17 Tanya Nazaretsky, Sara Hershkovitz and Giora Alexandron. Kappa Learning: A New Item-Similarity Method for Clustering Educational Items from Response Data
25 Tsung-Yen Yang, Christoph Studer, Ryan Baker, Neil Neffernan and Andrew Lan. Active Learning for Student Affect Detection
26 Rafael Wampfler, Severin Klingler, Barbara Solenthaler, Victor Schinazi and Markus Gross. Affective State Prediction in a Mobile Setting using Wearable Biometric Sensors and Stylus
31 Shamya Karumbaiah, Jaclyn Ocumpaugh and Ryan Baker. The Influence of School Demographics on the Relationship Between Student Outcomes and Their Help-Seeking Behavior in an Online Tuto
34 Niki Gitinabard, Sarah Heckman, Tiffany Barnes and Collin Lynch. What will you do next? A Sequence Analysis of the Student Transitions between Online Platforms
36 Han Jiang, Matthew Iandoli, Steven Van Dessel, Shichao Liu and Jacob Whitehill. Measuring students’ thermal comfort and its impact on learning
44 Zhiyun Ren, Xia Ning, Andrew Lan and Huzefa Rangwala. Grade Prediction Based on Cumulative Knowledge and Co-taken Courses
99 Atsushi Shimada. Optimizing Assignment of Students to Courses based on Learning Activity Analytics
110 Ye Mao, Rui Zhi, Farzaneh Khoshnevisan, Thomas Price, Tiffany Barnes and Min Chi. One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks
114 Josh Gardner, Yuming Yang, Ryan Baker and Christopher Brooks. Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective
122 Stephen Hutt, Margo Gardner, Angela L. Duckworth and Sidney D’Mello. Evaluating Fairness and Generalizability in Models of On-Time College Graduation from College Application Data
126 Joseph Reilly and Bertrand Schneider. Predicting the Quality of Collaborative Problem Solving Through Linguistic Analysis of Discourse
131 Benoît Choffin, Fabrice Popineau, Yolaine Bourda and Jill-Jênn Vie. DAS3H: a new student learning and forgetting model for optimally scheduling distributed practice of skills
132 Andrew Emerson, Andy Smith, Cody Smith, Fernando Rodríguez, Eric Wiebe, Bradford Mott, Kristy Boyer and James Lester. Predicting Early and Often: Predictive Student Modeling for Block-Based Programming Environments
138 Markel Sanz Ausin, Hamoon Azizsoltani, Tiffany Barnes and Min Chi. Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System
153 Lovenoor Aulck, Dev Nambi, Nishant Velagapudi, Joshua Blumenstock and Jevin West. Mining University Registrar Records to Predict First-Year Undergraduate Attrition
154 Rémi Venant and Mathieu d’Aquin. Towards the prediction of semantic complexity based on concept graphs
159 Guanliang Chen, David Lang, Rafael Ferreira and Dragan Gasevic. Predictors of Student Satisfaction: A Large-scale Study of Human-Human Online Tutorial Dialogues
163 Rui Zhi, Thomas Price, Samiha Marwan, Yihuan Dong, Nicholas Lytle and Tiffany Barnes. Toward Data-Driven Example Feedback for Novice Programming
171 Qian Hu and Huzefa Rangwala. Student’s Performance Estimation with Attention-based Graph Convolutional Networks
200 Huy Nguyen, Yeyu Wang, John Stamper and Bruce McLaren. Using Knowledge Component Modeling Techniques to Increase Domain Understanding in a Digital Learning Game
217 Tanja Käser and Daniel L. Schwartz. Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments



27 Antoine Pigeau, Olivier Aubert and Yannick Prié. Success prediction in MOOCs – A case study
28 Jacob Whitehill, Cecilia Aguerrebere and Benjamin Hylak. Do Learners Know What’s Good for Them? Crowdsourcing Subjective Ratings of OERs to Predict Learning Gains
29 Fangzhe Ai, Yishuai Chen, Yuchun Guo, Yongxiang Zhao, Guowei Fu, Zhenzhu Wang and Guangyan Wang. Concept-Aware Deep Knowledge Tracing and Exercise Recommendation in an Online Learning System
37 Daniel Weitekamp, Erik Harpstead, Napol Rachatasumrit, Christopher Maclellan and Kenneth R. Koedinger. Toward Near Zero-Parameter Prediction Using a Computational Model of Student Learning
43 John Kolb, Scott Farrar and Zach Pardos. Generalizing Expert Misconception Diagnoses Through Common Wrong Answer Embedding
50 Roi Shillo, Nicholas Hoernle and Kobi Gal. Detecting Creativity in an Open Ended Geometry Environment
51 Christian Hansen, Casper Hansen, Stephen Alstrup and Christina Lioma. Modelling End-of-Session Actions in Educational Systems
60 Xinyi Ding and Eric Larson. Why Deep Knowledge Tracing has less Depth than Anticipated
65 Cecilia Aguerrebere, Monica Bulger, Cristóbal Cobo, Sofía García, Gabriela Kaplan and Jacob Whitehill. How Should Online English as a Foreign Language Teachers Write their Feedback to Students?
