{"id":493,"date":"2019-06-29T16:00:56","date_gmt":"2019-06-29T16:00:56","guid":{"rendered":"http:\/\/educationaldatamining.org\/edm2019\/?page_id=493"},"modified":"2019-07-26T11:13:58","modified_gmt":"2019-07-26T11:13:58","slug":"proceedings","status":"publish","type":"page","link":"https:\/\/educationaldatamining.org\/edm2019\/proceedings\/","title":{"rendered":"Proceedings"},"content":{"rendered":"\n\n\n\n
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<\/td>\nFull proceeding (pdf file)<\/a> – Full papers<\/a> – Short papers<\/a> – Poster papers<\/a> – DC papers<\/a> – Industry papers<\/a>.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
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<\/a>FULL PAPERS<\/h4>\n<\/td>\n<\/tr>\n

17<\/td>\nTanya Nazaretsky, Sara Hershkovitz and Giora Alexandron.\u00a0Kappa Learning: A New Item-Similarity Method for Clustering Educational Items from Response Data<\/a><\/td>\n<\/tr>\n
25<\/td>\nTsung-Yen Yang, Christoph Studer, Ryan Baker, Neil Neffernan and Andrew Lan.\u00a0Active Learning for Student Affect Detection<\/a><\/td>\n<\/tr>\n
26<\/td>\nRafael Wampfler, Severin Klingler, Barbara Solenthaler, Victor Schinazi and Markus Gross.\u00a0Affective State Prediction in a Mobile Setting using Wearable Biometric Sensors and Stylus<\/a><\/td>\n<\/tr>\n
31<\/td>\nShamya Karumbaiah, Jaclyn Ocumpaugh and Ryan Baker.\u00a0The Influence of School Demographics on the Relationship Between Student Outcomes and Their Help-Seeking Behavior in an Online Tuto<\/a><\/td>\n<\/tr>\n
34<\/td>\nNiki Gitinabard, Sarah Heckman, Tiffany Barnes and Collin Lynch.\u00a0What will you do next? A Sequence Analysis of the Student Transitions between Online Platforms<\/a><\/td>\n<\/tr>\n
36<\/td>\nHan Jiang, Matthew Iandoli, Steven Van Dessel, Shichao Liu and Jacob Whitehill.\u00a0Measuring students\u2019 thermal comfort and its impact on learning<\/a><\/td>\n<\/tr>\n
44<\/td>\nZhiyun Ren, Xia Ning, Andrew Lan and Huzefa Rangwala.\u00a0Grade Prediction Based on Cumulative Knowledge and Co-taken Courses<\/a><\/td>\n<\/tr>\n
99<\/td>\nAtsushi Shimada, Kousuke Mouri, Yuta Taniguchi, Hiroaki Ogata, Rin-Ichiro Taniguchi
\nand Shinichi Konomi.\u00a0Optimizing Assignment of Students to Courses based on Learning Activity Analytics<\/a><\/td>\n<\/tr>\n
110<\/td>\nYe Mao, Rui Zhi, Farzaneh Khoshnevisan, Thomas Price, Tiffany Barnes and Min Chi.\u00a0One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks<\/a><\/td>\n<\/tr>\n
114<\/td>\nJosh Gardner, Yuming Yang, Ryan Baker and Christopher Brooks.\u00a0Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective<\/a><\/td>\n<\/tr>\n
122<\/td>\nStephen Hutt, Margo Gardner, Angela L. Duckworth and Sidney D’Mello.\u00a0Evaluating Fairness and Generalizability in Models of On-Time College Graduation from College Application Data<\/a><\/td>\n<\/tr>\n
126<\/td>\nJoseph Reilly and Bertrand Schneider.\u00a0Predicting the Quality of Collaborative Problem Solving Through Linguistic Analysis of Discourse<\/a><\/td>\n<\/tr>\n
131<\/td>\nBeno\u00eet Choffin, Fabrice Popineau, Yolaine Bourda and Jill-J\u00eann Vie.\u00a0DAS3H: a new student learning and forgetting model for optimally scheduling distributed practice of skills<\/a><\/td>\n<\/tr>\n
