Organized by the International Educational Data Mining Society (IEDMS).


To discover more about sponsorship contact David Lindrum

Accepted submissions

Best papers and exemplary papers

A total of 16 exemplary papers were selected by the program chairs as those that represent the best work submitted to EDM 2016. Candidates for exemplary papers were selected among those accepted as full papers using the following criteria: 1) the average ratings of all reviewers and 2) at least one reviewer indicated the paper should be considered for best paper. Program Chairs and the General Chair then performed meta-reviews for all of these papers to make the final exemplary paper selections.

Finally, the Best Paper Committee was formed to review the top papers in the conference to select best paper nominations. We used random selection to divide both the 16 exemplary papers and the 10 committee members into two groups. All members in the same Best Paper Sub-committee received the same 8 exemplary papers together with their reviews. Sub-committee members were asked to rank the three best papers from the 8 papers, and to provide a 1-2 sentence justification for each of the top 3 they chose. Based on these rankings, four Best Paper nominees were selected.

Best Paper Committee:

Koedinger, Kenneth
Pavlik Jr., Philip I.
Aleven, Vincent
Baker, Ryan
Galyardt, April
Goldin, Ilya
Heffernan, Neil
Ritter, Steven
Olney, Andrew
Pechenizkiy, Mykola

Best paper

How Deep is Knowledge Tracing?
Mohammad Khajah, Robert Lindsey and Michael Mozer

Best student paper

Calibrated Self-Assessment
Igor Labutov and Christoph Studer

Best paper nominees

LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos
Arjun Sharma, Arijit Biswas, Ankit Gandhi, Sonal Patil and Om Deshmukh

How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual Representations
Martina Rau, Blake Mason and Robert Nowak

Measuring Gameplay Affordances of User-Generated Content in an Educational Game
Andrew Hicks, Zhongxiu Liu and Tiffany Barnes


The following submissions have been accepted for EDM 2016. Papers marked with * are exemplary papers.

Full Papers (30)

11Temporally Coherent Clustering of Student Data *
Severin Klingler, Tanja Käser, Barbara Solenthaler and Markus Gross

17Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming *
Benjamin Paaßen, Joris Jensen and Barbara Hammer

23Dynamics of Peer Grading: An Empirical Study
Luca de Alfaro and Michael Shavlovsky

33Generating Data-driven Hints for Open-ended Programming *
Thomas Price, Yihuan Dong and Tiffany Barnes

42A Coupled User Clustering Algorithm for Web-based Learning Systems
Ke Niu, Zhendong Niu, Xiangyu Zhao, Kai Kang and Min Ye

46Effect of student ability and question difficulty on duration *
Yijun Ma, Lalitha Agnihotri, Ryan Baker and Shirin Mojarad

62An Ensemble Method to Predict Student Performance in an Online Math Learning Environment
Martin Stapel, Zhilin Zheng and Niels Pinkwart

63Gauging MOOC Learners' Adherence to the Designed Learning Path
Daniel Davis, Guanliang Chen, Claudia Hauff and Geert-Jan Houben

64LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos
Arjun Sharma, Arijit Biswas, Ankit Gandhi, Sonal Patil and Om Deshmukh

75Student Usage Predicts Treatment Effect Heterogeneity in the Cognitive Tutor Algebra I Program
Adam Sales, Asa Wilks and John Pane

76Riding an emotional roller-coaster: A multimodal study of young child's math problem solving activities *
Lujie Chen, Xin Li, Zhuyun Xia, Zhanmei Song, Louis-Philippe Morency and Artur Dubrawski

77The Affective Impact of Tutor Questions: Predicting Frustration and Engagement *
Alexandria Vail, Joseph Wiggins, Joseph Grafsgaard, Kristy Boyer, Eric Wiebe and James Lester

78The Eyes Have It: Gaze-based Detection of Mind Wandering during Learning with an Intelligent Tutoring System *
Stephen Hutt, Caitlin Mills, Shelby White, Patrick J. Donnelly and Sidney K. D'Mello

87How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual Representations
Martina Rau, Blake Mason and Robert Nowak

89Joint Discovery of Skill Prerequisite Graphs and Student Models
Yetian Chen, José González-Brenes and Jin Tian

92Modeling the Influence of Format and Depth during Effortful Retrieval Practice *
Jaclyn K. Maass and Philip I. Pavlik Jr.