71 Yong Han, Wenjun Wu, Suozhao Ji, Lijun Zhang and Hui Zhang. A Human-Machine Hybrid Peer Grading Framework for SPOCs
75 Emily Jensen, Stephen Hutt and Sidney D’Mello. Generalizability of Sensor-Free Affect Detection Models in a Longitudinal Dataset of Tens of Thousands of Students
77 Cathlyn Stone, Patrick Donnelly, Meghan Dale, Sarah Capello, Sean Kelly, Amanda Godley and Sidney K. D’Mello. Utterance-level Modeling of Indicators of Engaging Classroom Discourse
80 Takeru Sunahase, Yukino Baba and Hisashi Kashima. Probabilistic Modeling of Peer Correction and Peer Assessment
85 Unnam Abhishek, Rohit Takhar and Varun Aggarwal. Grading emails and generating feedback
87 Shalini Pandey and George Karypis. A Self Attentive model for Knowledge Tracing
92 Tianqi Wang, Qi Li, Jing Gao, Xia Jing and Jie Tang. Improving Peer Assessment Accuracy by Incorporating Relative Peer Grades
106 Arabella Sinclair, Kate McCurdy, Adam Lopez, Christopher G. Lucas and Dragan Gasevic. Tutorbot Corpus: Evidence of Human-Agent Verbal Alignment in Second Language Learner Dialogues
107 Julien Broisin and Clément Hérouard. Design and evaluation of a semantic indicator for automatically supporting programming learning
123 Shaghayegh Sahebi and Thanh-Nam Doan. Rank-Based Tensor Factorization for Predicting Student Performance
124 Russell Moore, Andrew Caines, Mark Elliott, Ahmed Zaidi, Andrew Rice and Paula Buttery. Skills Embeddings: a Neural Approach to Multicomponent Representations of Students and Tasks
125 Gabriel Zingle, Balaji Radhakrishnan, Yunkai Xiao, Edward Gehringer, Zhongcan Xiao, Ferry Pramudianto, Gauraang Khurana and Ayush Arnav. Detecting suggestions in peer assessments
137 Fatima Harrak, François Bouchet and Vanda Luengo. Categorizing students’ questions using an ensemble hybrid approach
141 Karina Huang, Tonya Bryant and Bertrand Schneider. Investigating Collaborative Learning States with Multimodal Data and Unsupervised Machine Learning
143 Noah Arthurs. Grades are not Normal: Improving Exam Score Models Using the Logit-Normal Distribution
151 Lu Ou, Abe Hofman, Vanessa Simmering, Timo Bechger, Gunter Maris and Han van der Maas. Modeling person-specific development of math skills in continuous time: New evidence for mutualism
152 Solmaz Abdi, Hassan Khosravi, Shazia Sadiq and Dragan Gasevic. A Multivariate ELO-based Learner Model for Adaptive Educational Systems
155 Jina Kang, Dongwook An, Lili Yan and Min Liu. Collaborative problem-solving process in a science serious game: Exploring Group Action Similarity Trajectory
157 Nisrine Ait Khayi and Vasile Rus. Clustering Students Based on Their Prior Knowledge
178 V. Elizabeth Owen, Marie-Helene Roy, K. P. Thai, Vesper Burnett, Daniel Jacobs, Eric Keylor and Ryan S. Baker. Detecting Wheel Spinning and Productive Persistence in Educational Games
187 Shahab Boumi and Adan Vela. Application of Hidden Markov Models to quantify the impact of enrollment patterns on student performance
191 Jingyu Wang, Chuankai Zhang, Yanzun Huang, Weiqi Fang, Dongyang Lu, Kenneth Holstein, Vincent Aleven, Stephen Fancsali and John Stamper. Early detection of wheel spinning: Comparison across tutors, models, features, and operationalizations
195 Munira Syed, Malolan Chetlur, Shazia Afzal, G. Alex Ambrose and Nitesh V. Chawla. Implicit and Explicit Emotions in MOOCs
196 Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell Stevens and Andreas Paepcke. Latent Variable Models of Enrollment for Course Planning and Understanding
207 Byungsoo Jeon, Eyal Shafran, Luke Breitfeller, Jason Levin and Carolyn P. Ros ́e. Time-series Insights into the Process of Passing or Failing Online University Courses using Neural-Induced Interpretable Student States