132<\/td>\nAndrew Emerson, Andy Smith, Cody Smith, Fernando Rodr\u00edguez, Eric Wiebe, Bradford Mott, Kristy Boyer and James Lester.\u00a0Predicting Early and Often: Predictive Student Modeling for Block-Based Programming Environments<\/a><\/td>\n<\/tr>\n
138<\/td>\nMarkel Sanz Ausin, Hamoon Azizsoltani, Tiffany Barnes and Min Chi.\u00a0Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System<\/a><\/td>\n<\/tr>\n
153<\/td>\nLovenoor Aulck, Dev Nambi, Nishant Velagapudi, Joshua Blumenstock and Jevin West.\u00a0Mining University Registrar Records to Predict First-Year Undergraduate Attrition<\/a><\/td>\n<\/tr>\n
154<\/td>\nR\u00e9mi Venant and Mathieu d’Aquin.\u00a0Towards the prediction of semantic complexity based on concept graphs<\/a><\/td>\n<\/tr>\n
159<\/td>\nGuanliang Chen, David Lang, Rafael Ferreira and Dragan Gasevic.\u00a0Predictors of Student Satisfaction: A Large-scale Study of Human-Human Online Tutorial Dialogues<\/a><\/td>\n<\/tr>\n
163<\/td>\nRui Zhi, Thomas Price, Samiha Marwan, Yihuan Dong, Nicholas Lytle and Tiffany Barnes.\u00a0Toward Data-Driven Example Feedback for Novice Programming<\/a><\/td>\n<\/tr>\n
171<\/td>\nQian Hu and Huzefa Rangwala.\u00a0Academic Performance Estimation with Attention-based Graph Convolutional Networks<\/a><\/td>\n<\/tr>\n
200<\/td>\nHuy Nguyen, Yeyu Wang, John Stamper and Bruce McLaren.\u00a0Using Knowledge Component Modeling Techniques to Increase Domain Understanding in a Digital Learning Game<\/a><\/td>\n<\/tr>\n
217<\/td>\nTanja K\u00e4ser and Daniel L. Schwartz.\u00a0Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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<\/a>SHORT PAPERS<\/h4>\n<\/td>\n<\/tr>\n

27<\/td>\nAntoine Pigeau, Olivier Aubert and Yannick Pri\u00e9.\u00a0Success prediction in MOOCs – A case study<\/a><\/td>\n<\/tr>\n
28<\/td>\nJacob Whitehill, Cecilia Aguerrebere and Benjamin Hylak.\u00a0Do Learners Know What\u2019s Good for Them? Crowdsourcing Subjective Ratings of OERs to Predict Learning Gains<\/a><\/td>\n<\/tr>\n
29<\/td>\nFangzhe Ai, Yishuai Chen, Yuchun Guo, Yongxiang Zhao, Guowei Fu, Zhenzhu Wang and Guangyan Wang.\u00a0Concept-Aware Deep Knowledge Tracing and Exercise Recommendation in an Online Learning System<\/a><\/td>\n<\/tr>\n
37<\/td>\nDaniel Weitekamp, Erik Harpstead, Napol Rachatasumrit, Christopher Maclellan and Kenneth R. Koedinger.\u00a0Toward Near Zero-Parameter Prediction Using a Computational Model of Student Learning<\/a><\/td>\n<\/tr>\n
43<\/td>\nJohn Kolb, Scott Farrar and Zach Pardos.\u00a0Generalizing Expert Misconception Diagnoses Through Common Wrong Answer Embedding<\/a><\/td>\n<\/tr>\n
50<\/td>\nRoi Shillo, Nicholas Hoernle and Kobi Gal.\u00a0Detecting Creativity in an Open Ended Geometry Environment<\/a><\/td>\n<\/tr>\n
51<\/td>\nChristian Hansen, Casper Hansen, Stephen Alstrup and Christina Lioma.\u00a0Modelling End-of-Session Actions in Educational Systems<\/a><\/td>\n<\/tr>\n
60<\/td>\nXinyi Ding and Eric Larson.\u00a0Why Deep Knowledge Tracing has less Depth than Anticipated<\/a><\/td>\n<\/tr>\n
