Table of Contents

• Adaptive Practice of Facts in Domains with Varied Prior KnowledgeJan Papousek, Radek Pelánek, Vít Stanislav. 6-13 [doi]
• Alternating Recursive Method for Q-matrix LearningYuan Sun, Shiwei Ye, Shunya Inoue, Yi Sun. 14-20 [doi]
• Application of Time Decay Functions and the Elo System in Student ModelingRadek Pelánek. 21-27 [doi]
• Causal Discovery with Models: Behavior, Affect, and Learning in Cognitive Tutor AlgebraStephen Fancsali. 28-35 [doi]
• Choice-based Assessment: Can Choices Made in Digital Games Predict 6th-Grade Students' Math Test Scores?Min Chi, Daniel L. Schwartz, Kristen Pilner Blair, Doris B. Chin. 36-43 [doi]
• Comparing Expert and Metric-Based Assessments of Association Rule InterestingnessDiego Luna Bazaldua, Ryan S. Baker, Maria Ofelia San Pedro. 44-51 [doi]
• Different parameters - same prediction: An analysis of learning curvesTanja Käser, Kenneth R. Koedinger, Markus H. Gross. 52-59 [doi]
• Discovering Gender-Specific Knowledge from Finnish Basic Education using PISA Scale IndicesMirka Saarela, Tommi Kärkkäinen. 60-67 [doi]
• EduRank: A Collaborative Filtering Approach to Personalization in E-learningAvi Segal, Ziv Katzir, Kobi Gal, Guy Shani, Bracha Shapira. 68-75 [doi]
• Exploring Differences in Problem Solving with Data-Driven Approach MapsMichael Eagle, Tiffany Barnes. 76-83 [doi]
• General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert KnowledgeYun Huang, José P. González-Brenes, Peter Brusilovsky. 84-91 [doi]
• Generating Hints for Programming Problems Using Intermediate OutputBarry W. Peddycord III, Andrew Hicks, Tiffany Barnes. 92-98 [doi]
• Integrating latent-factor and knowledge-tracing models to predict individual differences in learningMohammad Khajah, Rowan Wing, Robert V. Lindsey, Michael Mozer. 99-106 [doi]
• Interpreting model discovery and testing generalization to a new datasetRan Liu, Elizabeth A. McLaughlin, Kenneth R. Koedinger. 107-113 [doi]
• Learning Individual Behavior in an Educational Game: A Data-Driven ApproachSeong Jae Lee, Yun-En Liu, Zoran Popovic. 114-121 [doi]
• Predicting Learning and Affect from Multimodal Data Streams in Task-Oriented Tutorial DialogueJoseph F. Grafsgaard, Joseph B. Wiggins, Kristy Elizabeth Boyer, Eric N. Wiebe, James C. Lester. 122-129 [doi]
• Sentiment Analysis in MOOC Discussion Forums: What does it tell us?Miaomiao Wen, Diyi Yang, Carolyn Penstein Rosé. 130-137 [doi]
• The Effect of Mutual Gaze Perception on Students' Verbal CoordinationBertrand Schneider, Roy Pea. 138-144 [doi]
• The Opportunities and Limitations of Scaling Up Sensor-Free Affect DetectionMichael Wixon, Ivon Arroyo, Kasia Muldner, Winslow Burleson, Dovan Rai, Beverly Park Woolf. 145-152 [doi]
• The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized ExercisesJulio Guerra, Shaghayegh Sahebi, Yu-Ru Lin, Peter Brusilovsky. 153-160 [doi]
• Trading Off Scientific Knowledge and User Learning with Multi-Armed BanditsYun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popovic. 161-168 [doi]
• Vertical and Stationary Scales for Progress MapsRussell G. Almond, Ilya M. Goldin, Yuhua Guo, Nan Wang. 169-176 [doi]
• Visualization and Confirmatory Clustering of Sequence Data from a Simulation-Based Assessment TaskYoav Bergner, Zhan Shu, Alina Von Davier. 177-184 [doi]
• Who's in Control?: Categorizing Nuanced Patterns of Behaviors within a Game-Based Intelligent Tutoring SystemErica L. Snow, Laura K. Varner, Devin G. Russell, Danielle S. McNamara. 185-192 [doi]