221 Agoritsa Polyzou, Athanasios N. Nikolakopoulos and George Karypis. ”Scholars Walk”: A Markov Chain Framework for Course Recommendation
224 Armando Toda, Wilk Oliveira, Lei Shi, Ig Ibert Bittencourt, Seiji Isotani and Alexandra Cristea. Towards Planning Gamification Strategies based on User Characteristics using Data Mining Techniques : A gender-based Case Study
229 Steven Dang and Kenneth Koedinger. Exploring the Link Between Motivations and Gaming
230 Sara Morsy and George Karypis. Neural Attentive Knowledge-based Model for Grade Prediction
238 Rajendra Banjade and Vasile Rus. Assessing Student Response in Tutorial Dialogue Context using Probabilistic Soft Logic
247 Anthony Raborn, Walter Leite and Katerina Marcoulides. A Comparison of Automated Scale Short Form Selection Strategies
249 Donia Malekian, James Bailey, Gregor Kennedy, Paula de Barba and Sadia Nawaz. Characterising Students’ Writing Processes Using Temporal Keystroke Analysis
250 Chen Liang, Jianbo Ye, Han Zhao, Bart Pursel and C. Lee Giles. Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations


19 Sanaz Bahargam, Theodoros Lappas and Evimaria Terzi. The Guided TeamPartitioning Problem: Definition, Complexity, and Algorithm
20 Chun-Kit Yeung. Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory
21 Christopher Krauss, Agathe Merceron and Stefan Arbanowski. Smart Learning Object Recommendations based on Time-Dependent Learning Need Models
23 Ange Adrienne Nyamen Tato, Roger Nkambou and Aude Dufresne. Combining Deep Neural Network with Expert Knowledge for Predicting Socio-Moral Reasoning skills
24 Anwar Ali Yahya and Addin Osman. A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs
38 Gaurav Nanda and Kerrie Douglas. Machine Learning Based Decision Support System for Categorizing MOOC Discussion Forum Posts
40 Yiqiao Xu, Niki Gitinabard, Collin Lynch and Tiffany Barnes. What You Say is Relevant to How You Make Friends: Measuring the Effect of Content on Social Connection
53 Oded Vainas, Yossi Ben-David, Ran Gilad-Bachrach, Meitar Ronen, Ori Bar-Ilan, Roi Shillo and Daniel Sitton. STAYING IN THE ZONE: SEQUENCING CONTENT IN CLASSROOMS BASED ON THE ZONE OF PROXIMAL DEVELOPMENT
54 Anthony F. Botelho, Ryan Baker and Neil Heffernan. Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Disengaged Behavior and Affect
56 Henry Anderson, Afshan Boodhwani and Ryan Baker. Assessing the Fairness of Graduation Predictions
74 Korah Wiley, Allison Bradford, Zach Pardos and Marcia Linn. Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction
83 Anik Jacobsen and Gerasimos Spanakis. It’s a Match! Reciprocal Recommender System forGraduating Students and Jobs
91 Yanjun Pu, Wenjun Wu and Tianrui Jiang. ATC Framework: A fully Automatic Cognitive Tracing Model for Student and Educational Contents
94 Tianqi Wang, Fenglong Ma and Jing Gao. Deep Hierarchical Knowledge Tracing
97 Juanita Hicks, Ruhan Circi and Mengyi Li. Students’ Use of Support Functions in DBAs: Analysis of NAEP Grade 8 Mathematics Process Data
103 Niklas Hjuler, Stephan Lorenzen and Stephen Alstrup. Investigating Writing Style Development in High School
104 Song Ju, Guojing Zhou and Min Chi. Identify Crucial Pedagogical Decisions through Adversarial Deep Reinforcement Learning
111 Shivangi Chopra, Abeer Khan, Melicaalsadat Mirsafian and Lukasz Golab. Gender Differences in Work-Integrated Learning
117 Mariana Oliveira and Carlos Mello. Identifying bias and underlying knowledge structures in Brazilian higher education national exam