100Measuring Gameplay Affordances of User-Generated Content in an Educational Game
Andrew Hicks, Zhongxiu Liu and Tiffany Barnes

118The Apprentice Learner Architecture: Closing the loop between learning theory and educational data *
Christopher Maclellan, Erik Harpstead, Rony Patel and Kenneth Koedinger

121MOOC Learner Behaviors by Country and Culture; an Exploratory Analysis
Zhongxiu Liu, Rebecca Brown, Collin Lynch, Tiffany Barnes, Ryan Baker, Yoav Bergner and Danielle Mcnamara

123Predicting Post-Test Performance from Student Behavior: A High School MOOC Case Study
Sabina Tomkins, Arti Ramesh and Lise Getoor

126{ENTER}ing the Time Series {SPACE}: Uncovering the Writing Process through Keystroke Analyses
Laura Allen, Matthew Jacovina, Mihai Dascalu, Rod Roscoe, Kevin Kent, Aaron Likens and Danielle McNamara

137Unnatural Feature Engineering: Evolving Augmented Graph Grammars for Argument Diagrams
Linting Xue, Collin Lynch and Min Chi

140Semantic Features of Math Problems: Relationships to Student Learning and Engagement *
Stefan Slater, Jaclyn Ocumpaugh, Ryan Baker, Peter Scupelli, Paul Salvador Inventado and Neil Heffernan

143Automatic Gaze-Based Detection of Mind Wandering during Film Viewing
Robert Bixler, Caitlin Mills, Xinyi Wang and Sidney D'Mello

144How Deep is Knowledge Tracing? *
Mohammad Khajah, Robert Lindsey and Michael Mozer

154Modelling the way: Using action sequence archetypes to differentiate learning pathways from learning outcomes
Kelvin H. R. Ng, Kevin Hartman, Kai Liu and Andy W H Khong

158Calibrated Self-Assessment
Igor Labutov and Christoph Studer

159Web as a textbook: Curating Targeted Learning Paths through the Heterogeneous Learning Resources on the Web *
Igor Labutov and Hod Lipson

164Sequence Matters, But How Exactly? A Methodology for Evaluating Activity Sequences from Data
Shayan Doroudi, Kenneth Holstein, Vincent Aleven and Emma Brunskill

172Mining behaviors of students in autograding submission system logs
Jessica McBroom, Bryn Jeffries, Irena Koprinska and Kalina Yacef

Short Papers (55)

12On Competition for Undergraduate Co-op Placements: A Graph Mining Approach
Yuheng Jiang and Lukasz Golab

13Properties and Applications of Wrong Answers in Online Educational Systems
Pelánek and Jiří Řihák

15A Scalable Learning Analytics Platform for Automated Writing Feedback
Jacqueline Feild, Nicolas Lewkow, Neil Zimmerman, Mark Riedesel and Alfred Essa

18A Contextual Bandits Framework for Personalized Learning Action Selection
Andrew Lan and Richard Baraniuk

20Collaborative Problem Solving Skills versus Collaboration Outcomes: Findings from Statistical Analysis and Data Mining
Jiangang Hao, Lei Liu, Alina von Davier, Patrick Kyllonen and Christopher Kitchen

21Using Inverse Planning for Personalized Feedback
Anna Rafferty, Rachel Jansen and Thomas Griffiths

22Predicting Performance on MOOC Assessments using Multi-Regression Models
Zhiyun Ren, Huzefa Rangwala and Aditya Johri

26Predicting Student Progress from Peer-Assessment Data
Michael Mogessie Ashenafi, Marco Ronchetti and Giuseppe Riccardi

27A Comparison of Automatic Teaching Strategies for Heterogeneous Student Populations
Benjamin Clement, Pierre-Yves Oudeyer and Manuel Lopes

31Investigating Difficult Topics in a Data Structures Course Using Item Response Theory and Logged Data Analysis
Eric Fouh, Mohammed F. Farghally, Sally Hamouda, Kyu Han Koh and Clifford A. Shaffer