65<\/td>\nCecilia Aguerrebere, Monica Bulger, Crist\u00f3bal Cobo, Sof\u00eda Garc\u00eda, Gabriela Kaplan and Jacob Whitehill.\u00a0How Should Online English as a Foreign Language Teachers Write their Feedback to Students?<\/a><\/td>\n<\/tr>\n
71<\/td>\nYong Han, Wenjun Wu, Suozhao Ji, Lijun Zhang and Hui Zhang.\u00a0A Human-Machine Hybrid Peer Grading Framework for SPOCs<\/a><\/td>\n<\/tr>\n
75<\/td>\nEmily Jensen, Stephen Hutt and Sidney D’Mello.\u00a0Generalizability of Sensor-Free Affect Detection Models in a Longitudinal Dataset of Tens of Thousands of Students<\/a><\/td>\n<\/tr>\n
77<\/td>\nCathlyn Stone, Patrick Donnelly, Meghan Dale, Sarah Capello, Sean Kelly, Amanda Godley and Sidney K. D’Mello.\u00a0Utterance-level Modeling of Indicators of Engaging Classroom Discourse<\/a><\/td>\n<\/tr>\n
80<\/td>\nTakeru Sunahase, Yukino Baba and Hisashi Kashima.\u00a0Probabilistic Modeling of Peer Correction and Peer Assessment<\/a><\/td>\n<\/tr>\n
85<\/td>\nUnnam Abhishek, Rohit Takhar and Varun Aggarwal.\u00a0Grading emails and generating feedback<\/a><\/td>\n<\/tr>\n
87<\/td>\nShalini Pandey and George Karypis.\u00a0A Self Attentive model for Knowledge Tracing<\/a><\/td>\n<\/tr>\n
92<\/td>\nTianqi Wang, Qi Li, Jing Gao, Xia Jing and Jie Tang.\u00a0Improving Peer Assessment Accuracy by Incorporating Relative Peer Grades<\/a><\/td>\n<\/tr>\n
106<\/td>\nArabella Sinclair, Kate McCurdy, Adam Lopez, Christopher G. Lucas and Dragan Gasevic.\u00a0Tutorbot Corpus: Evidence of Human-Agent Verbal Alignment in Second Language Learner Dialogues<\/a><\/td>\n<\/tr>\n
107<\/td>\nJulien Broisin and Cl\u00e9ment H\u00e9rouard.\u00a0Design and evaluation of a semantic indicator for automatically supporting programming learning<\/a><\/td>\n<\/tr>\n
123<\/td>\nShaghayegh Sahebi and Thanh-Nam Doan.\u00a0Rank-Based Tensor Factorization for Predicting Student Performance<\/a><\/td>\n<\/tr>\n
124<\/td>\nRussell Moore, Andrew Caines, Mark Elliott, Ahmed Zaidi, Andrew Rice and Paula Buttery.\u00a0Skills Embeddings: a Neural Approach to Multicomponent Representations of Students and Tasks<\/a><\/td>\n<\/tr>\n
125<\/td>\nGabriel Zingle, Balaji Radhakrishnan, Yunkai Xiao, Edward Gehringer, Zhongcan Xiao, Ferry Pramudianto, Gauraang Khurana and Ayush Arnav.\u00a0Detecting suggestions in peer assessments<\/a><\/td>\n<\/tr>\n
137<\/td>\nFatima Harrak, Fran\u00e7ois Bouchet and Vanda Luengo.\u00a0Categorizing students’ questions using an ensemble hybrid approach<\/a><\/td>\n<\/tr>\n
141<\/td>\nKarina Huang, Tonya Bryant and Bertrand Schneider. Identifying Collaborative Learning States Using Unsupervised Machine Learning on Eye-Tracking, Physiological and Motion Sensor Data<\/a><\/td>\n<\/tr>\n
143<\/td>\nNoah Arthurs.\u00a0Grades are not Normal: Improving Exam Score Models Using the Logit-Normal Distribution<\/a><\/td>\n<\/tr>\n
151<\/td>\nLu Ou, Abe Hofman, Vanessa Simmering, Timo Bechger, Gunter Maris and Han van der Maas.\u00a0Modeling person-specific development of math skills in continuous time: New evidence for mutualism<\/a><\/td>\n<\/tr>\n
152<\/td>\nSolmaz Abdi, Hassan Khosravi, Shazia Sadiq and Dragan Gasevic.\u00a0A Multivariate ELO-based Learner Model for Adaptive Educational Systems<\/a><\/td>\n<\/tr>\n
