Presentations and Authors


Last name A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Track:
 

Full Paper

Data Mining Algorithms to Classify Students PDF
Cristobal Romero, Sebastian Ventura, Pedro G Espejo, Cesar Hervas 8-17
Acquiring Background Knowledge for Intelligent Tutoring Systems PDF
Claudia Antunes 18-27
Analytic Comparison of Three Methods to Evaluate Tutorial Behaviors PDF
Jack Mostow, Xiaonan Zhang 28-37
Labeling Student Behavior Faster and More Precisely with Text Replays PDF
Ryan Baker, Adriana de Carvalho 38-47
Adaptive Test Design with a Naive Bayes Framework PDF
Michel Desmarais, Alejandro Villarreal, Michael Gagnon 48-56
Interestingness Measures for Association Rules in Educational Data PDF
Agathe Merceron, Kalina Yacef 57-66
Improving Contextual Models of Guessing and Slipping with a Truncated Training Set PDF
Ryan Baker, Alexander Corbett, Vincent Aleven 67-76
Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor PDF
Philip Pavlik, Hao Cen, Lili Wu, Kenneth Koedinger 77-86
Data-driven modelling of students' interactions in an ILE PDF
Manolis Mavrikis 87-96
Integrating Knowledge Gained From Data Mining With Pedagogical Knowledge PDF
Roland Hubscher, Sadhana Puntambekar 97-106
Can an Intelligent Tutoring System Predict Math Proficiency as Well as a Standardized Test? PDF
Mingyu Feng, Joseph Beck, Neil Heffernan, Kenneth Koedinger 107-116
A Response Time Model for Bottom-Out Hints as Worked Examples PDF
Benjamin Shih, Kenneth Koedinger, Richard Scheines 117-126
Mining Student Behavior Models in Learning-by-Teaching Environments PDF
Hogyeong Jeong, Gautam Biswas 127-136
Argument graph classification with Genetic Programming and C4.5 PDF
Collin Lynch, Kevin Ashley, Niels Pinkwart, Vincent Aleven 137-146
The Composition Effect: Conjuntive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS PDF
Zachary Pardos, Neil Heffernan, Carolina Ruiz, Joseph Beck 147-156
An open repository and analysis tools for fine-grained, longitudinal learner data PDF
Kenneth Koedinger, Kyle Cunningham, Alida Skogsholm, Brett Leber 157-166
Mining Data from an Automated Grading and Testing System by Adding Rich Reporting Capabilities PDF
Anthony Allevato, Matthew Thornton, Stephen Edwards, Manuel Perez-Quinones 167-176

Poster

Analyzing Rule Evaluation Measures with Educational Datasets: A Framework to Help the Teacher PDF
Sebastian Ventura, Cristobal Romero, Cesar Hervas 177-181
Mining and Visualizing Visited Trails in Web-Based Educational Systems PDF
Cristobal Romero, Sergio GutiƩrrez, Manuel Freire, Sebastian Ventura 182-186
Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study PDF
Mykola Pechenizkiy, Toon Calders, Ekaterina Vasilyeva, Paul De Bra 187-191
Machine Classification of Peer Comments in Physics PDF
Kwangsu Cho 192-196
A pilot study on logic proof tutoring using hints generated from historical student data PDF
Tiffany Barnes, John Stamper, Lorrie Lehman, Marvin Croy 197-201

Young Researcher Track

Towards Argument Mining from Relational DataBase PDF
Safia Abbas, Hajime Sawamura 202-209
Skill Set Profile Clustering Based on Weighted Student Responses PDF
Elizabeth Ayers, Rebecca Nugent, Nema Dean 210-217
Can we predict which groups of questions students will learn from? PDF
Mingyu Feng, Neil Heffernan, Joseph Beck, Kenneth Koedinger 218-225
Developing a Log-based Motivation Measuring Tool PDF
Arnon Hershkovitz, Rafi Nachmias 226-233
Mining Free-form Spoken Responses to Tutor Prompts PDF
Xiaonan Zhang, Jack Mostow, Nell Duke, Christina Trotochaud, Joseph Valeri, Albert Corbett 234-241
Computational Infrastructures for School Improvement: A Way to Move Forward PDF
R. Benjamin Shapiro, Hisham Petry, Louis M Gomez 242-249
A Preliminary Analysis of the Logged Questions that Students Ask in Introductory Computer Science PDF
Cecily Heiner 250-257
Reinforcement Learningbased Feature Selection For Developing Pedagogically Effective Tutorial Dialogue Tactics PDF
Min Chi, Pamela Jordan, Kurth VanLehn, Moses Hall 258-265
Do Students Who See More Concepts in an ITS Learn More? PDF
Moffat Mathews, Tanja Mitrovic 266-273