Table of Contents

• Social Information DiscoveryBarry Smyth. 3 [doi]
• On Exploration and Mining of Data in Educational PracticeErik-Jan van der Linden. 5 [doi]
• EDM and the 4th Paradigm of Scientific Discovery - Reflections on KDD Cup 2010John C. Stamper. 7 [doi]
• Factorization Models for Forecasting Student PerformanceNguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme. 11-20 [doi]
• Analyzing Participation of Students in Online Courses Using Social Network Analysis TechniquesReihaneh Rabbany, Mansoureh Takaffoli, Osmar R. Zaïane. 21-30 [doi]
• A Machine Learning Approach for Automatic Student Model DiscoveryNan Li, William W. Cohen, Kenneth R. Koedinger, Noboru Matsuda. 31-40 [doi]
• Conditions for Effectively Deriving a Q-Matrix from Data with Non-negative Matrix Factorization. Best Paper AwardMichel Desmarais. 41-50 [doi]
• Student Translations of Natural Language into Logic: The Grade Grinder Translation Corpus Release 1.0Dave Barker-Plummer, Richard Cox, Robert Dale. 51-60 [doi]
• Instructional Factors Analysis: A Cognitive Model For Multiple Instructional InterventionsMin Chi, Kenneth R. Koedinger, Geoffrey J. Gordon, Pamela W. Jordan, Kurt VanLehn. 61-70 [doi]
• The Simple Location Heuristic is Better at Predicting Students' Changes in Error Rate Over Time Compared to the Simple Temporal HeuristicAdaeze Nwaigwe, Kenneth R. Koedinger. 71-80 [doi]
• Items, Skills, and Transfer Models: Which Really Matters for Student Modeling?Yue Gong, Joseph Beck. 81-90 [doi]
• Avoiding Problem Selection Thrashing with Conjunctive Knowledge TracingKenneth R. Koedinger, Philip I. Pavlik Jr., John C. Stamper, Tristan Nixon, Steven Ritter. 91-100 [doi]
• Less is More: Improving the Speed and Prediction Power of Knowledge Tracing by Using Less DataBahador B. Nooraei, Zachary A. Pardos, Neil T. Heffernan, Ryan Shaun Joazeiro de Baker. 101-110 [doi]
• Analysing Frequent Sequential Patterns of Collaborative Learning Activity Around an Interactive Tabletop. Nominee for Best Paper AwardRoberto Martínez Maldonado, Kalina Yacef, Judy Kay, Ahmed Sulaiman Kharrufa, Ammar Al-Qaraghuli. 111-120 [doi]
• Acquiring Item Difficulty Estimates: a Collaborative Effort of Data and Judgment. Nominee for Best Paper AwardKelly Wauters, Piet Desmet, Wim van den Noortgate. 121-128 [doi]
• Spectral Clustering in Educational Data MiningShubhendu Trivedi, Zachary A. Pardos, Gábor N. Sárközy, Neil T. Heffernan. 129-138 [doi]
• Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge TracingYumeng Qiu, Yingmei Qi, Hanyuan Lu, Zachary A. Pardos, Neil T. Heffernan. 139-148 [doi]
• Learning Classifiers From a Relational Database of Tutor LogsJack Mostow, José P. González-Brenes, Bao Hong (Lucas) Tan. 149-158 [doi]
• A Framework for Capturing Distinguishing User Interaction Behaviors in Novel InterfacesSamad Kardan, Cristina Conati. 159-168 [doi]
• How to Classify Tutorial Dialogue? Comparing Feature Vectors vs. SequencesJosé P. González-Brenes, Jack Mostow, Weisi Duan. 169-178 [doi]
• Automatically Detecting a Student's Preparation for Future Learning: Help Use is KeyRyan Shaun Joazeiro de Baker, Sujith M. Gowda, Albert T. Corbett. 179-188 [doi]
• Ensembling Predictions of Student Post-Test Scores for an Intelligent Tutoring SystemZachary A. Pardos, Sujith M. Gowda, Ryan Shaun Joazeiro de Baker, Neil T. Heffernan. 189-198 [doi]