155<\/td>\nJina Kang, Dongwook An, Lili Yan and Min Liu.\u00a0Collaborative problem-solving process in a science serious game: Exploring Group Action Similarity Trajectory<\/a><\/td>\n<\/tr>\n
157<\/td>\nNisrine Ait Khayi and Vasile Rus.\u00a0Clustering Students Based on Their Prior Knowledge<\/a><\/td>\n<\/tr>\n
178<\/td>\nV. Elizabeth Owen, Marie-Helene Roy, K. P. Thai, Vesper Burnett, Daniel Jacobs, Eric Keylor and Ryan S. Baker.\u00a0Detecting Wheel Spinning and Productive Persistence in Educational Games<\/a><\/td>\n<\/tr>\n
187<\/td>\nShahab Boumi and Adan Vela.\u00a0Application of Hidden Markov Models to quantify the impact of enrollment patterns on student performance<\/a><\/td>\n<\/tr>\n
191<\/td>\nJingyu Wang, Chuankai Zhang, Yanzun Huang, Weiqi Fang, Dongyang Lu, Kenneth Holstein, Vincent Aleven, Stephen Fancsali and John Stamper.\u00a0Early detection of wheel spinning: Comparison across tutors, models, features, and operationalizations<\/a><\/td>\n<\/tr>\n
195<\/td>\nMunira Syed, Malolan Chetlur, Shazia Afzal, G. Alex Ambrose and Nitesh V. Chawla.\u00a0Implicit and Explicit Emotions in MOOCs<\/a><\/td>\n<\/tr>\n
196<\/td>\nNate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell Stevens and Andreas Paepcke.\u00a0Using Latent Variable Models to Observe Academic Pathways<\/a><\/td>\n<\/tr>\n
207<\/td>\nByungsoo Jeon, Eyal Shafran, Luke Breitfeller, Jason Levin and Carolyn P. Ros \u0301e.\u00a0Time-series Insights into the Process of Passing or Failing Online University Courses using Neural-Induced Interpretable Student States<\/a><\/td>\n<\/tr>\n
221<\/td>\nAgoritsa Polyzou, Athanasios N. Nikolakopoulos and George Karypis.\u00a0‘‘Scholars Walk”: A Markov Chain Framework for Course Recommendation<\/a><\/td>\n<\/tr>\n
224<\/td>\nArmando Toda, Wilk Oliveira, Lei Shi, Ig Ibert Bittencourt, Seiji Isotani and Alexandra Cristea.\u00a0Towards Planning Gamification Strategies based on User Characteristics using Data Mining Techniques : A gender-based Case Study<\/a><\/td>\n<\/tr>\n
229<\/td>\nSteven Dang and Kenneth Koedinger.\u00a0Exploring the Link Between Motivations and Gaming<\/a><\/td>\n<\/tr>\n
230<\/td>\nSara Morsy and George Karypis.\u00a0Neural Attentive Knowledge-based Model for Grade Prediction<\/a><\/td>\n<\/tr>\n
238<\/td>\nRajendra Banjade and Vasile Rus.\u00a0Assessing Student Response in Tutorial Dialogue Context using Probabilistic Soft Logic<\/a><\/td>\n<\/tr>\n
247<\/td>\nAnthony Raborn, Walter Leite and Katerina Marcoulides.\u00a0A Comparison of Automated Scale Short Form Selection Strategies<\/a><\/td>\n<\/tr>\n
249<\/td>\nDonia Malekian, James Bailey, Gregor Kennedy, Paula de Barba and Sadia Nawaz.\u00a0Characterising Students\u2019 Writing Processes Using Temporal Keystroke Analysis<\/a><\/td>\n<\/tr>\n
250<\/td>\nChen Liang, Jianbo Ye, Han Zhao, Bart Pursel and C. Lee Giles.\u00a0Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations<\/a><\/td>\n<\/tr>\n
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<\/a>POSTER PAPERS<\/h4>\n<\/td>\n<\/tr>\n

19<\/td>\nSanaz Bahargam, Theodoros Lappas and Evimaria Terzi.\u00a0The Guided TeamPartitioning Problem: Definition, Complexity, and Algorithm<\/a><\/td>\n<\/tr>\n
