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ORCID9th EDM 2016: Raleigh, NC, USA
- Tiffany Barnes, Min Chi, Mingyu Feng:
Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016, Raleigh, North Carolina, USA, June 29 - July 2, 2016. International Educational Data Mining Society (IEDMS) 2016
Best paper
- Mohammad Khajah, Robert V. Lindsey, Michael Mozer:
How Deep is Knowledge Tracing?
Best student paper
- Igor Labutov, Christoph Studer:
Calibrated Self-Assessment.
Best paper nominees
- Arjun Sharma, Arijit Biswas, Ankit Gandhi, Sonal Patil, Om Deshmukh:
LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos. 215-222 - Martina A. Rau, Blake Mason, Robert D. Nowak:
How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual Representations. 199-206 - Andrew Hicks, Zhongxiu Liu, Michael Eagle, Tiffany Barnes:
Measuring Gameplay Affordances of User-Generated Content in an Educational Game. 78-85
Invited Talks
- Rakesh Agrawal:
Data-Driven Education: Some opportunities and Challenges. 2 - Marcia C. Linn:
WISE Ways to Strengthen Inquiry Science Learning. 3 - Judy Kay:
Enabling people to harness and control EDM for lifelong, life-wide learning. 4
JEDM Track Journal Papers
- Rakesh Agrawal, Behzad Golshan, Evangelos E. Papalexakis:
Toward Data-Driven Design of Educational Courses: A Feasibility Study. 6 - Mack Sweeney, Jaime Lester, Huzefa Rangwala, Aditya Johri:
Next-Term Student Performance Prediction: A Recommender Systems Approach. 7 - Diyi Yang, Robert E. Kraut, Carolyn P. Rosé:
Exploring the Effect of Student Confusion in Massive Open Online Courses. 8
Invited Paper
- Judy Kay:
Enabling people to harness and control EDM for lifelong, life-wide learning. 10-20
Full Papers
- Laura K. Allen, Matthew E. Jacovina, Mihai Dascalu, Rod D. Roscoe, Kevin Kent, Aaron D. Likens, Danielle S. McNamara:
{ENTER}ing the Time Series {SPACE}: Uncovering the Writing Process through Keystroke Analyses. 22-29 - Caitlin Mills, Robert Bixler, Xinyi Wang, Sidney K. D'Mello:
Automatic Gaze-Based Detection of Mind Wandering during Film Viewing. 30-37 - Lujie Chen, Xin Li, Zhuyun Xia, Zhanmei Song, Louis-Philippe Morency, Artur Dubrawski:
Riding an emotional roller-coaster: A multimodal study of young child's math problem solving activities. 38-45 - Yetian Chen, José P. González-Brenes, Jin Tian:
Joint Discovery of Skill Prerequisite Graphs and Student Models. 46-53 - Dan Davis, Guanliang Chen, Claudia Hauff, Geert-Jan Houben:
Gauging MOOC Learners' Adherence to the Designed Learning Path. 54-61 - Luca de Alfaro, Michael Shavlovsky:
Dynamics of Peer Grading: An Empirical Study. 62-69 - Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill:
Sequence Matters, But How Exactly? A Method for Evaluating Activity Sequences from Data. 70-77 - Andrew Hicks, Zhongxiu Liu, Michael Eagle, Tiffany Barnes:
Measuring Gameplay Affordances of User-Generated Content in an Educational Game. 78-85 - Stephen Hutt, Caitlin Mills, Shelby White, Patrick J. Donnelly, Sidney K. D'Mello:
The Eyes Have It: Gaze-based Detection of Mind Wandering during Learning with an Intelligent Tutoring System. 86-93 - Mohammad Khajah, Robert V. Lindsey, Michael Mozer:
How Deep is Knowledge Tracing? - Severin Klingler, Tanja Käser, Barbara Solenthaler, Markus H. Gross:
Temporally Coherent Clustering of Student Data. 102-109 - Igor Labutov, Hod Lipson:
Web as a textbook: Curating Targeted Learning Paths through the Heterogeneous Learning Resources on the Web. 110-118 - Igor Labutov, Christoph Studer:
Calibrated Self-Assessment. - Zhongxiu Liu, Rebecca Brown, Collin F. Lynch, Tiffany Barnes, Ryan S. Baker, Yoav Bergner, Danielle S. McNamara:
MOOC Learner Behaviors by Country and Culture; an Exploratory Analysis. 127-134 - Yijun Ma, Lalitha Agnihotri, Ryan S. Baker, Shirin Mojarad:
Effect of student ability and question difficulty on duration. 135-142 - Jaclyn K. Maass, Philip I. Pavlik Jr.:
Modeling the Influence of Format and Depth during Effortful Retrieval Practice. 143-150 - Christopher J. MacLellan, Erik Harpstead, Rony Patel, Kenneth R. Koedinger:
The Apprentice Learner architecture: Closing the loop between learning theory and educational data. 151-158 - Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
Mining behaviors of students in autograding submission system logs. 159-166 - Kelvin H. R. Ng, Kevin Hartman, Kai Liu, Andy W. H. Khong:
Modelling the way: Using action sequence archetypes to differentiate learning pathways from learning outcomes. 167-174 - Ke Niu, Zhendong Niu, Xiangyu Zhao, Can Wang, Kai Kang, Min Ye:
A Coupled User Clustering Algorithm for Web-based Learning Systems. 175-182 - Benjamin Paaßen, Joris Jensen, Barbara Hammer:
Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming. 183-190 - Thomas W. Price, Yihuan Dong, Tiffany Barnes:
Generating Data-driven Hints for Open-ended Programming. 191-198 - Martina A. Rau, Blake Mason, Robert D. Nowak:
How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual Representations. 199-206 - Adam Sales, Asa Wilks, John Pane:
Student Usage Predicts Treatment Effect Heterogeneity in the Cognitive Tutor Algebra I Program. 207-214 - Arjun Sharma, Arijit Biswas, Ankit Gandhi, Sonal Patil, Om Deshmukh:
LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos. 215-222 - Stefan Slater, Jaclyn Ocumpaugh, Ryan S. Baker, Peter Scupelli, Paul Salvador Inventado, Neil T. Heffernan:
Semantic Features of Math Problems: Relationships to Student Learning and Engagement. 223-230 - Martin Stapel, Zhilin Zheng, Niels Pinkwart:
An Ensemble Method to Predict Student Performance in an Online Math Learning Environment. 231-238 - Sabina Tomkins, Arti Ramesh, Lise Getoor:
Predicting Post-Test Performance from Student Behavior: A High School MOOC Case Study. 239-246 - Alexandria Katarina Vail, Joseph B. Wiggins, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C. Lester:
The Affective Impact of Tutor Questions: Predicting Frustration and Engagement. 247-254 - Linting Xue, Collin F. Lynch, Min Chi:
Unnatural Feature Engineering: Evolving Augmented Graph Grammars for Argument Diagrams. 255-262
Short Papers
- Mohammad Majid al-Rifaie, Matthew Yee-King, Mark d'Inverno:
Investigating Swarm Intelligence for Performance Prediction. 264-269 - Michael Mogessie Ashenafi, Marco Ronchetti, Giuseppe Riccardi:
Predicting Student Progress from Peer-Assessment Data. 270-275 - Thushari Atapattu, Katrina Falkner, Hamid Tarmazdi:
Topic-wise Classification of MOOC Discussions: A Visual Analytics Approach. 276-281 - Divyanshu Bhartiya, Danish Contractor, Sovan Biswas, Bikram Sengupta, Mukesh K. Mohania:
Document Segmentation for Labeling with Academic Learning Objectives. 282-287 - Nathaniel Blanchard, Patrick J. Donnelly, Andrew Olney, Borhan Samei, Sean Kelly, Xiaoyi Sun, Brooke Ward, Martin Nystrand, Sidney K. D'Mello:
Semi-Automatic Detection of Teacher Questions from Human-Transcripts of Audio in Live Classrooms. 288-291 - Anthony F. Botelho, Seth Adjei, Neil T. Heffernan:
Modeling Interactions Across Skills: A Method to Construct and Compare Models Predicting the Existence of Skill Relationships. 292-297 - Sebastien Boyer, Kalyan Veeramachaneni:
Robust Predictive Models on MOOCs : Transferring Knowledge across Courses. 298-305 - Hana Bydzovská:
A Comparative Analysis of Techniques for Predicting Student Performance. 306-311 - Hana Bydzovská:
Course Enrollment Recommender System. 312-317 - Devendra Singh Chaplot, Yiming Yang, Jaime G. Carbonell, Kenneth R. Koedinger:
Data-driven Automated Induction of Prerequisite Structure Graphs. 318-323 - Hongkyu Choi, Ji Eun Lee, Won-Joon Hong, Kyumin Lee, Mimi Recker, Andy Walker:
Exploring Learning Management System Interaction Data: Combining Data-driven and Theory-driven Approaches. 324-329 - Benjamin Clement, Pierre-Yves Oudeyer, Manuel Lopes:
A Comparison of Automatic Teaching Strategies for Heterogeneous Student Populations. 330-335 - Scott A. Crossley, Kris Kyle, Jodi L. Davenport, Danielle S. McNamara:
Automatic Assessment of Constructed Response Data in a Chemistry Tutor. 336-340 - Maria Cutumisu, Daniel L. Schwartz:
Choosing versus Receiving Feedback: The Impact of Feedback Valence on Learning in an Assessment Game. 341-346 - Yiling Dai, Yasuhito Asano, Masatoshi Yoshikawa:
Course Content Analysis: An Initiative Step toward Learning Object Recommendation Systems for MOOC Learners. 347-352 - John Z. Dillon, Nigel Bosch, Malolan Chetlur, Nirandika Wanigasekara, G. Alex Ambrose, Bikram Sengupta, Sidney K. D'Mello:
Student Emotion, Co-occurrence, and Dropout in a MOOC Context. 353-357 - Louis Faucon, Lukasz Kidzinski, Pierre Dillenbourg:
Semi-Markov model for simulating MOOC students. 358-363 - Mingyu Feng, Jeremy Roschelle, Craig Mason, Ruchi Bhanot:
Investigating Gender Difference on Homework in Middle School Mathematics. 364-369 - Eric Fouh, Mohammed F. Farghally, Sally Hamouda, Kyu Han Koh, Clifford A. Shaffer:
Investigating Difficult Topics in a Data Structures Course Using Item Response Theory and Logged Data Analysis. 370-375 - Ben U. Gelman, Matt Revelle, Carlotta Domeniconi, Kalyan Veeramachaneni, Aditya Johri:
Acting the Same Differently: A Cross-Course Comparison of User Behavior in MOOCs. 376-381 - Jiangang Hao, Lei Liu, Alina von Davier, Patrick C. Kyllonen, Christopher Kitchen:
Collaborative Problem Solving Skills versus Collaboration Outcomes: Findings from Statistical Analysis and Data Mining. 382-387 - Paul Salvador Inventado, Peter Scupelli, Eric Van Inwegen, Korinn Ostrow, Neil Thomas Heffernan III, Jaclyn Ocumpaugh, Ryan S. Baker, Stefan Slater, Mia Almeda:
Hint Availability Slows Completion Times in Summer Work. 388-393 - Yuheng Helen Jiang, Lukasz Golab:
On Competition for Undergraduate Co-op Placements: A Graph Mining Approach. 394-399 - Yohan Jo, Gaurav Tomar, Oliver Ferschke, Carolyn P. Rosé, Dragan Gasevic:
Expediting Support for Social Learning with Behavior Modeling. 400-405 - Lukasz Kidzinski, Kshitij Sharma, Mina Shirvani Boroujeni, Pierre Dillenbourg:
On generalizability of MOOC models. 406-411 - Kenneth R. Koedinger, Elizabeth A. McLaughlin:
Closing the Loop with Quantitative Cognitive Task Analysis. 412-417 - Hugues Labarthe, François Bouchet, Rémi Bachelet, Kalina Yacef:
Does a Peer Recommender Foster Students' Engagement in MOOCs? 418-423 - Andrew S. Lan, Richard G. Baraniuk:
A Contextual Bandits Framework for Personalized Learning Action Selection. 424-429 - Haiying Li, Zhiqiang Cai, Arthur C. Graesser:
How Good Is Popularity? Summary Grading in Crowdsourcing. 430-435 - Ran Liu, Jodi L. Davenport, John C. Stamper:
Beyond Log Files: Using Multi-Modal Data Streams Towards Data-Driven KC Model Improvement. 436-441 - Yihan Lu, Sharon I-Han Hsiao:
Seeking Programming-related Information from Large Scaled Discussion Forums, Help or Harm? 442-447 - Laura J. Malkiewich, Ryan S. Baker, Valerie Shute, Shiming Kai, Luc Paquette:
Classifying behavior to elucidate elegant problem solving in an educational game. 448-453 - Wookhee Min, Joseph B. Wiggins, Lydia Pezzullo, Alexandria Katarina Vail, Kristy Elizabeth Boyer, Bradford W. Mott, Megan Frankosky, Eric N. Wiebe, James C. Lester:
Predicting Dialogue Acts for Intelligent Virtual Agents with Multimodal Student Interaction Data. 454-459 - Behrooz Mostafavi, Tiffany Barnes:
Exploring the Impact of Data-driven Tutoring Methods on Students' Demonstrative Knowledge in Logic Problem Solving. 460-465 - Radek Pelánek, Jirí Rihák:
Properties and Applications of Wrong Answers in Online Educational Systems. 466-471 - Anna N. Rafferty, Rachel Jansen, Thomas L. Griffiths:
Using Inverse Planning for Personalized Feedback. 472-477 - Martina A. Rau:
Pattern mining uncovers social prompts of conceptual learning with physical and virtual representations. 478-483 - Zhiyun Ren, Huzefa Rangwala, Aditya Johri:
Predicting Performance on MOOC Assessments using Multi-Regression Models. 484-489 - Elizabeth Rowe, Jodi Asbell-Clarke, Michael Eagle, Andrew Hicks, Tiffany Barnes, Rebecca Brown, Teon Edwards:
Validating Game-based Measures of Implicit Science Learning. 490-495 - Vasile Rus, Dipesh Gautam, Zach Swiecki, David W. Shaffer, Art Graesser:
Assessing Student-Generated Design Justifications in Virtual Engineering Internships. 496-501 - Shaghayegh Sahebi, Yu-Ru Lin, Peter Brusilovsky:
Tensor Factorization for Student Modeling and Performance Prediction in Unstructured Domain. 502-506 - Shitian Shen, Min Chi:
Aim Low: Correlation-based Feature Selection for Model-based Reinforcement Learning. 507-512 - Mingxuan Sun, Seungwon Yang:
Personalization of Learning Paths in Online Communities of Creators. 513-516 - Michael Tissenbaum, Matthew Berland, Vishesh Kumar:
Modeling Visitor Behavior in a Game-Based Engineering Museum Exhibit with Hidden Markov Models. 517-522 - Brett van de Sande:
Learning Curves for Problems with Multiple Knowledge Components. 523-526 - Feng Wang, Li Chen:
A Nonlinear State Space Model for Identifying At-Risk Students in Open Online Courses. 527-532 - Miaomiao Wen, Keith Maki, Xu Wang, Steven Dow, James D. Herbsleb, Carolyn P. Rosé:
Transactivity as a Predictor of Future Collaborative Knowledge Integration in Team-Based Learning in Online Courses. 533-538 - Kevin H. Wilson, Yan Karklin, Bojian Han, Chaitanya Ekanadham:
Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation. 539-544 - Xiaolu Xiong, Siyuan Zhao, Eric Van Inwegen, Joseph Beck:
Going Deeper with Deep Knowledge Tracing. 545-550 - Peng Xu, Michel C. Desmarais:
Boosted Decision Tree for Q-matrix Refinement. 551-555 - Michael Yudelson:
Individualizing Bayesian Knowledge Tracing. Are Skill Parameters More Important Than Student Parameters? 556-561 - Yuan Zhang, Rajat Shah, Min Chi:
Deep Learning + Student Modeling + Clustering: a Recipe for Effective Automatic Short Answer Grading. 562-567
Posters and Demo
- Alok Baikadi, Carrie Demmans Epp, Yanjin Long, Christian Schunn:
Redefining "What" in Analyses of Who Does What in MOOCs. 569-570 - Sameer Bhatnagar, Michel C. Desmarais, Nathaniel Lasry, Elizabeth S. Charles:
Text Classification of Student Self-Explanations in College Physics Questions. 571-572 - Marcela Borge, Carolyn P. Rosé:
Automated Feedback on the Quality of Collaborative Processes: An Experience Report. 573-574 - Philip Sheridan Buffum, Megan Frankosky, Kristy Elizabeth Boyer, Eric N. Wiebe, Bradford W. Mott, James C. Lester:
Mining Sequences of Gameplay for Embedded Assessment in Collaborative Learning. 575-576 - Zhiqiang Cai, Haiying Li, Xiangen Hu, Art Graesser:
Can Word Probabilities from LDA be Simply Added up to Represent Documents? 577-578 - Zhongzhou Chen, Neset Demirci, David E. Pritchard:
Examining the necessity of problem diagrams using MOOC AB experiments. 579-580 - Scotty D. Craig, Xudong Huang, Jun Xie, Ying Fang, Xiangen Hu:
Identifying relevant user behavior and predicting learning and persistence in an ITS-based afterschool program. 581-582 - Nicholas Diana, Michael Eagle, John C. Stamper, Kenneth R. Koedinger:
Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC Data. 583-584 - Ogheneovo Dibie, Tamara Sumner, Keith E. Maull, David Quigley:
Exploring Social Influence on the Usage of Resources in an Online Learning Community. 585-586 - Konomu Dobashi:
Time Series Cross Section method for monitoring students' page views of course materials and improving classroom teaching. 587-588 - Michelle Dominguez, Matthew L. Bernacki, Phillip Merlin Uesbeck:
Predicting STEM Achievement with Learning Management System Data: Prediction Modeling and a Test of an Early Warning System. 589-590 - Yi Dong, John S. Kinnebrew, Gautam Biswas:
Comparison of Selection Criteria for Multi-Feature Hierarchical Activity Mining in Open Ended Learning Environments. 591-592 - Yun Huang, Julio Guerra, Peter Brusilovsky:
A Data-Driven Framework of Modeling Skill Combinations for Deeper Knowledge Tracing. 593-594 - Zhuoxuan Jiang, Peng Li, Yan Zhang, Xiaoming Li:
Generating Semantic Concept Map for MOOCs. 595-596 - Jaechoon Jo, Heuiseok Lim:
How to Judge Learning on Online Learning: Minimum Learning Judgment System. 597-598 - Igor Jugo, Bozidar Kovacic, Vanja Slavuj:
Guiding Students Towards Frequent High-Utility Paths in an Ill-Defined Domain. 599-600 - Andrew Lamb, Jose Hernandez, Jeffrey D. Ullman, Andreas Paepcke:
Portrait of an Indexer - Computing Pointers Into Instructional Videos. 601-602 - Ji Eun Lee, Mimi Recker, Alex J. Bowers, Min Yuan:
Hierarchical Cluster Analysis Heatmaps and Pattern Analysis: An Approach for Visualizing Learning Management System Interaction Data. 603-604 - Qiujie Li, Rachel Baker:
Understanding Engagement in MOOCs. 605-606 - Noboru Matsuda, Sanjay Chandrasekaran, John C. Stamper:
How quickly can wheel spinning be detected? 607-608 - Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
Exploring and Following Students' Strategies When Completing Their Weekly Tasks. 609-610 - Makoto Mori, Philip Chan:
Identifying Student Behaviors Early in the Term for Improving Online Course Performance. 611-612 - Ewa Mlynarska, Pádraig Cunningham, Derek Greene:
Time Series Analysis of VLE Activity Data. 613-614 - Tristan Nixon:
Massively Scalable EDM with Spark. 615 - Izuru Nogaito, Keiji Yasuda, Hiroaki Kimura:
Study on Automatic Scoring of Descriptive Type Tests using Text Similarity Calculations. 616-617 - David Quigley, Ogheneovo Dibie, Md. Arafat Sultan, Katie Van Horne, William R. Penuel, Tamara Sumner, Ugochi Acholonu, Nichole Pinkard:
Equity of Learning Opportunities in the Chicago City of Learning Program. 618-619 - Vikram Ramanarayanan, Saad Khan:
Novel features for capturing cooccurrence behavior in dyadic collaborative problem solving tasks. 620-621 - Martina A. Rau, Zachary A. Pardos:
Adding eye-tracking AOI data to models of representation skills does not improve prediction accuracy. 622-623 - Steven Ritter, Stephen Fancsali:
MATHia X: The Next Generation Cognitive Tutor. 624-625 - Steven Ritter, Michael Yudelson, Stephen Fancsali, Susan R. Berman:
Towards Integrating Human and Automated Tutoring Systems. 626-627 - Rod D. Roscoe, Matthew E. Jacovina, Laura K. Allen, Adam C. Johnson, Danielle S. McNamara:
Toward Revision-Sensitive Feedback in Automated Writing Evaluation. 628-629