Hey, wake up: Come alongwith the artificial learning companion to the e-learner's outcomes high!

Hyun Young Kim, Bomyeong Kim, Jeehang Lee, Jinwoo Kim

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

1 Citation (Scopus)

Abstract

Compared to offline learners, online learners' attitude during the learning process is relatively poor, and a feeling of loneliness is entailed as they often study alone. This results in a low learning outcome. So far, no examples exist for the design of a learning companion to this end. Herein we present a pioneering work on a co-existing, artificial learning companion capable of improving the learner's attitude through sleepiness detection. We capture, analyze and estimate the level of sleepiness employing a machine learning technique with the pilot study data. Then, we propose a prototype called LearniCube using a sleepiness detection model with an experimental evaluation of LearniCube.

Original languageEnglish
Title of host publicationCHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Pages1763-1770
Number of pages8
ISBN (Electronic)9781450346566
DOIs
Publication statusPublished - 2017 May 6
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: 2017 May 62017 May 11

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
VolumePart F127655

Other

Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
CountryUnited States
CityDenver
Period17/5/617/5/11

Bibliographical note

Funding Information:
We thank Jioon Park and Mincheol Shin who provided helpful comments on the prototype. This research was supported by the MSIP, Korea, under the G-ITRC support program (IITP-2017-R6812-15-0001) supervised by the IITP. This research was supported by the Ministry of Education(NRF-2016R1D1A1B02015987).

Publisher Copyright:
Copyright © 2017 by the Association for Computing Machinery, Inc. (ACM).

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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