20<\/td>\nChun-Kit Yeung.\u00a0Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory<\/a><\/td>\n<\/tr>\n
21<\/td>\nChristopher Krauss, Agathe Merceron and Stefan Arbanowski.\u00a0Smart Learning Object Recommendations based on Time-Dependent Learning Need Models<\/a><\/td>\n<\/tr>\n
23<\/td>\nAnge Adrienne Nyamen Tato, Roger Nkambou and Aude Dufresne.\u00a0Combining Deep Neural Network with Expert Knowledge for Predicting Socio-Moral Reasoning skills<\/a><\/td>\n<\/tr>\n
24<\/td>\nAnwar Ali Yahya and Addin Osman.\u00a0A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs<\/a><\/td>\n<\/tr>\n
38<\/td>\nGaurav Nanda and Kerrie Douglas.\u00a0Machine Learning Based Decision Support System for Categorizing MOOC Discussion Forum Posts<\/a><\/td>\n<\/tr>\n
40<\/td>\nYiqiao Xu, Niki Gitinabard, Collin Lynch and Tiffany Barnes.\u00a0What You Say is Relevant to How You Make Friends: Measuring the Effect of Content on Social Connection<\/a><\/td>\n<\/tr>\n
53<\/td>\nOded Vainas, Yossi Ben-David, Ran Gilad-Bachrach, Meitar Ronen, Ori Bar-Ilan, Roi Shillo and Daniel Sitton.\u00a0Staying in the Zone: Sequencing Content in Classrooms Based on the Zone of Proximal Development<\/a><\/td>\n<\/tr>\n
54<\/td>\nAnthony F. Botelho, Ryan Baker and Neil Heffernan.\u00a0Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Disengaged Behavior and Affect<\/a><\/td>\n<\/tr>\n
56<\/td>\nHenry Anderson, Afshan Boodhwani and Ryan Baker.\u00a0Assessing the Fairness of Graduation Predictions<\/a><\/td>\n<\/tr>\n
74<\/td>\nKorah Wiley, Allison Bradford, Zach Pardos and Marcia Linn.\u00a0Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction<\/a><\/td>\n<\/tr>\n
83<\/td>\nAnik Jacobsen and Gerasimos Spanakis.\u00a0It\u2019s a Match! Reciprocal Recommender System for Graduating Students and Jobs<\/a><\/td>\n<\/tr>\n
91<\/td>\nYanjun Pu, Wenjun Wu and Tianrui Jiang.\u00a0ATC Framework: A fully Automatic Cognitive Tracing Model for Student and Educational Contents<\/a><\/td>\n<\/tr>\n
94<\/td>\nTianqi Wang, Fenglong Ma and Jing Gao.\u00a0Deep Hierarchical Knowledge Tracing<\/a><\/td>\n<\/tr>\n
97<\/td>\nJuanita Hicks, Ruhan Circi and Mengyi Li.\u00a0Students\u2019 Use of Support Functions in DBAs: Analysis of NAEP Grade 8 Mathematics Process Data<\/a><\/td>\n<\/tr>\n
103<\/td>\nNiklas Hjuler, Stephan Lorenzen and Stephen Alstrup.\u00a0Investigating Writing Style Development in High School<\/a><\/td>\n<\/tr>\n
104<\/td>\nSong Ju, Guojing Zhou and Min Chi.\u00a0Identify Crucial Pedagogical Decisions through Adversarial Deep Reinforcement Learning<\/a><\/td>\n<\/tr>\n
111<\/td>\nShivangi Chopra, Abeer Khan, Melicaalsadat Mirsafian and Lukasz Golab.\u00a0Gender Differences in Work-Integrated Learning<\/a><\/td>\n<\/tr>\n
117<\/td>\nMariana Oliveira and Carlos Mello.\u00a0Identifying bias and underlying knowledge structures in Brazilian higher education national exam<\/a><\/td>\n<\/tr>\n
127<\/td>\nRachel Dickler, Haiying Li and Janice Gobert.\u00a0A Data-Driven Approach for Automated Assessment of Scientific Explanations in Science Inquiry<\/a><\/td>\n<\/tr>\n
