenzhu Wang, Guowei Fu, Guangyan Wang:
Concept-Aware Deep Knowledge Tracing and Exercise Recommendation in an Online Learning System. - Daniel Weitekamp III, Erik Harpstead, Christopher J. MacLellan, Napol Rachatasumrit, Kenneth R. Koedinger:
Toward Near Zero-Parameter Prediction Using a Computational Model of Student Learning. - John Kolb, Scott Farrar, Zachary A. Pardos:
Generalizing Expert Misconception Diagnoses Through Common Wrong Answer Embedding. - Roi Shillo, Nicholas Hoernle, Kobi Gal:
Detecting Creativity in an Open Ended Geometry Environment. - Christian Hansen, Casper Hansen, Stephen Alstrup, Christina Lioma:
Modelling End-of-Session Actions in Educational Systems. - Xinyi Ding, Eric C. Larson:
Why Deep Knowledge Tracing has less Depth than Anticipated. - Cecilia Aguerrebere, Monica Bulger, Cristóbal Cobo, Sofía García, Gabriela Kaplan, Jacob Whitehill:
How Should Online Teachers of English as a Foreign Language (EFL) Write Feedback to Students? - Yong Han, Wenjun Wu, Suozhao Ji, Lijun Zhang, Hui Zhang:
A Human-Machine Hybrid Peer Grading Framework for SPOCs. - Emily Jensen, Stephen Hutt, Sidney K. D'Mello:
Generalizability of Sensor-Free Affect Detection Models in a Longitudinal Dataset of Tens of Thousands of Students. - Cathlyn Stone, Patrick J. Donnelly, Meghan Dale, Sarah Capello, Sean Kelly, Amanda Godley, Sidney K. D'Mello:
Utterance-level Modeling of Indicators of Engaging Classroom Discourse. - Takeru Sunahase, Yukino Baba, Hisashi Kashima:
Probabilistic Modeling of Peer Correction and Peer Assessment. - Abhishek Unnam, Rohit Takhar, Varun Aggarwal:
Grading emails and generating feedback. - Shalini Pandey, George Karypis:
A Self Attentive model for Knowledge Tracing. - Tianqi Wang, Qi Li, Jing Gao, Xia Jing, Jie Tang:
Improving Peer Assessment Accuracy by Incorporating Relative Peer Grades. - Arabella Sinclair, Kate McCurdy, Christopher G. Lucas, Adam Lopez, Dragan Gasevic:
Tutorbot Corpus: Evidence of Human-Agent Verbal Alignment in Second Language Learner Dialogues. - Julien Broisin, Clément Hérouard:
Design and evaluation of a semantic indicator for automatically supporting programming learning. - Thanh-Nam Doan, Shaghayegh Sahebi:
Rank-Based Tensor Factorization for Student Performance Prediction. - Russell Moore, Andrew Caines, Mark Elliott, Ahmed H. Zaidi, Andrew Rice, Paula Buttery:
Skills Embeddings: A Neural Approach to Multicomponent Representations of Students and Tasks. - Gabriel Zingle, Balaji Radhakrishnan, Yunkai Xiao, Edward F. Gehringer, Zhongcan Xiao, Ferry Pramudianto, Gauraang Khurana, Ayush Arnav:
Detecting Suggestions in Peer Assessments. - Fatima Harrak, François Bouchet, Vanda Luengo:
Categorizing students' questions using an ensemble hybrid approach. - Karina Huang, Tonya Bryant, Bertrand Schneider:
Identifying Collaborative Learning States Using Unsupervised Machine Learning on Eye-Tracking, Physiological and Motion Sensor Data. - Noah Arthurs, Ben Stenhaug, Sergey Karayev, Chris Piech:
Grades are not Normal: Improving Exam Score Models Using the Logit-Normal Distribution. - Lu Ou, Abe D. Hofman, Vanessa R. Simmering, Timo Bechger, Gunter K. J. Maris, Han L. J. van der Maas:
Modeling person-specific development of math skills in continuous time: New evidence for mutualism. - Solmaz Abdi, Hassan Khosravi, Shazia W. Sadiq, Dragan Gasevic:
A Multivariate ELO-based Learner Model for Adaptive Educational Systems. - Jina Kang, Dongwook An, Lili Yan, Min Liu:
Collaborative Problem-Solving Process in A Science Serious Game: Exploring Group Action Similarity Trajectory. - Nisrine Ait Khayi, Vasile Rus:
Clustering Students Based on Their Prior Knowledge. - V. Elizabeth Owen, Marie-Helene Roy, K. P. Thai, Vesper Burnett, Daniel Jacobs, Eric Keylor, Ryan S. Baker:
