poster

User type clustering to refine search and browse for educational resources (abstract only)

Authors:

Monika Akbar,

Clifford A. ShafferAuthors Info & Claims

SIGCSE '12: Proceedings of the 43rd ACM technical symposium on Computer Science Education

Page 666

https://doi.org/10.1145/2157136.2157371

Published: 29 February 2012 Publication History

Abstract

Educational portals such as Algoviz.org contain rich information resources, and a key concern is directing the users to specific resources that are of interest to them. While AlgoViz has significant traffic, we cannot count on active user participation in the form of explicit ratings of individual resources. Often called a "cold-start" problem, this scenario is well-known in community-based websites. Lacking active user data, we instead use log data to deduce user trends. We describe our techniques for clustering users based on the log data. We show how this cluster analysis can be used to refine searching and browsing within AlgoViz. Our approach has the potential to be useful for a wide range of educational resource portals.

Index Terms

User type clustering to refine search and browse for educational resources (abstract only)

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Information & Contributors

Information

Published In

SIGCSE '12: Proceedings of the 43rd ACM technical symposium on Computer Science Education

February 2012

734 pages

ISBN:9781450310987

DOI:10.1145/2157136

Conference Chairs:
Laurie Smith King
College of the Holy Cross
,
David R. Musicant,
Program Chairs:
Tracy Camp
Colorado School of Mines
,
Paul Tymann
Rochester Institute of Technology

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 February 2012

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Author Tags

Qualifiers

Poster

Conference

SIGCSE '12

Sponsor:

SIGCSE

SIGCSE '12: The 43rd ACM Technical Symposium on Computer Science Education

February 29 - March 3, 2012

North Carolina, Raleigh, USA

Acceptance Rates

SIGCSE '12 Paper Acceptance Rate 100 of 289 submissions, 35%;

Overall Acceptance Rate 1,787 of 5,146 submissions, 35%

Index Terms

Recommendations

Personalised recommendation of educational resources based on collaborative filtering

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