• Acquisition of Triples of Knowledge from Lecture Notes: A Natural Langauge Processing ApproachThushari Atapattu, Katrina Falkner, Nickolas J. G. Falkner. 193-196 [doi]
• Towards Assessing Students' Prior Knowledge from Tutorial DialoguesDan Stefanescu, Vasile Rus, Arthur C. Graesser. 197-201 [doi]
• Assigning Educational Videos at Appropriate Locations in TextbooksMarios Kokkodis, Anitha Kannan, Krishnaram Kenthapadi. 201-204 [doi]
• Better Data Beats Big DataMichael Yudelson, Stephen Fancsali, Steven Ritter, Susan R. Berman, Tristan Nixon, Ambarish Joshi. 205-208 [doi]
• The refinement of a Q-matrix: Assessing methods to validate tasks to skills mappingMichel Desmarais, Behzad Beheshti, Peng Xu. 208-311 [doi]
• Building a Student At-Risk Model: An End-to-End Perspective From User to Data ScientistLalitha Agnihotri, Alexander Ott. 209-212 [doi]
• Can Engagement be Compared? Measuring Academic Engagement for ComparisonLing Tan, Xiaoxun Sun, Siek Toon Khoo. 213-216 [doi]
• Comparison of Algorithms for Automatically Building Example-Tracing Tutor ModelsRohit Kumar 0001, Matthew E. Roy, R. Bruce Roberts, John Makhoul. 217-220 [doi]
• Computer-based Adaptive Speed TestsDaniel Bengs, Ulf Brefeld. 221-224 [doi]
• Discovering Students' Complex Problem Solving Strategies in Educational AssessmentKrisztina Tóth, Heiko Rölke, Samuel Greiff, Sascha Wüstenberg. 225-228 [doi]
• Discovering Theoretically Grounded Predictors of Shallow vs. Deep- level LearningCarol Forsyth, Arthur C. Graesser, Philip I. Pavlik Jr., Keith K. Millis, Borhan Samei. 229-232 [doi]
• Domain Independent Assessment of Dialogic Properties of Classroom DiscourseBorhan Samei, Andrew Olney, Sean Kelly, Martin Nystrand, Sidney K. D'Mello, Nathaniel Blanchard, Xiaoyi Sun, Marci Glaus, Arthur C. Graesser. 233-236 [doi]
• Empirically Valid Rules for Ill-Defined DomainsCollin Lynch, Kevin D. Ashley. 237-240 [doi]
• Entropy: A Stealth Measure of Agency in Learning EnvironmentsErica L. Snow, Matthew E. Jacovina, Laura K. Varner, Jianmin Dai, Danielle S. McNamara. 241-244 [doi]
• Error Analysis as a Validation of Learning ProgressionsBrent Morgan, William Baggett, Vasile Rus. 245-248 [doi]
• Exploration of Student's Use of Rule Application References in a Propositional Logic TutorMichael Eagle, Vinaya Polamreddi, Behrooz Mostafavi, Tiffany Barnes. 249-252 [doi]
• Exploring real-time student models based on natural-language tutoring sessionsBenjamin Nye, Mustafa H. Hajeer, Carol Forsyth, Borhan Samei, Xiangen Hu, Keith K. Millis. 253-256 [doi]
• Forum Thread Recommendation for Massive Open Online CoursesDiyi Yang, Mario Piergallini, Iris K. Howley, Carolyn Penstein Rosé. 257-260 [doi]
• Investigating Automated Student Modeling in a Java MOOCMichael Yudelson, Roya Hosseini, Arto Vihavainen, Peter Brusilovsky. 261-264 [doi]
• Mining Gap-fill Questions from Tutorial DialoguesNobal B. Niraula, Vasile Rus, Dan Stefanescu, Arthur C. Graesser. 265-268 [doi]
• Online Optimization of Teaching Sequences with Multi-Armed BanditsBenjamin Clement, Pierre-Yves Oudeyer, Didier Roy, Manuel Lopes. 269-272 [doi]
• Predicting MOOC performance with Week 1 BehaviorSuhang Jiang, Adrienne E. Williams, Katerina Schenke, Mark Warschauer, Diane K. O'Dowd. 273-275 [doi]
• Predicting STEM and Non-STEM College Major Enrollment from Middle School Interaction with Mathematics Educational SoftwareMaria Ofelia San Pedro, Jaclyn Ocumpaugh, Ryan S. Baker, Neil T. Heffernan. 276-279 [doi]