129<\/td>\nJoseph Reilly and Chris Dede.\u00a0Stealth Assessment via Deep Learning in an Open-Ended Virtual Environment<\/a><\/td>\n<\/tr>\n
135<\/td>\nFatima Harrak, Fran\u00e7ois Bouchet, Vanda Luengo and Remi Bachelet.\u00a0Automatic identification of questions in MOOC forums and association with self-regulated learning<\/a><\/td>\n<\/tr>\n
136<\/td>\nLucia Ramirez, William Yao, Edwin Chng, Iulian Radu and Bertrand Schneider.\u00a0Toward Instrumenting Makerspaces: Using Motion Sensors to Capture Students\u2019 Affective States and Social Interactions in Open-Ended Learning Environments<\/a><\/td>\n<\/tr>\n
147<\/td>\nBruno Emond and Julio J. Vald\u00e9s.\u00a0Visualizing Learning Performance Data and Model Predictions as Objects in a 3D Space<\/a><\/td>\n<\/tr>\n
156<\/td>\nTyler Angert and Bertrand Schneider.\u00a0Augmenting Transcripts with\u00a0Natural Language Processing and\u00a0Multimodal Data<\/a><\/td>\n<\/tr>\n
160<\/td>\nLujie Chen, Eva Gjekmarkaj and Artur Dubrawski.\u00a0Parent as a Companion for Solving Challenging Math Problems: Insights from Multi-modal Observational Data<\/a><\/td>\n<\/tr>\n
162<\/td>\nVarun Mandalapu and Jiaqi Gong. Studying Factors Influencing the Prediction of Student STEM and Non-STEM Career Choice<\/a><\/td>\n<\/tr>\n
164<\/td>\nMeng Cao, Philip Pavlik and Gavin Bidelman.\u00a0Incorporating Prior Practice Difficulty into Performance Factor Analysis to Model Mandarin Tone Learning<\/a><\/td>\n<\/tr>\n
167<\/td>\nDavid Boulanger and Vivekanandan Kumar.\u00a0Shedding Light on the Automated Essay Scoring Process<\/a><\/td>\n<\/tr>\n
169<\/td>\nYupei Zhang, Huan Dai, Yue Yun and Xuequn Shang.\u00a0Student Knowledge Diagnosis on Response Data via the Model of Sparse Factor Learning<\/a><\/td>\n<\/tr>\n
173<\/td>\nMatthew Dong, Run Yu and Zachary Pardos.\u00a0Design and deployment of a better university course search: Inferring latent keywords from enrollment networks<\/a><\/td>\n<\/tr>\n
176<\/td>\nMatthew Guthrie and Zhongzhou Chen.\u00a0Adding duration-based quality labels to learning events for improved description of students\u2019 online learning behavior<\/a><\/td>\n<\/tr>\n
182<\/td>\nZichao Wang, Andrew Lan, Andrew Waters, Phillip Grimaldi and Richard Baraniuk.\u00a0A Meta-Learning Approach to Automatic Short Answer Grading<\/a><\/td>\n<\/tr>\n
198<\/td>\nAshvini Varatharaj, Anthony Botelho, Xiwen Lu and Neil Heffernan.\u00a0H\u01ceo F\u0101 Y\u012bn: Developing Automated Audio Assessment Tools for a Chinese Language Course<\/a><\/td>\n<\/tr>\n
205<\/td>\nYuta Taniguchi, Atsushi Shimada and Shin’Ichi Konomi.\u00a0Investigating Error Resolution Processes in C Programming Exercise Courses<\/a><\/td>\n<\/tr>\n
206<\/td>\nGlenn Davis, Cindy Wang and Christina Yuan.\u00a0N-gram Graphs for Topic Extraction in Educational Forums<\/a><\/td>\n<\/tr>\n
208<\/td>\nPraseeda, Srinath Srinivasa and Prasad Ram.\u00a0Validating the Myth of Average through Evidences<\/a><\/td>\n<\/tr>\n
210<\/td>\nRory Flemming, Emmanuel Schm\u00fcck, Dominic Mussack, Pedro Cardoso-Leite and Paul Schrater.\u00a0A generalizable performance evaluation model of driving games via risk-weighted trajectories<\/a><\/td>\n<\/tr>\n
