Organized by the International Working Group on Educational Data Mining.


Université du Québec à Montréal (UQAM), Canada

Machine Learning Department at the School of Computer Science, Carnegie Melon University

Full proceedings are available

Accepted Papers

  1. Anthony Allevato, Matthew Thornton, Stephen Edwards and Manuel Perez-Quinones. Mining Data from an Automated Grading and Testing System by Adding Rich Reporting Capabilities
  2. Claudia Antunes. Acquiring Background Knowledge for Intelligent Tutoring Systems
  3. Ryan Baker, Albert Corbett and Vincent Aleven. Improving Contextual Models of Guessing and Slipping with a Truncated Training Set
  4. Ryan Baker and Adriana de Carvalho.  Labeling Student Behavior Faster and More Precisely with Text Replays
  5. Michel Desmarais, Alejandro Villarreal and Michel Gagnon. Adaptive Test Design with a Naive Bayes Framework
  6. Mingyu Feng, Joseph Beck, Neil Heffernan and Ken Koedinger. Can an Intelligent Tutoring System Predict Math Proficiency as Well as a Standardized Test?
  7. Roland Hubscher and Sadhana Puntambekar. Integrating Knowledge Gained From Data Mining With Pedagogical Knowledge
  8. Hogyeong Jeong and Gautam Biswas. Mining Student Behavior Models in Learning-by-Teaching Environments
  9. Ken Koedinger, Kyle Cunningham, Alida Skogsholm and Brett Leber. An Open Repository and Analysis Tools for Fine-grained, Longitudinal Learner Data
  10. Collin Lynch, Kevin Ashley, Niels Pinkwart and Vincent Aleven. Argument Graph Classification With Genetic Programming and C4.5
  11. Manolis Mavrikis. Data-driven Modelling of Students' Interactions in an ILE
  12. Jack Mostow and Xiaonan Zhang. Analytic Comparison of Three Methods to Evaluate Tutorial Behaviors
  13. Zachary Pardos, Joseph Beck, Neil Heffernan and Carolina Ruiz. The Composition Effect: Conjuntive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS
  14. Philip Pavlik, Hao Cen, Lili Wu and Ken Koedinger. Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor
  15. Cristobal Romero, Sebastián Ventura, Pedro G. Espejo and Cesar Hervas. Data Mining Algorithms to Classify Students
  16. Benjamin Shih, Kenneth Koedinger and Richard Scheines.  A Response Time Model for Bottom-Out Hints as Worked Examples
  17. Kalina Yacef and Agathe Merceron. Interestingness Measures for Association Rules in Educational Data

Accepted Posters and Young Researchers' Track Papers

  1. Safia Abbas and Hajime Sawamura. Argument Mining Using Highly Structured Argument Repertoire
  2. Elizabeth Ayers, Rebecca Nugent and Nema Dean. Skill Set Profile Clustering Based on Weighted Student Responses
  3. Tiffany Barnes, John Stamper, Lorrie Lehman and Marvin Croy.  A Pilot Study on Logic Proof Tutoring Using Hints Generated from Historical Student Data
  4. Min Chi, Pamela Jordan, Kurt VanLehn and Moses Hall. Reinforcement Learning-based Feature Selection For Developing Pedagogically Effective Tutorial Dialogue Tactics
  5. Kwangsu Cho. Machine Classification of Peer Comments in Physics
  6. Mingyu Feng, Neil Heffernan, Joseph Beck and Ken Koedinger. Can We Predict Which Groups of Questions Students Will Learn From?
  7. Cecily Heiner. A Preliminary Analysis of the Logged Questions that Students Ask in Introductory Computer Science
  8. Arnon Hershkovitz and Rafi Nachmias. Developing a Log-based Motivation Measuring Tool
  9. Moffat Mathews and Tanja Mitrovic. Do Students Who See More Concepts in an ITS Learn More?
  10. Mykola Pechenizkiy, Toon Calders, Ekaterina Vasilyeva and Paul De Bra. Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study
  11. Cristobal Romero, Sergio Gutiérrez, Manuel Freire and Sebastián Ventura. Mining and Visualizing Visited Trails in Web-Based Educational Systems
  12. Ben Shapiro, Hisham Petry and Louis Gomez. Computational Infrastructures for School Improvement: A Way to Move Forward
  13. Sebastián Ventura, Cristobal Romero and Cesar Hervas. Analyzing Rule Evaluation Measures with Educational Datasets: A Framework to Help the Teacher
  14. Xiaonan Zhang, Jack Mostow, Nell Duke, Christina Trotochaud, Joseph Valeri and Albert Corbett. Mining Free-form Spoken Responses to Tutor Prompts