• Quantized Matrix Completion for Personalized LearningAndrew S. Lan, Christoph Studer, Richard G. Baraniuk. 280-283 [doi]
• Reengineering the Feature Distillation Process: A case study in detection of Gaming the SystemLuc Paquette, Adriana de Carvahlo, Ryan Baker, Jaclyn Ocumpaugh. 284-287 [doi]
• SKETCHMINER: Mining Learner-Generated Science Drawings with Topological AbstractionAndy Smith, Eric N. Wiebe, Bradford W. Mott, James C. Lester. 288-291 [doi]
• Teachers and Students Learn Cyber Security: Comparing Software Quality, SecurityShlomi Boutnaru, Arnon Hershkovitz. 292-295 [doi]
• Testing the Multimedia Principle in the Real World: A Comparison of Video vs. Text Feedback in Authentic Middle School Math AssignmentsKorinn Ostrow, Neil T. Heffernan. 296-299 [doi]
• The Importance of Grammar and Mechanics in Writing Assessment and Instruction: Evidence from Data MiningScott A. Crossley, Kris Kyle, Laura K. Varner, Danielle S. McNamara. 300-303 [doi]
• The Long and Winding Road: Investigating the Differential Writing Patterns of High and Low Skilled WritersLaura K. Varner, Erica L. Snow, Danielle S. McNamara. 304-407 [doi]
• Tracing Knowledge and Engagement in Parallel in an Intelligent Tutoring SystemSarah E. Schultz, Ivon Arroyo. 312-315 [doi]
• Tracking Choices: Computational Analysis of Learning TrajectoriesErica L. Snow, Laura K. Varner, Danielle S. McNamara. 316-319 [doi]
• Unraveling Students' Interaction Around a Tangible Interface Using Gesture RecognitionBertrand Schneider, Paulo Blikstein. 320-323 [doi]
• A Predictive Model for Video Lectures ClassificationPriscylla Silva, Robert Pinheiro, Evandro Costa. 325-326 [doi]
• Accepting or Rejecting Students_ Self-grading in their Final Marks by using Data MiningJavier Fuentes, Cristóbal Romero, Carlos García-Martínez, Sebastián Ventura. 327-328 [doi]
• Analysis and extraction of behaviors by students in lecturesEiji Watanabe, Takashi Ozeki, Takeshi Kohama. 329-330 [doi]
• Analysis of Student Retention and Drop-out using Visual AnalyticsJan Géryk, Lubomír Popelínský. 331-332 [doi]
• Automatic assessment of student reading comprehension from short summariesLisa Mintz, Dan Stefanescu, Shi Feng, Sidney K. D'Mello, Arthur C. Graesser. 333-334 [doi]
• Building an Intelligent PAL from the Tutor.com Session Database Phase 1: Data MiningDonald M. Morrison, Benjamin Nye, Borhan Samei, Vivek V. Datla, Craig Kelly, Vasile Rus. 335-336 [doi]
• Building Automated Detectors of Gameplay Strategies to Measure Implicit Science LearningElizabeth Rowe, Ryan S. Baker, Jodi Asbell-Clarke, Emily Kasman, William J. Hawkins. 337-338 [doi]
• Challenges on adopting BKT to model student knowledge in multi-context online learning platformWolney Leal De Mello Neto, Eduardo Barbosa, Felipe García, Leonardo Carvalho, Nicolau Leal Werneck, Pedro Carvalho. 339-340 [doi]
• Combination of statistical and semantic data sources for the improvement of software engineering courses (Vision Paper)Michael Koch, Markus Ring, Florian Otto, Dieter Landes. 341-342 [doi]
• Comparing Learning in a MOOC and a Blended, On-Campus CourseKimberly F. Colvin, John Champaign, Alwina Liu, Colin Fredericks, David E. Pritchard. 343-344 [doi]
• Cost-Effective, Actionable Engagement Detection at ScaleRyan S. Baker, Jaclyn Ocumpaugh. 345-346 [doi]
• Data mining of undergraduate course evaluationsSohail Javaad Syed, Yuheng Helen Jiang, Lukasz Golab. 347-348 [doi]