32Association rules uncover social triggers of conceptual learning with physical and virtual representations
Martina Rau

40A Comparative Analysis of Techniques for Predicting Student Performance
Hana Bydžovská

41Analysing and Refining Pilot Training
Bruno Emond, Scott Buffett, Cyril Goutte and Jaff Guo

43Automatic Assessment of Constructed Response Data in a Chemistry Tutor
Scott Crossley, Kris Kyle, Jodi Davenport and Danielle McNamara

48Transactivity as a Predictor of Future Collaborative Knowledge Integration in Team-Based Learning in Online Courses
Miaomiao Wen, Keith Maki, Xu Wang and Carolyn Rose

51Classifying behavior to elucidate elegant problem solving in an educational game
Laura Malkiewich, Ryan S. Baker, Valerie Shute, Shimin Kai and Luc Paquette

52Individualizing Bayesian Knowledge Tracing Models. Are Skills More Important Than Students?
Michael Yudelson

53Validating Game-based Measures of Implicit Science Learning
Elizabeth Rowe, Jodi Asbell-Clarke, Michael Eagle, Andrew Hicks, Tiffany Barnes, Rebecca Brown and Teon Edwards

54Automatic Detection of Teacher Questions from Audio in Live Classrooms
Nathaniel Blanchard, Patrick Donnelly, Andrew Olney, Borhan Samei, Sean Kelly, Xiaoyi Sun, Brooke Ward, Martin Nystrand and Sidney D'Mello

56A Nonlinear State Space Model for Identifying At-Risk Students in Open Online Courses
Feng Wang and Li Chen

61Deep Learning + Student Modeling + Clustering: a Recipe for Effective Automatic Answer Grading
Yuan Zhang, Rajat Shah and Min Chi

67Document Segmentation for Labeling with Academic Learning Objectives
Divyanshu Bhartiya, Danish Contractor, Sovan Biswas, Bikram Sengupta and Mukesh Mohania

69Investigating Swarm Intelligence for Performance Prediction
Mohammad Majid Al-Rifaie, Matthew Yee-King and Mark d'Inverno

70Expediting Support for Social Learning with Behavior Modeling
Yohan Jo, Gaurav Singh Tomar, Oliver Ferschke, Carolyn Rose and Dragan Gasevic

79An Automated Test of Motor Skills for Job Selection and Feedback
Bhanu Pratap Singh Rawat and Varun Aggarwal

83Course Enrollment Recommender System
Hana Bydžovská

84Learning Curves for Problems with Multiple Knowledge Components
Brett van de Sande

85On generalizability of MOOC research
Łukasz Kidziński, Kshitij Sharma, Mina Shirvani Boroujeni and Pierre Dillenbourg

90Investigating Gender Difference on Homework in Middle School Mathematics
Mingyu Feng, Jeremy Roschelle, Craig Mason and Ruchi Bhanot

101Exploring Learning Management System Interaction Data: Combining Data-driven and Theory-driven Approaches
Hongkyu Choi, Ji Eun Lee, Won-Joon Hong, Kyumin Lee, Mimi Recker and Andy Walker

104Modeling Visitor Behavior in a Game-Based Engineering Museum Exhibit with Hidden Markov Models
Mike Tissenbaum, Matthew Berland and Vishesh Kumar

109Topic-wise Classification of MOOC Discussions: A Visual Analytics Approach
Thushari Atapattu, Katrina Falkner and Hamid Tarmazdi

110Predicting Dialogue Acts for Intelligent Virtual Agents with Multimodal Student Interaction Data
Wookhee Min, Joseph Wiggins, Lydia Pezzullo, Alexandria Vail, Kristy Elizabeth Boyer, Bradford Mott, Megan Frankosky, Eric Wiebe and James Lester

112Semi-Markov model for simulating MOOC students
Louis Faucon, Łukasz Kidziński and Pierre Dillenbourg

113Assessing Student-Generated Design Justifications in Virtual Engineering Internships
Vasile Rus, Dipesh Gautam, Zach Swiecki, David Shaffer and Art Graesser