127 Rachel Dickler, Haiying Li and Janice Gobert. A Data-Driven Approach for Automated Assessment of Scientific Explanations in Science Inquiry
129 Joseph Reilly and Chris Dede. Stealth Assessment via Deep Learning in an Open-Ended Virtual Environment
135 Fatima Harrak, François Bouchet, Vanda Luengo and Remi Bachelet. Automatic identification of questions in MOOC forums and association with self-regulated learning
136 Lucia Ramirez, William Yao, Edwin Chng, Iulian Radu and Bertrand Schneider. Toward Instrumenting Makerspaces: Using Motion Sensors to Capture Students’ Affective States and Social Interactions in Open-Ended Learning Environments
147 Bruno Emond and Julio J. Valdés. Visualizing Learning Performance Data and Model Predictions as Objects in a 3D Space
156 Tyler Angert and Bertrand Schneider. Augmenting Transcripts with Multimodal Data
160 Lujie Chen, Eva Gjekmarkaj and Artur Dubrawski. Parent as a Companion for Solving Challenging Math Problems: Insights from Multi-modal Observational Data
162 Varun Mandalapu and Jiaqi Gong. Studying Factors Influencing the Prediction of Student STEM and Non-STEM College Major Enrollment
164 Meng Cao, Philip Pavlik and Gavin Bidelman. Incorporating Prior Practice Difficulty into Performance Factor Analysis to Model Mandarin Tone Learning
167 David Boulanger and Vivekanandan Kumar. Shedding Light on the Automated Essay Scoring Process
169 Yupei Zhang, Huan Dai, Yue Yun and Xuequn Shang. Student Knowledge Diagnosis on Response Data via the Model of Sparse Factor Learning
173 Matthew Dong, Run Yu and Zachary Pardos. Design and deployment of a better university course search: Inferring latent keywords from enrollment networks
176 Matthew Guthrie and Zhongzhou Chen. Adding duration-based quality labels to learning events for improved description of students’ online learning behavior
182 Zichao Wang, Andrew Lan, Andrew Waters, Phillip Grimaldi and Richard Baraniuk. A Meta-Learning Approach to Automatic Short Answer Grading
193 Alfonso Díaz-Furlong, Alfonso Díaz-Cárdenas, Alicia Cuanalo-Pérez, Paola Flores-Espinoza and Dulce Guzmán-Márquez. Educational Research in Mexico: A Text Mining and Mapping Science Analysis
198 Ashvini Varatharaj, Anthony Botelho, Xiwen Lu and Neil Heffernan. Hǎo Fā Yīn: Developing Automated Audio Assessment Tools for a Chinese Language Course
205 Yuta Taniguchi, Atsushi Shimada and Shin’Ichi Konomi. Investigating Error Resolution Processes in C Programming Exercise Courses
206 Glenn Davis, Cindy Wang and Christina Yuan. N-gram Graphs for Topic Extraction in Educational Forums
208 Praseeda, Srinath Srinivasa and Prasad Ram. Validating the Myth of Average through Evidences
210 Rory Flemming, Emmanuel Schmück, Dominic Mussack, Pedro Cardoso-Leite and Paul Schrater. A generalizable performance evaluation model of driving games via risk-weighted trajectories
213 Mizuho Ikeda. Learning Feature Analysis for Quality Improvement of Web-Based Teaching Materials Using Mouse Cursor Tracking
220 Ahmed Zaidi, Andrew Caines, Christopher Davis, Russell Moore, Paula Buttery and Andrew Rice. Accurate modelling of language learning tasks and students using representations of grammatical proficiency
223 J.D Jayaraman. Supporting Minority Student Success by using Machine Learning to Identify At-Risk Students
245 Boniface Mbouzao, Michel Desmarais and Ian Shrier. A Methodology for Student Video Interaction Patterns Analysis and Classification
252 Dominic Mussack, Rory Flemming, Paul Schrater and Pedro Cardoso-Leite. Discovering item similarity through deep learning: combining item features and user behavior.