• Data Sharing: Low-Cost Sensors for Affect and CognitionKeith W. Brawner. 349-350 [doi]
• Diagnosing Algebra Understanding via Bayesian Inverse PlanningAnna N. Rafferty, Thomas L. Griffiths. 351-352 [doi]
• Discovering and describing types of mathematical errorsThomas S. McTavish, Johann Ari Larusson. 353-354 [doi]
• Discovering Prerequisite Relationships Among Knowledge ComponentsRichard Scheines, Elizabeth Silver, Ilya M. Goldin. 355-356 [doi]
• Dynamic Re-Composition of Learning Groups Using PSO-Based AlgorithmsZhilin Zheng, Niels Pinkwart. 357-358 [doi]
• Educational Data Mining and Analyzing of Student Learning Outcomes from the Perspective of Learning ExperienceZhongmei Shu, Qiong-Fei Qu, Lu-Qi Feng. 359-360 [doi]
• Using EEG in Knowledge TracingYanbo Xu, Kai-min Chang, Yueran Yuan, Jack Mostow. 361-362 [doi]
• Exploring Engaging Dialogues in Video DiscussionsI-Han Hsiao, Hui Soo Chae, Manav Malhotra, Ryan Baker, Gary Natriello. 363-364 [doi]
• Exploring indicators from keyboard and mouse interactions to predict the user affective stateSergio Salmeron-Majadas, Olga C. Santos, Jesus Boticario. 365-366 [doi]
• Extracting Latent Skills from Time Series of Asynchronous and Incomplete ExaminationsShinichi Oeda, Yu Ito, Kenji Yamanishi. 367-368 [doi]
• Generalizing and Extending a Predictive Model for Standardized Test Scores Based On Cognitive Tutor InteractionsAmbarish Joshi, Stephen Fancsali, Steven Ritter, Tristan Nixon, Susan R. Berman. 369-370 [doi]
• How patterns in source codes of students can help in detection of their programming skills?Stefan Pero, Tomás Horváth. 371-372 [doi]
• A Preliminary Investigation of Learner Characteristics for Unsupervised Dialogue Act ClassificationAysu Ezen-Can, Kristy Elizabeth Boyer. 373-374 [doi]
• Improving Retention Performance Prediction with Prerequisite Skill FeaturesXiaolu Xiong, Seth Adjei, Neil T. Heffernan. 375-376 [doi]
• Indicator Visualization for Adaptive Exploratory Learning EnvironmentsManolis Mavrikis, Sergio Gutiérrez Santos, Alexandra Poulovassilis, Zheng Zhu. 377-378 [doi]
• Learning Aid Use Patterns and Their Impact on Exam Performance in Online Developmental MathematicsNicole Forsgren Velasquez, Ilya M. Goldin, Taylor Martin, Jason Maughan. 379-380 [doi]
• Learning to Teach like a BanditMykola Pechenizkiy, Pedro A. Toledo. 381-382 [doi]
• Matching Hypothesis Text in Diagrams and EssaysCollin Lynch, Mohammad Hassan Falakmasir, Kevin D. Ashley. 383-384 [doi]
• Matrix Factorization Feasibility for Sequencing and Adaptive Support in Intelligent Tutoring SystemsCarlotta Schatten, Ruth Janning, Manolis Mavrikis, Lars Schmidt-Thieme. 385-386 [doi]
• Microgenetic Designs for Educational Data Mining Research: PosterTaylor Martin, Nicole Forsgren Velasquez, Ani Aghababyan, Jason Maughan, Philip Janisiewicz. 387-388 [doi]
• Mining and Identifying Relationships Among Sequential Patterns in Multi-Feature, Hierarchical Learning Activity DataCheng Ye, John S. Kinnebrew, Gautam Biswas. 389-390 [doi]
• Mining coherent evolution patterns in education through biclusteringAndré Vale, Sara C. Madeira, Cláudia Antunes. 391-392 [doi]
• Mining Multi-dimensional Patterns for Student ModellingAndreia Silva, Cláudia Antunes. 393-394 [doi]
• Mining Reading Comprehension Within Educational Objective FrameworksTerry Peckham, Gordon McCalla. 395-396 [doi]