125Exploring the Impact of Data-driven Tutoring Methods on Students' Demonstrative Knowledge in Logic Problem Solving
Behrooz Mostafavi and Tiffany Barnes

131Choosing versus Receiving Feedback: The Impact of Feedback Valence on Learning in an Assessment Game
Maria Cutumisu and Daniel L. Schwartz

133Going Deeper with Deep Knowledge Tracing
Xiaolu Xiong, Siyuan Zhao, Eric Vaninwegen and Joseph Beck

134Boosted Decision Tree for Q-matrix Refinement
Peng Xu and Michel Desmarais

135Aim Low: Correlation-based Feature Selection for Model-based Reinforcement Learning
Shitian Shen and Min Chi

136Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCs
Ben Gelman, Matt Revelle, Carlotta Domeniconi, Kalyan Veeramachaneni and Aditya Johri

139Beyond Log Files: Using Multi-Modal Data Streams Towards Data-Driven KC Model Improvement
Ran Liu, Jodi Davenport and John Stamper

142Student Emotion, Co-occurrence, and Dropout in a MOOC Context
John Dillon, Nigel Bosch, Malolan Chetlur, Nirandika Wanigasekara, G. Alex Ambrose, Bikram Sengupta and Sidney D'Mello

145Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation
Kevin Wilson, Yan Karklin, Bojian Han and Chaitanya Ekanadham

146Robust Predictive Models on MOOCs : Transferring Knowledge across Courses
Sebastien Boyer and Kalyan Veeramachaneni

149Data-driven Automated Induction of Prerequisite Structure Graphs
Devendra Singh Chaplot, Yiming Yang, Jaime Carbonell and Kenneth R. Koedinger

150Tensor Factorization for Student Modeling and Performance Prediction in Unstructured Domain
Shaghayegh Sahebi, Yu-Ru Lin and Peter Brusilovsky

151Seeking Programming-related Information from Large Scaled Discussion Forums, Help or Harm?
Yihan Lu and Sharon Hsiao

152Closing the Loop with Quantitative Cognitive Task Analysis
Kenneth Koedinger and Elizabeth Mclaughlin

166Hint Availability Slows Completion Times in Summer Work
Paul Salvador Inventado, Peter Scupelli, Eric Van Inwegen, Korinn Ostrow, Neil Heffernan III, Ryan Baker, Stefan Slater, Mia Almeda and Jaclyn Ocumpaugh

167Modeling Interactions Across Skills: A Method to Construct and Compare Models Predicting the Existence of Skill Relationships
Anthony F. Botelho, Seth Adjei and Neil Heffernan

169Course Content Analysis: An Initiative Step toward Learning Object Recommendation Systems for MOOC Learners
Yiling Dai, Yasuhito Asano and Masatoshi Yoshikawa

171Does a Peer Recommender Foster Students' Engagement in MOOCs?
Hugues Labarthe, Francois Bouchet, Remi Bachelet and Kalina Yacef

173How Good Is Popularity? Summary Grading in Crowdsourcing
Haiying Li, Zhiqiang Cai and Art Graesser

175Personalization of Learning Trajectories in Online Communities of Creators
Mingxuan Sun and Seungwon Yang

Posters (51)

1Applicability of Educational Data Mining in Afghanistan Opportunities and Challenges
Abdul Rahman Sherzad

9Meta-learning for predicting the best vote aggregation method: Case study in collaborative searching of LOs
Alfredo Zapata González, Victor Menendez, Cristobal Romero and Manuel E. Prieto Méndez

14Generating Semantic Concept Map for MOOCs
Zhuoxuan Jiang, Peng Li, Yan Zhang and Xiaoming Li

19Q-matrix Learning and DINA Model Parameter Estimation
Yuan Sun, Shiwei Ye and Yi Sun

34Hierarchical Cluster Analysis Heatmaps and Pattern Analysis: An Approach for Visualizing Learning Management System Interaction Data
Ji Eun Lee, Mimi Recker, Alex Bowers and Min Yuan

37Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC Data
Nicholas Diana, Michael Eagle, John Stamper and Kenneth Koedinger

