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