• Improving Models of Slipping, Guessing, and Moment-By-Moment Learning with Estimates of Skill DifficultySujith M. Gowda, Jonathan P. Rowe, Ryan Shaun Joazeiro de Baker, Min Chi, Kenneth R. Koedinger. 199-208 [doi]
• A Method for Finding Prerequisites Within a CurriculumAnnalies Vuong, Tristan Nixon, Brendon Towle. 211-216 [doi]
• Estimating Prerequisite Structure From Noisy DataEmma Brunskill. 217-222 [doi]
• What Can Closed Sets of Students and Their Marks Say?Dmitry I. Ignatov, Serafima Mamedova, Nikita Romashkin, Ivan Shamshurin. 223-228 [doi]
• How University Entrants are Choosing Their Department? Mining of University Admission Process with FCA TaxonomiesNikita Romashkin, Dmitry I. Ignatov, Elena Kolotova. 229-234 [doi]
• What's an Expert? Using Learning Analytics to Identify Emergent Markers of Expertise through Automated Speech, Sentiment and Sketch AnalysisMarcelo Worsley, Paulo Blikstein. 235-240 [doi]
• Using Logistic Regression to Trace Multiple Sub-skills in a Dynamic Bayes NetYanbo Xu, Jack Mostow. 241-246 [doi]
• Monitoring Learners' Proficiency: Weight Adaptation in the Elo Rating SystemKelly Wauters, Piet Desmet, Wim van den Noortgate. 247-252 [doi]
• Modeling Students' Activity in Online Discussion Forums: A Strategy based on Time Series and Agglomerative Hierarchical ClusteringGermán Cobo, David García-Solórzano, Eugènia Santamaria, Jose Antonio Morán, Javier Melenchón, Carlos Monzo. 253-258 [doi]
• Prediction of Perceived Disorientation in Online Learning Environment with Random Forest RegressionGökhan Akçapinar, Erdal Cosgun, Arif Altun. 259-264 [doi]
• Analyzing Student Spatial Deployment in a Computer LaboratoryVladimir Ivancevic, Milan Celikovic, Ivan Lukovic. 265-270 [doi]
• Predicting School Failure Using Data MiningCarlos Márquez-Vera, Cristóbal Romero, Sebastián Ventura. 271-276 [doi]
• A Dynamical System Model of Microgenetic Changes in Performance, Efficacy, Strategy Use and Value during Vocabulary LearningPhilip I. Pavlik Jr., Sue-mei Wu. 277-282 [doi]
• Desperately Seeking Subscripts: Towards Automated Model ParameterizationJack Mostow, Yanbo Xu, Mdahaduzzaman Munna. 283-288 [doi]
• Automatic Generation of Proof Problems in Deductive LogicBehrooz Mostafavi, Tiffany Barnes, Marvin J. Croy. 289-294 [doi]
• Comparing of Traditional Assessment with Dynamic Testing in a Tutoring SystemMingyu Feng, Neil T. Heffernan, Zachary A. Pardos, Cristina Heffernan. 295-300 [doi]
• Evaluating a Bayesian Student Model of Decimal MisconceptionsGeorge Goguadze, Sergey A. Sosnovsky, Seiji Isotani, Bruce M. McLaren. 301-306 [doi]
• Exploring User Data From a Game-like Math Tutor: A Case Study in Causal ModelingDovan Rai, Joseph Beck. 307-313 [doi]
• Goal Orientation and Changes of Carelessness over Consecutive Trials in Science InquiryArnon Hershkovitz, Ryan Shaun Joazeiro de Baker, Janice D. Gobert, Michael Wixon. 315-316 [doi]
• Towards Improvements on Domain-independent Measurements for Collaborative AssessmentAntonio R. Anaya, Jesus Boticario. 317-318 [doi]
• A Java Desktop Tool for Mining Moodle DataRafael Pedraza Perez, Cristóbal Romero, Sebastián Ventura. 319-320 [doi]
• Using Data Mining in a Recommender System to Search for Learning Objects in RepositoriesAlfredo Zapata Gonzalez, Víctor Hugo Menéndez-Domínguez, Manuel E. Prieto, Cristóbal Romero. 321-322 [doi]
• E-learning Web Miner: A Data Mining Application to Help Instructors Involved in Virtual CoursesDiego García-Saiz, Marta E. Zorrilla. 323-324 [doi]