47Predicting STEM Achievement with Learning Management System Data: Prediction Modeling and a Test of an Early Warning System
Michelle Dominguez, Matthew Bernacki and Merlin Uesbeck

55Diagnosis at Scale: Detecting the Expertise Level and Knowledge States of Lifelong Professional Learners
Oluwabukola Ishola and Gord McCalla

66How quickly can wheel spinning be detected?
Noboru Matsuda, Sanjay Chandrasekaran and John Stamper

71Portrait of an Indexer - Computing Pointers Into Instructional Videos
Andrew Lamb, Jose Hernandez, Jeffrey Ullman and Andreas Paepcke

72Time Series Analysis of VLE Activity Data
Ewa Mlynarska, Pádraig Cunningham and Derek Greene

74Equity of Learning Opportunities in Chicago City of Learning
David Quigley, Ogheneovo Dibie, Arafat Sultan, Katie Van Horne, William R. Penuel, Tamara Sumner, Ugochi Acholonu and Nichole Pinkard

80Toward Revision-Sensitive Feedback in Automated Writing Evaluation
Rod Roscoe, Matthew Jacovina, Laura Allen, Adam Johnson and Danielle McNamara

81Novel features for capturing cooccurrence behavior in dyadic collaborative problem solving tasks
Vikram Ramanarayanan and Saad Khan

93Time-series cross-section method for monitoring students’ page views of course materials and improving classroom teaching
Konomu Dobashi

94How employment constrains participation in MOOCs?
Mina Shirvani Boroujeni, Łukasz Kidziński and Pierre Dillenbourg

95Automated Feedback on the Quality of Collaborative Processes: An Experience Report
Marcela Borge and Carolyn Rosé

96Mining Sequences of Gameplay for Embedded Assessment in Collaborative Learning
Philip Buffum, Megan Frankosky, Kristy Boyer, Eric Wiebe, Bradford Mott and James Lester

98Toward Automated Support for Teacher-Facilitated Formative Feedback on Student Writing
Jennifer Sabourin, Lucy Kosturko, Kristin Hoffmann and Scott Mcquiggan

102Identifying relevant user behavior and predicting learning and persistence in an ITS-based afterschool program
Scotty Craig, Xudong Huang, Jun Xie, Ying Fang and Xiangen Hu

103TutorSpace: Content-centric Platform for Enabling Blended Learning in Developing Countries
Kuldeep Yadav, Kundan Shrivastava, Ranjeet Kumar, Saurabh Srivastava and Om Deshmukh

105Exploring Social Influence on the Usage of Resources in an Online Learning Community
Ogheneovo Dibie, Tamara Sumner and Keith Maull

106How Long Must We Spin Our Wheels? Analysis of Student Time and Classifier Inaccuracy
Yan Wang, Yue Gong and Joseph Beck

115Comparison of Selection Criteria for Multi-Feature Hierarchical Activity Mining in Open Ended Learning Environments
Yi Dong, John S. Kinnebrew and Gautam Biswas

116Perfect Scores Indicate Good Students !? The Case of One Hundred Percenters in a Math Learning System
Zhilin Zheng, Martin Stapel and Niels Pinkwart

117Can We Rely on Reliability? Testing the assumptions of inter-rater reliability
Brendan Eagan, Bradley Rogers, Ronald Serlin, Andrew Ruis, Golnaz Arastoopour and David Williamson Shaffer

119Stimulating collaborative activity in online social learning environments with Markov decision processes
Matthew Yee-King and Mark D'Inverno

120Predicting student grades from online, collaborative social learning metrics using KNN
Matthew Yee-King and Mark D'Inverno

124Can Word Probabilities from LDA be Simply Added up to Represent Documents?
Zhiqiang Cai, Haiying Li, Xiangen Hu and Art Graesser

127Learning curves versus problem difficulty: an analysis of the Knowledge Component picture for a given context
Brett van de Sande

128Redefining "What" in Analyses of Who Does What in MOOCs
Alok Baikadi, Carrie Demmans Epp, Yanjin Long and Christian Schunn

