EduRank: A Collaborative Filtering Approach to Personalization in E-learning

Avi Segal, Ziv Katzir, Yakov Gal, Guy Shani, Bracha Shapira

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The growing prevalence of e-learning systems and on-line courses has made educational material widely accessible to students of varying abilities, backgrounds and styles. There is thus a growing need to accomodate for individual differences in such e-learning systems. This paper presents a new algorithm for personliazing educational content to students that combines collaborative filtering algorithms with social choice theory. The algorithm constructs a “difficulty” ranking over questions for a target student by aggregating the ranking of similar students, as measured by different aspects of their performance on common past questions, such as grades, number of retries, and time spent solving questions. It infers a difficulty ranking directly over the questions for a target student, rather than ordering them according to predicted performance, which is prone to error. The algorithm was tested on two large real world data sets containing tens of thousands of students and a million records. Its performance was compared to a variety of personalization methods as well as a non-personalized method that relied on a domain expert. It was able to significantly outperform all of these approaches according to standard information retrieval metrics. Our approach can potentially be used to support teachers in tailoring problem sets and exams to individual students and students in informing them about areas they may need to strengthen.
Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Educational Data Mining (EDM 2014)
Place of PublicationInstitute of Education, London, UK
Pages68-75
Number of pages8
Publication statusPublished - 2014
Event7th International Conference on Educational Data Mining - Institute of Education, London, United Kingdom
Duration: 4 Jul 20147 Jul 2014
http://educationaldatamining.org/EDM2014/

Conference

Conference7th International Conference on Educational Data Mining
Abbreviated titleEDM 2014
CountryUnited Kingdom
CityLondon
Period4/07/147/07/14
Internet address

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