Detecting Wheel Spinning and Productive Persistence in Educational Games. - Shahab Boumi, Adan Vela:
Application of Hidden Markov Models to quantify the impact of enrollment patterns on student performance. - Chuankai Zhang, Yanzun Huang, Jingyu Wang, Dongyang Lu, Weiqi Fang, John C. Stamper, Stephen Fancsali, Kenneth Holstein, Vincent Aleven:
Early Detection of Wheel Spinning: Comparison across Tutors, Models, Features, and Operationalizations. - Munira Syed, Malolan Chetlur, Shazia Afzal, G. Alex Ambrose, Nitesh V. Chawla:
Implicit and Explicit Emotions in MOOCs. - Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke:
Using Latent Variable Models to Observe Academic Pathways. - Byungsoo Jeon, Eyal Shafran, Luke Breitfeller, Jason Levin, Carolyn P. Rosé:
Time-series Insights into the Process of Passing or Failing Online University Courses using Neural-Induced Interpretable Student States. - Agoritsa Polyzou, Athanasios N. Nikolakopoulos, George Karypis:
Scholars Walk: A Markov Chain Framework for Course Recommendation. - Armando Maciel Toda, Wilk Oliveira, Lei Shi, Ig Ibert Bittencourt, Seiji Isotani, Alexandra I. Cristea
:
Planning Gamification Strategies based on User Characteristics and DM: A Gender-based Case Study. - Steven Dang, Ken Koedinger:
Exploring the Link Between Motivations and Gaming. - Sara Morsy, George Karypis:
Neural Attentive Knowledge-based Model for Grade Prediction. - Rajendra Banjade, Vasile Rus:
Assessing Student Response in Tutorial Dialogue Context using Probabilistic Soft Logic. - Anthony W. Raborn, Walter L. Leite, Katerina M. Marcoulides:
A Comparison of Automated Scale Short Form Selection Strategies. - Donia Malekian, James Bailey, Gregor E. Kennedy, Paula G. de Barba, Sadia Nawaz:
Characterising Students' Writing Processes Using Temporal Keystroke Analysis. - Chen Liang, Jianbo Ye, Han Zhao, Bart Pursel, C. Lee Giles
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations.
Poster Papers
- Sanaz Bahargam, Theodoros Lappas, Evimaria Terzi:
The Guided Team-Partitioning Problem: Definition, Complexity, and Algorithm. - Chun-Kit Yeung:
Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory. - Christopher Krauss, Agathe Merceron, Stefan Arbanowski:
Smart Learning Object Recommendations based on Time-Dependent Learning Need Models. - Ange Adrienne Nyamen Tato, Roger Nkambou, Aude Dufresne:
Hybrid Deep Neural Networks to Predict Socio-Moral Reasoning Skills. - Anwar Ali Yahya, Fekri Abdulwadod Mohammed, Addin Osman:
A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs. - Gaurav Nanda, Kerrie Anna Douglas:
Machine Learning Based Decision Support System for Categorizing MOOC Discussion Forum Posts. - Yiqiao Xu, Niki Gitinabard, Collin F. Lynch, Tiffany Barnes:
What You Say is Relevant to How You Make Friends: Measuring the Effect of Content on Social Connection. - Oded Vainas, Yossi Ben David, Ran Gilad-Bachrach, Meitar Ronen, Ori Bar-Ilan, Roi Shillo, Galit Lukin, Daniel Sitton:
Staying in the Zone: Sequencing Content in Classrooms Based on the Zone of Proximal Development. - Anthony F. Botelho, Ryan S. Baker, Neil T. Heffernan:
Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Student Behavior and Affect. - Henry Anderson, Afshan Boodhwani, Ryan S. Baker:
Assessing the Fairness of Graduation Predictions. - Korah J. Wiley, Allison Bradford, Zachary A. Pardos, Marcia C. Linn:
Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction. - Anik Jacobsen, Gerasimos Spanakis:
It's a Match! Reciprocal Recommender System for Graduating Students and Jobs. - Yanjun Pu, Wenjun Wu, Tianrui Jiang:
ATC Framework: A fully Automatic Cognitive Tracing Model for Student and Educational Contents. - Tianqi Wang, Fenglong Ma, Jing Gao:
Deep Hierarchical Knowledge Tracing. - Juanita Hicks, Ruhan Circi, Mengyi (Elaine) Li:
Students' Use of Support Functions in DBAs: Analysis of NAEP Grade 8 Mathematics Process Data. - Stephan Lorenzen, Niklas Hjuler, Stephen Alstrup:
Investigating Writing Style Development in High School. - Song Ju, Guojing Zhou, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Identifying Critical Pedagogical Decisions through Adversarial Deep Reinforcement Learning. - Shivangi Chopra, Abeer Khan, Melicaalsadat Mirsafian, Lukasz Golab:
Gender Differences in Work-Integrated Learning Assessments. - Mariana S. Oliveira, Carlos E. Mello:
Identifying bias and underlying knowledge structures in Brazilian National Exam of Students Performance. - Rachel Dickler, Haiying Li, Janice D. Gobert:
A Data-Driven Approach for Automated Assessment of Scientific Explanations in Science Inquiry. - Joseph M. Reilly, Chris Dede:
Exploring Stealth Assessment via Deep Learning in an Open-Ended Virtual Environment. - Fatima Harrak, François Bouchet, Vanda Luengo, Rémi Bachelet:
Automatic identification of questions in MOOC forums and association with self-regulated learning. - Lucia Ramirez, William Yao, Edwin Chng, Iulian Radu, Bertrand Schneider:
Toward Instrumenting Makerspaces: Using Motion Sensors to Capture Students' Affective States in Open-Ended Learning Environments. - Bruno Emond, Julio J. Valdés:
Visualizing Learning Performance Data and Model Predictions as Objects in a 3D Space. - Tyler Angert, Bertrand Schneider:
Augmenting Transcripts with Natural Language Processing and Multimodal Data. - Lujie Chen, Eva Gjekmarkaj, Artur Dubrawski:
Parent as a Companion for Solving Challenging Math Problems: Insights from Multi-modal Observational Data. - Varun Mandalapu, Jiaqi Gong:
Studying Factors Influencing the Prediction of Student STEM and Non-STEM Career Choice. - Meng Cao, Philip I. Pavlik Jr., Gavin M. Bidelman:
Incorporating Prior Practice Difficulty into Performance Factor Analysis to Model Mandarin Tone Learning. - David Boulanger, Vivekanandan Kumar:
Shedding Light on the Automated Essay Scoring Process. - Yupei Zhang, Huan Dai, Yue Yun, Xuequn Shang:
Student Knowledge Diagnosis on Response Data via the Model of Sparse Factor Learning. - Matthew Dong, Run Yu, Zachary A. Pardos:
Design and Deployment of a Better University Course Search: Inferring Latent Keywords from Enrollments. - Matthew W. Guthrie, Zhongzhou Chen:
Adding duration-based quality labels to learning events for improved description of students' online learning behavior. - Zichao Wang, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk:
A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading. - Ashvini Varatharaj, Anthony F. Botelho, Xiwen Lu, Neil T. Heffernan:
Hao Fa Yin: Developing Automated Audio Assessment Tools for a Chinese Language Course. - Yuta Taniguchi, Atsushi Shimada, Shin'ichi Konomi:
Investigating Error Resolution Processes in C Programming Exercise Courses. - Glenn M. Davis, Cindy Wang, Christina Yuan:
N-gram Graphs for Topic Extraction in Educational Forums. - Praseeda, Srinath Srinivasa, Prasad Ram:
Validating the Myth of Average through Evidences. - Rory Flemming, Emmanuel Schmück, Dominic Mussack, Pedro Cardoso-Leite, Paul Schrater:
A generalizable performance evaluation model of driving games via risk-weighted trajectories. - Mizuho Ikeda:
Learning Feature Analysis for Quality Improvement of Web-Based Teaching Materials Using Mouse Cursor Tracking. - Ahmed H. Zaidi, Andrew Caines, Christopher Davis, Russell Moore, Paula Buttery, Andrew Rice:
Accurate Modelling of Language Learning Tasks and Students Using Representations of Grammatical Proficiency. - J. D. Jayaraman, Sue Gerber, Julian Garcia:
Supporting Minority Student Success by using Machine Learning to Identify At-Risk Students. - Boniface Mbouzao, Michel C. Desmarais, Ian Shrier:
A Methodology for Student Video Interaction Patterns Analysis and Classification. - Dominic Mussack, Rory Flemming, Paul Schrater, Pedro Cardoso-Leite:
Towards discovering problem similarity through deep learning: combining problem features and user behavior. - Alexander Askinadze, Stefan Conrad:
Predicting Student Dropout in Higher Education Based on Previous Exam Results. - Andréa K. Davis, Yun Jin Rho, Daniel Furr:
Individual Differences in Student Learning Aid Usage. - Ben Levy, Arnon Hershkovitz, Odelia Tzayada, Orit Ezra, Avi Segal, Kobi Gal, Anat Cohen, Michal Tabach:
Teacher vs. Algorithm: Double-blind experiment of content sequencing in mathematics. - Jaechoon Jo, YeongWook Yang, Gyeongmin Kim, Heuiseok Lim:
A Comparative Analysis of Emotional Words for Learning Effectiveness in Online Education. - Varshita Sher, Marek Hatala, Dragan Gasevic:
Investigating effects of considering mobile and desktop learning data on predictive power of learning management system (LMS) features on student success. - Hammad Shaikh, Arghavan Modiri, Joseph Jay Williams, Anna N. Rafferty:
Balancing Student Success and Inferring Personalized Effects in Dynamic Experiments. - Daniel Furr:
Visualization and clustering of learner pathways in an interactive online learning environment. - Giora Alexandron, José A. Ruipérez-Valiente, David E. Pritchard:
Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses. - Vincent Gagnon, Audrey Labrie, Sameer Bhatnagar, Michel C. Desmarais:
Filtering non-relevant short answers in peer learning applications. - Juan Miguel L. Andres-Bray, Jaclyn L. Ocumpaugh, Ryan S. Baker:
Hello? Who is posting, who is answering, and who is succeeding in Massive Open Online Courses. - Nan Jiang, Zachary A. Pardos:
Binary Q-matrix Learning with dAFM.
Doctoral Consortium
- Matthew Woodruff:
Predicting student academic outcomes in UK secondary phase education: an architecture for machine learning and user interaction. - Zichao Wang:
Techniques for Automatically Evaluating Machine-Generated Questions. - Boxuan Ma:
Design of an Elective Course Recommendation System for University Environment. - Varshita Sher:
Anatomy of mobile learners: Using learning analytics to unveil learning in presence of mobile devices. - Zhang Guo, Roghayeh Barmaki:
Collaboration Analysis Using Object Detection. - Korah J. Wiley, Allison Bradford, Zachary A. Pardos, Marcia C. Linn:
Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction. - Huy Anh Nguyen, John C. Stamper, Bruce M. McLaren:
Towards Modeling Students' Problem-solving Skills in Non-routine Mathematics Problems. - Deniz Sonmez Unal:
Modeling Student Performance and Disengagement Using Decomposition of Response Time Data.
Industry Track
- Chad Coleman, Ryan S. Baker, Shonte Stephenson:
A Better Cold-Start for Early Prediction of Student At-Risk Status in New School Districts. - Jon Harmon, Rasil Warnakulasooriya:
Measuring Item Teaching Value in an Online Learning Environment. - Roger Smeets, Francette L. Broekman, Eric Bouwers:
Affect detection in home-based educational software for young children. - Colm P. Howlin, Charles D. Dziuban:
Detecting Outlier Behaviors in Student Progress Trajectories Using a Repeated Fuzzy Clustering Approach. - S. Thomas Christie, Daniel C. Jarratt, Lukas A. Olson, Taavi T. Taijala:
Machine-Learned School Dropout Early Warning at Scale. - Rachel Reddick:
Using a Glicko-based Algorithm to Measure In-Course Learning. - Raphaël Morsomme, Sofia Vazquez Alferez:
Content-based Course Recommender System for Liberal Arts Education.
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