130Discovering 'Tough Love' Interventions Despite Dropout
Joseph Jay Williams, Anthony Botelho, Adam Sales, Neil Heffernan and Charles Lang

141Identifying Student Behaviors Early in the Term for Improving Online Course Performance
Makoto Mori and Philip Chan

156Text Classification of Student Self-Explanations in College Physics Questions
Sameer Bhatnagar, Michel Desmarais, Nathaniel Lasry and Elizabeth Charles

157Anonymization versus Information in Data Sharing: a Case Study in Fine-grained Keystroke Data
Juho Leinonen, Petri Ihantola and Arto Vihavainen

163A Data-Driven Framework of Modeling Skill Combinations for Deeper Knowledge Tracing
Yun Huang, Julio Guerra and Peter Brusilovsky

165Adding Eye-Tracking Data to Models of Representational Competencies Does Not Improve Prediction Accuracy
Martina Rau and Zach Pardos

168Guiding Students Towards Frequent High-Utility Paths in an Ill-Defined Domain
Igor Jugo, Božidar Kovačić and Vanja Slavuj

170Deep & Shallow Modelling of Student Behavior in a MOOC
Steven Tang, Joshua Peterson and Zachary Pardos

174Soft Clustering of Physics Misconceptions Using a Mixed Membership Model
April Galyardt, Seohyun Kim, Guoguo Zheng and Yanyan Tan

181Understanding Engagement in MOOCs
Qiujie Li and Rachel Baker

183Browsing-Skill Mining from e-Book Logs with Non-negative Matrix Factorization
Atsushi Shimada, Fumiya Okubo and Hiroaki Ogata

184Study on Automatic Scoring of Descriptive Type Tests using Text Similarity Calculations
Izuru Nogaito, Keiji Yasuda and Hiroaki Kimura

185How to Judge Learning on Online Learning: Minimum Learning Judgment System
Jaechoon Jo and Heuiseok Lim

186Preliminary Results On Dialogue Act and Subact Classification in Chat-based Online Tutorial Dialogues
Vasile Rus, Donald Morrison, Rajendra Banjade, Nabin Maharjan and Steve Ritter

188Validating Automated Triggers and Notifications @ Scale in Blackboard Learn
John Whitmer, Aleksander Dietrichson and Bryan O'Haver

189Toward Integrating Human and Automated Tutoring Systems
Steven Ritter, Michael Yudelson, Stephen Fancsali and Susan Berman

190Quantifying How Students Use an Online Learning System: A Focus on Transitions and Performance
Erica Snow, Andrew Krumm, Timothy Podkul, Mingyu Feng and Alex Bowers

193Examining the necessity of problem diagrams using MOOC AB experiments.
Zhongzhou Chen, Neset Demirci and David Pritchard

195Exploring and Following Students' Strategies When Completing Their Weekly Tasks
Jessica McBroom, Bryn Jeffries, Irena Koprinska and Kalina Yacef

203Educational Technology: What 49 Schools Discovered about Usage when the Data were Uncovered
Daniel Stanhope

Demos (2)

187MATHia X: The Next Generation Cognitive Tutor
Steven Ritter and Stephen Fancsali

202A Platform for Integrating and Analyzing Data to Evaluate the Impacts of Educational Technologies
Daniel Stanhope and Joyce Yu

Tutorials (2)

180SAS Tools for Educational Data Mining
Jennifer Sabourin, Scott Mcquiggan and André De Waal

194Massively Scalable EDM with Spark
Tristan Nixon

Doctoral Consortium (6)

179Towards the Understanding of Gestures and Vocalization Coordination in Teaching Context
Roghayeh Barmaki

192Predicting Off-task Behaviors for Adaptive Vocabulary Learning System
Sungjin Nam

196Towards Modeling Chunks in a Knowledge Tracing Framework for Students’ Deep Learning
Yun Huang and Peter Brusilovsky

197Estimation of prerequisite skills model from large scale assessment data using semantic data mining
Bruno Penteado

199Using Case-Based Reasoning to Automatically Generate High-Quality Feedback for Programming Exercises
Angelo Kyrilov

201Designing Interactive and Personalized Concept Mapping Learning Environments
Shang Wang