213<\/td>\nMizuho Ikeda.\u00a0Learning Feature Analysis for Quality Improvement of Web-Based Teaching Materials Using Mouse Cursor Tracking<\/a><\/td>\n<\/tr>\n
220<\/td>\nAhmed Zaidi, Andrew Caines, Christopher Davis, Russell Moore, Paula Buttery and Andrew Rice.\u00a0Accurate modelling of language learning tasks and students using representations of grammatical proficiency<\/a><\/td>\n<\/tr>\n
223<\/td>\nJ.D Jayaraman.\u00a0Supporting Minority Student Success by using Machine Learning to Identify At-Risk Students<\/a><\/td>\n<\/tr>\n
245<\/td>\nBoniface Mbouzao, Michel Desmarais and Ian Shrier.\u00a0A Methodology for Student Video Interaction Patterns Analysis and Classification<\/a><\/td>\n<\/tr>\n
252<\/td>\nDominic Mussack, Rory Flemming, Paul Schrater and Pedro Cardoso-Leite.\u00a0Discovering item similarity through deep learning: combining item features and user behavior.<\/a><\/td>\n<\/tr>\n
262<\/td>\nAlexander Askinadze.\u00a0Predicting Student Drop-Out In Higher Education Based on Previous Exam Results<\/a><\/td>\n<\/tr>\n
263<\/td>\nAndrea Davis and Yun Jin Rho.\u00a0Individual Differences in Student Learning Aid Usage<\/a><\/td>\n<\/tr>\n
264<\/td>\nBen Levy, Arnon Hershkovitz, Odelia Tzayada, Orit Ezra, Avi Segal, Kobi Gal, Anat Cohen and Michal Tabach.\u00a0Teacher vs. algorithm double-blind experiment of content sequencing in mathematics<\/a><\/td>\n<\/tr>\n
267<\/td>\nJaechoon Jo, Yeongwook Yang, Gyeongmin Kim and Heuiseok Lim.\u00a0A Comparative Analysis of Emotional Words for Learning Effectiveness in Online Education<\/a><\/td>\n<\/tr>\n
271<\/td>\nVarshita Sher.\u00a0Investigating effects of considering mobile and desktop learning data on predictive power of learning management system (LMS) features on student success<\/a><\/td>\n<\/tr>\n
272<\/td>\nHammad Shaikh, Arghavan Modiri, Joseph Jay Williams and Anna Rafferty.\u00a0Balancing Student Success and Inferring Personalized Effects in Dynamic Experiments<\/a><\/td>\n<\/tr>\n
277<\/td>\nDaniel Furr.\u00a0Visualization and clustering of learner pathways in an interactive online learning environment<\/a><\/td>\n<\/tr>\n
281<\/td>\nGiora Alexandron, Jose Ruiperez Valiente and Dave Pritchard.\u00a0Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses<\/a><\/td>\n<\/tr>\n
283<\/td>\nVincent Gagnon, Audrey Labrie, Michel Desmarais and Sameer Bhatnagar.\u00a0Filtering non-relevant short answers in peer learning applications<\/a><\/td>\n<\/tr>\n
284<\/td>\nJuan Miguel Andres-Bray, Jaclyn Ocumpaugh and Ryan S. Baker.\u00a0Hello? Who is posting, who is answering, and who is succeeding in Massive Open Online Courses<\/a><\/td>\n<\/tr>\n
290<\/td>\nNan Jiang and Zach Pardos.\u00a0Binary Q-matrix Learning with dAFM<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
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<\/a>DOCTORAL CONSORTIUM<\/span><\/span><\/h4>\n<\/td>\n<\/tr>\n

270<\/span><\/td>\nMatthew Woodruff.\u00a0Predicting student academic outcomes in UK secondary phase education: an architecture for machine learning and user interaction<\/a><\/span><\/td>\n<\/tr>\n
273<\/span><\/td>\nZichao Wang.\u00a0Techniques for Automatically Evaluating Machine-Authored Homework Questions<\/a><\/span><\/td>\n<\/tr>\n