262 Alexander Askinadze. Predicting Student Drop-Out In Higher Education Based on Previous Exam Results
263 Andrea Davis and Yun Jin Rho. Individual Differences in Student Learning Aid Usage
264 Ben Levy, Arnon Hershkovitz, Odelia Tzayada, Orit Ezra, Avi Segal, Kobi Gal, Anat Cohen and Michal Tabach. Teacher vs. algorithm double-blind experiment of content sequencing in mathematics
267 Jaechoon Jo, Yeongwook Yang, Gyeongmin Kim and Heuiseok Lim. A Comparative Analysis of Emotional Words for Learning Effectiveness in Online Education
271 Varshita Sher. Investigating effects of considering mobile and desktop learning data on predictive power of learning management system (LMS) features on student success
272 Hammad Shaikh, Arghavan Modiri, Joseph Jay Williams and Anna Rafferty. Balancing Student Success and Inferring Personalized Effects in Dynamic Experiments
277 Daniel Furr. Visualization and clustering of learner pathways in an interactive online learning environment
281 Giora Alexandron, Jose Ruiperez Valiente and Dave Pritchard. Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses
283 Vincent Gagnon, Audrey Labrie, Michel Desmarais and Sameer Bhatnagar. Filtering non-relevant short answers in peer learning applications
284 Juan Miguel Andres-Bray, Jaclyn Ocumpaugh and Ryan S. Baker. Hello? Who is posting, who is answering, and who is succeeding in Massive Open Online Courses
290 Nan Jiang and Zach Pardos. Binary Q-matrix Learning with dAFM


270 Matthew Woodruff. Predicting student academic outcomes in UK secondary phase education: an architecture for machine learning and user interaction
273 Zichao Wang. Techniques for Automatically Evaluating Machine-Authored Homework Questions
274 Boxuan Ma. Design an Elective Course Recommendation System for University Environment
280 Varshita Sher. Anatomy of mobile learners: Using learning analytics to unveil learning in presence of mobile devices
282 Zhang Guo. Collaboration Analysis Using Object Detection
286 Korah Wiley, Allison Bradford, Zach Pardos and Marcia Linn. Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction
287 Huy Nguyen, John Stamper and Bruce McLaren. Towards Modeling Students’ Problem-solving Skills in Non-routine Mathematics Problems
289 Deniz Sonmez Unal. Modeling Student Performance and Disengagement Using Decomposition of Response Time Data


22 Chad Coleman, Ryan Baker and Shonte Stephenson. A Better Cold-Start for Early Prediction of Student At-Risk Status in New School Districts
118 Jon Harmon and Rasil Warnakulasooriya. Measuring Microlearning in an Online Learning Environment
214 Roger Smeets, Francette Broekman and Eric Bouwers. Affect detection in home-based educational software for young children
235 Colm Howlin and Charles Dziuban. Detecting Outlier Behaviors in Student Progress Trajectories Using a Repeated Fuzzy Clustering Approach
256 S. Thomas Christie, Daniel Jarratt, Lukas Olson and Taavi Taijala. Machine-Learned School Dropout Early Warning at Scale
257 Rachel Reddick. Using a Glicko-based Algorithm to Measure In-Course Learning
297 Raphael Morsomme and Sofia Vazquez. Course Recommender System in a Liberal Arts Context