Full proceedings are available
Accepted Papers
- Anthony Allevato, Matthew Thornton, Stephen Edwards and Manuel Perez-Quinones. Mining Data from an Automated Grading and Testing System by Adding Rich Reporting Capabilities
- Claudia Antunes. Acquiring Background Knowledge for Intelligent Tutoring Systems
- Ryan Baker, Albert Corbett and Vincent Aleven. Improving Contextual Models of Guessing and Slipping with a Truncated Training Set
- Ryan Baker and Adriana de Carvalho. Labeling Student Behavior Faster and More Precisely with Text Replays
- Michel Desmarais, Alejandro Villarreal and Michel Gagnon. Adaptive Test Design with a Naive Bayes Framework
- Mingyu Feng, Joseph Beck, Neil Heffernan and Ken Koedinger. Can an Intelligent Tutoring System Predict Math Proficiency as Well as a Standardized Test?
- Roland Hubscher and Sadhana Puntambekar. Integrating Knowledge Gained From Data Mining With Pedagogical Knowledge
- Hogyeong Jeong and Gautam Biswas. Mining Student Behavior Models in Learning-by-Teaching Environments
- Ken Koedinger, Kyle Cunningham, Alida Skogsholm and Brett Leber. An Open Repository and Analysis Tools for Fine-grained, Longitudinal Learner Data
- Collin Lynch, Kevin Ashley, Niels Pinkwart and Vincent Aleven. Argument Graph Classification With Genetic Programming and C4.5
- Manolis Mavrikis. Data-driven Modelling of Students' Interactions in an ILE
- Jack Mostow and Xiaonan Zhang. Analytic Comparison of Three Methods to Evaluate Tutorial Behaviors
- Zachary Pardos, Joseph Beck, Neil Heffernan and Carolina Ruiz. The Composition Effect: Conjuntive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS
- Philip Pavlik, Hao Cen, Lili Wu and Ken Koedinger. Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor
- Cristobal Romero, Sebastián Ventura, Pedro G. Espejo and Cesar Hervas. Data Mining Algorithms to Classify Students
- Benjamin Shih, Kenneth Koedinger and Richard Scheines. A Response Time Model for Bottom-Out Hints as Worked Examples
- Kalina Yacef and Agathe Merceron. Interestingness Measures for Association Rules in Educational Data
Accepted Posters and Young Researchers' Track Papers
- Safia Abbas and Hajime Sawamura. Argument Mining Using Highly Structured Argument Repertoire
- Elizabeth Ayers, Rebecca Nugent and Nema Dean. Skill Set Profile Clustering Based on Weighted Student Responses
- Tiffany Barnes, John Stamper, Lorrie Lehman and Marvin Croy. A Pilot Study on Logic Proof Tutoring Using Hints Generated from Historical Student Data
- Min Chi, Pamela Jordan, Kurt VanLehn and Moses Hall. Reinforcement Learning-based Feature Selection For Developing Pedagogically Effective Tutorial Dialogue Tactics
- Kwangsu Cho. Machine Classification of Peer Comments in Physics
- Mingyu Feng, Neil Heffernan, Joseph Beck and Ken Koedinger. Can We Predict Which Groups of Questions Students Will Learn From?
- Cecily Heiner. A Preliminary Analysis of the Logged Questions that Students Ask in Introductory Computer Science
- Arnon Hershkovitz and Rafi Nachmias. Developing a Log-based Motivation Measuring Tool
- Moffat Mathews and Tanja Mitrovic. Do Students Who See More Concepts in an ITS Learn More?
- Mykola Pechenizkiy, Toon Calders, Ekaterina Vasilyeva and Paul De Bra. Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study
- Cristobal Romero, Sergio Gutiérrez, Manuel Freire and Sebastián Ventura. Mining and Visualizing Visited Trails in Web-Based Educational Systems
- Ben Shapiro, Hisham Petry and Louis Gomez. Computational Infrastructures for School Improvement: A Way to Move Forward
- Sebastián Ventura, Cristobal Romero and Cesar Hervas. Analyzing Rule Evaluation Measures with Educational Datasets: A Framework to Help the Teacher
- Xiaonan Zhang, Jack Mostow, Nell Duke, Christina Trotochaud, Joseph Valeri and Albert Corbett. Mining Free-form Spoken Responses to Tutor Prompts