• Computerized Coding System for Life Narratives to Assess Students' Personality AdaptionQiwei He, Bernard P. Veldkamp, Gerben Westerhof. 325-326 [doi]
• Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring SystemEmma Brunskill, Stuart Russell. 327-328 [doi]
• Mining Teaching Behaviors from Pedagogical SurveysJoana Barracosa, Cláudia Antunes. 329-330 [doi]
• Variable Construction and Causal Modeling of Online Education Messaging Data: Initial ResultsStephen Fancsali. 331-332 [doi]
• The Hospital Classrooms Environments ChallengeCarina S. González, Pedro A. Toledo. 333-334 [doi]
• Combining Study of Complex Network and Text Mining Analysis to Understand Growth Mechanism of Communities on SNSOsamu Yamakawa. 335-336 [doi]
• Logistic Regression in a Dynamic Bayes Net Models Multiple Subskills Better!Yanbo Xu, Jack Mostow. 337-338 [doi]
• Studying the Problem-solving Strategies in the Early Stages of Learning ProgrammingEdgar Cambranes-Martinez, Judith Good. 339-340 [doi]
• Brick: Mining Pedagogically Interesting Sequential PatternsAnjo Anjewierden, Hannie Gijlers, Nadira Saab, Robert de Hoog. 341-342 [doi]
• Intelligent Evaluation of Social Knowledge Building Using Conceptual Maps with MLNLorenzo Moreno, Carina S. González, Román Estévez, Béatrice Pesquet-Popescu. 343-344 [doi]
• Identifying Influence Factors on Students Success by Subgroup DiscoveryFlorian Lemmerich, Marianus Ifland, Frank Puppe. 345-346 [doi]
• Analyzing University Data for Determining Student Profiles and Predicting PerformanceDorina Kabakchieva, Kamelia Stefanova, Valentin S. Kisimov. 347-348 [doi]
• The EDM Vis ToolMatt Johnson, Michael Eagle, Leena Joseph, Tiffany Barnes. 349-350 [doi]
• Towards Modeling Forgetting and Relearning in ITS: Preliminary Analysis of ARRS DataYutao Wang, Neil T. Heffernan. 352 [doi]
• Quality Control and Data Mining Techniques Applied to Monitoring Scaled ScoresAlina Von Davier. 353-354 [doi]
• eLAT: An Exploratory Learning Analytics Tool for Reflection and Iterative Improvement of Technology Enhanced LearningAnna Lea Dyckhoff, Dennis Zielke, Mohamed Amine Chatti, Ulrik Schroeder. 355-356 [doi]
• Predicting Graduate-level Performance from Undergraduate AchievementsJudith Zimmermann, Kay Henning Brodersen, Jean-Philippe Pellet, Elias August, Joachim M. Buhmann. 357-358 [doi]
• Mining Assessment and Teaching Evaluation Data of Regular, Advanced Stream StudentsIrena Koprinska. 359-360 [doi]
• Investigating Usage of Resources in LMS with Specific Association RulesAgathe Merceron. 361-362 [doi]
• Towards Parameter-free Data Mining: Mining Educational Data with YacareeMarta E. Zorrilla, Diego García-Saiz, José L. Balcázar. 363-364 [doi]
• Factors Impacting Novice Code Comprehension in a Tutor for Introductory Computer ScienceLeigh Ann Sudol-DeLyser, Jonathan Steinhart. 365-366 [doi]
• Investigating the Transitions between Learning and Non-learning Activities as Students Learn OnlinePaul Salvador Inventado, Roberto S. Legaspi, Merlin Suarez, Masayuki Numao. 367-368 [doi]
• Learning Parameters for a Knowledge Diagnostic Tools in Orthopedic SurgerySébastien Lallé, Vanda Luengo. 369-370 [doi]
• Problem Response Theory and its Application for TutoringPetr Jarusek, Radek Pelánek. 371-372 [doi]
• Towards Better Understanding of Transfer in Cognitive Models of PracticeMichael Yudelson, Philip I. Pavlik, Kenneth R. Koedinger. 373-374 [doi]