Associative recommendation of learning contents aided by eye-tracking in a social media enhanced environment

Guangyu Piao, Xiaokang Zhou, Qun Jin*

*Corresponding author for this work

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

Abstract

In this paper, an approach to presenting the learning resources, especially those existing user-generated contents associated with learners’ activities, as the recommendation to satisfy their current requirements in a social media enhanced learning system, is proposed. Users’ attentions are caught and analyzed from the browsing behaviors of learners on a webpage through an eye-tracking device.

Original languageEnglish
Title of host publicationUbiquitous Computing Application and Wireless Sensor, UCAWSN-2014
EditorsYi Pan, Gangman Yi, Han-Chieh Chao, James J. Park
PublisherSpringer Verlag
Pages493-501
Number of pages9
ISBN (Electronic)9789401796170
DOIs
Publication statusPublished - 2015
Event2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network, UCAWSN 2014 - , Korea, Republic of
Duration: 2014 Jul 72014 Jul 10

Publication series

NameLecture Notes in Electrical Engineering
Volume331
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network, UCAWSN 2014
Country/TerritoryKorea, Republic of
Period14/7/714/7/10

Keywords

  • Associative recommendation
  • Browsing behavior
  • Eye-tracking
  • Social media

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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