Off the beaten path: The impact of adaptive content sequencing on student navigation in an open social student modeling interface

Roya Hosseini, Ihan Hsiao, Julio Guerra, Peter Brusilovsky

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

5 Scopus citations

Abstract

One of the original goals of intelligent educational systems is to guide every student to the most appropriate educational content. Exploring both knowledge-based and social guidance approaches in past work, we learned that each of these approaches has weak sides. In this paper we follow the idea of combining social guidance with more traditional knowledge-based guidance to support more optimal content navigation. We proposed a greedy sequencing approach that maximizes student’s level of knowledge and tested it in a classroom. Results indicated that this approach positively impacts students’ navigation.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 17th International Conference, AIED 2015, Proceedings
EditorsCristina Conati, Neil Heffernan, Antonija Mitrovic, M. Felisa Verdejo
PublisherSpringer Verlag
Pages624-628
Number of pages5
ISBN (Print)9783319197722
DOIs
StatePublished - 2015
Event17th International Conference on Artificial Intelligence in Education, AIED 2015 - Madrid, Spain
Duration: Jun 22 2015Jun 26 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9112

Conference

Conference17th International Conference on Artificial Intelligence in Education, AIED 2015
Country/TerritorySpain
CityMadrid
Period6/22/156/26/15

Keywords

  • Adaptive navigation support
  • E-learning
  • Java programming
  • Open social student modeling
  • Personalized guidance

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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