Educational Data Mining
Papers from the 2006 AAAI Workshop
Joseph E. Beck, Esma Aimeur, and Tiffany Barnes, Program Cochairs
Technical Report WS-06-05 published by The AAAI Press, Menlo Park, California
This technical report is also available in book and CD format.
Please Note: Abstracts are linked to individual titles, and will appear in a separate browser window. Full-text versions of the papers are linked to the abstract text. Access to full text may be restricted to AAAI members. PDF file sizes may be large!
Contents
Organizing Committee / vii
Joseph E. Beck, Esma Aimeur, and Tiffany Barnes
Predicting End-of-Year Accountability Assessment Scores from Monthly Student Records in an Online Tutoring System / 1
Nathaniel O. Anozie and Brian W. Junker
Feature Discovery in the Context of Educational Data Mining: An Inductive Approach / 7
Andrew Arnold, Joseph E. Beck, and Richard Scheines
Do Skills Combine Additively to Predict Task Difficulty in Eighth-Grade Mathematics? / 14
Elizabeth Ayers and Brian Junker
Comparative Analysis of Concept Derivation Using the Q-matrix Method and Facets / 21
Tiffany Barnes, John Stamper, and Tara Madhyastha
Using Association Rules for Course Recommendation / 31
Narimel Bendakir and Esma Aïmeur
Does Help Help? A Bayes Net Approach to Modeling Tutor Interventions / 41
Kai-min Chang, Joseph E. Beck, Jack Mostow, and Albert Corbett
Item-based Bayesian Student Models / 47
Michel C. Desmarais, Michel Gagnon, and Peyman Meshkinfam
Using Mixed-Effects Modeling to Compare Different Grain-Sized Skill Models / 57
Mingyu Feng, Neil Heffernan, Murali Mani, and Cristina Heffernan
Modeling and Assessing Student Activities in On-Line Discussions / 67
Jihie Kim, Erin Shaw, Donghui Feng, Carole Beal, and Eduard Hovy
Inferring Use Cases from Unit Testing / 75
Jaime Spacco, Titus Winters, and Tom Payne
Mining Student Learning Data to Develop High Level Pedagogic Strategy in a Medical ITS / 82
Michael V. Yudelson, Olga Medvedeva, Elizabeth Legowski, Melissa Castine, Drazen Jukic, and Rebecca S. Crowley
AAAI Digital Library
AAAI relies on your generous support through membership and donations. If you find these resources useful, we would be grateful for your support.