274<\/span><\/td>\nBoxuan Ma.\u00a0Design an Elective Course Recommendation System for University Environment<\/a><\/span><\/td>\n<\/tr>\n
280<\/span><\/td>\nVarshita Sher.\u00a0Anatomy of mobile learners: Using learning analytics to unveil learning in presence of mobile devices<\/a><\/span><\/td>\n<\/tr>\n
282<\/span><\/td>\nZhang Guo.\u00a0Collaboration Analysis Using Object Detection<\/a><\/span><\/td>\n<\/tr>\n
286<\/span><\/td>\nKorah Wiley, Allison Bradford, Zach Pardos and Marcia Linn.\u00a0Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction<\/a><\/span><\/td>\n<\/tr>\n
287<\/span><\/td>\nHuy Nguyen, John Stamper and Bruce McLaren.\u00a0Towards Modeling Students\u2019 Problem-solving Skills in Non-routine Mathematics Problems<\/a><\/span><\/td>\n<\/tr>\n
289<\/span><\/td>\nDeniz Sonmez Unal.\u00a0Modeling Student Performance and Disengagement Using Decomposition of Response Time Data<\/a><\/span><\/td>\n<\/tr>\n
\u00a0<\/span><\/td>\n\u00a0<\/span><\/td>\n<\/tr>\n
\n

<\/a>INDUSTRY TRACK<\/span><\/span><\/h4>\n<\/td>\n<\/tr>\n

22<\/span><\/td>\nChad Coleman, Ryan Baker and Shonte Stephenson.\u00a0A Better Cold-Start for Early Prediction of Student At-Risk Status in New School Districts<\/a><\/span><\/td>\n<\/tr>\n
118<\/span><\/td>\nJon Harmon and Rasil Warnakulasooriya.\u00a0Measuring Microlearning in an Online Learning Environment<\/a><\/span><\/td>\n<\/tr>\n
214<\/span><\/td>\nRoger Smeets, Francette Broekman and Eric Bouwers.\u00a0Affect detection in home-based educational software for young children<\/a><\/span><\/td>\n<\/tr>\n
235<\/span><\/td>\nColm Howlin and Charles Dziuban.\u00a0Detecting Outlier Behaviors in Student Progress Trajectories Using a Repeated Fuzzy Clustering Approach<\/a><\/span><\/td>\n<\/tr>\n
256<\/span><\/td>\nS. Thomas Christie, Daniel Jarratt, Lukas Olson and Taavi Taijala.\u00a0Machine-Learned School Dropout Early Warning at Scale<\/a><\/span><\/td>\n<\/tr>\n
257<\/span><\/td>\nRachel Reddick.\u00a0Using a Glicko-based Algorithm to Measure In-Course Learning<\/a><\/span><\/td>\n<\/tr>\n
297<\/span><\/td>\nRaphael Morsomme and Sofia Vazquez.\u00a0Course Recommender System in a Liberal Arts Context<\/a><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Full proceeding (pdf file) – Full papers – Short papers – Poster papers – DC papers – Industry papers. FULL PAPERS 17 Tanya Nazaretsky, Sara Hershkovitz and Giora Alexandron.\u00a0Kappa Learning: A New Item-Similarity Method for Clustering Educational Items from Response… Continue Reading →<\/a><\/p>\n","protected":false},"author":5,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-493","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/pages\/493","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/comments?post=493"}],"version-history":[{"count":20,"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/pages\/493\/revisions"}],"predecessor-version":[{"id":564,"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/pages\/493\/revisions\/564"}],"wp:attachment":[{"href":"https:\/\/educationaldatamining.org\/edm2019\/wp-json\/wp\/v2\/media?parent=493"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}