• Mining students' strategies to enable collaborative learningSergio Gutiérrez Santos, Manolis Mavrikis, Alexandra Poulovassilis. 397-398 [doi]
• Modeling Student Socioaffective Responses to Group Interactions in a Collaborative Online Chat EnvironmentWhitney L. Cade, Nia Dowell, Arthur C. Graesser, Yla R. Tausczik, James W. Pennebaker. 399-400 [doi]
• Now We're Talking: Leveraging the Power of Natural Language Processing to Inform ITS DevelopmentLaura K. Allen, Erica L. Snow, Danielle S. McNamara. 401-402 [doi]
• Peer assessment in the first French MOOC : Analyzing assessors' behaviorMatthieu Cisel, Rémi Bachelet, Eric Bruillard. 403-404 [doi]
• Peer Influence on Attrition in Massively Open Online CoursesDiyi Yang, Miaomiao Wen, Carolyn Penstein Rosé. 405-406 [doi]
• Predicting students' learning achievement by using online learning patterns in blended learning environments: Comparison of two cases on linear and non-linear modelJeonghyun Kim, Yeonjeong Park, Jongwoo Song, Il-Hyun Jo. 407-408 [doi]
• Predictive performance of prevailing approaches to skills assessment techniques: Insights from real vs. synthetic data setsBehzad Beheshti, Michel Desmarais. 409-410 [doi]
• Recent-Performance Factors AnalysisApril Galyardt, Ilya M. Goldin. 411-412 [doi]
• Refining Learning Maps with Data Fitting Techniques: Searching for Better Fitting Learning MapsSeth Adjei, Douglas Selent, Neil T. Heffernan, Zachary A. Pardos, Angela Broaddus, Neal Kingston. 413-414 [doi]
• Relevancy prediction of micro-blog questions in an educational settingMariheida Cordova-Sanchez, Parameswaran Raman, Luo Si, Jason Fish. 415-416 [doi]
• Singular Value Decomposition in Education: a case study on recommending coursesFábio Carballo, Cláudia Antunes. 417-418 [doi]
• The predictive power of the SNA metrics for educationDiego García-Saiz, Camilo Palazuelos, Marta E. Zorrilla. 419-420 [doi]
• Data-Driven Curriculum Design: Mining the Web to Make Better Teaching DecisionsAntonio Moretti, José P. González-Brenes, Katherine McKnight. 421-422 [doi]
• Towards IRT-based student modeling from problem solving stepsManuel Hernando, Eduardo Guzmán, Sergey A. Sosnovsky, Eric Andres, Susanne Narciss. 423-424 [doi]
• Towards Uncovering the Mysterious World of Math HomeworkMingyu Feng. 425-426 [doi]
• Towards Using Similarity Measure for Automatic Detection of Significant Behaviors from Continuous DataBen-Manson Toussaint, Vanda Luengo, Jérôme Tonetti. 427-428 [doi]
• Using Data Mining to Automate ADDIEFritz Ray, Keith W. Brawner, Robby Robson. 429-430 [doi]
• Using Multimodal Learning Analytics to Study Learning MechanismsMarcelo Worsley, Paulo Blikstein. 431-432 [doi]
• Using Problem Solving Times and Expert Opinion to Detect SkillsJuraj Niznan, Radek Pelánek, Jirí Rihák. 433-434 [doi]
• Toward Collaboration Sensing: Multimodal Detection of the Chameleon Effect in Collaborative Learning SettingsBertrand Schneider. 435-437 [doi]
• The Use of Student Confidence for Prediction & Resolving Individual Student Knowledge StructureCharles Lang. 438-440 [doi]
• Nonverbal Communication and Teaching PerformanceRoghayeh Barmaki. 441-443 [doi]
• Data-Driven Feedback Beyond Next-Step HintsMichael Eagle, Tiffany Barnes. 444-446 [doi]
• E3: Emotions, Engagement and Educational GamesAni Aghababyan. 447-451 [doi]
• MOOC Leaner Motivation and Learning Pattern DiscoveryYuan Wang. 452-454 [doi]
• Personalization and Incentive Design in E-Learning SystemsAvi Segal. 455-457 [doi]