Publication Details

Gamification in Assignments: Using Dynamic Difficulty Adjustment and Learning Analytics to Enhance Education

PASTUSHENKO, O. Gamification in Assignments: Using Dynamic Difficulty Adjustment and Learning Analytics to Enhance Education. In Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play Companion. Extended Abstracts. Barcelona: Association for Computing Machinery, 2019. p. 47-53. ISBN: 978-3-319-77711-5.
Czech title
Gamifikace v úkolech: použití dynamické úpravy složitosti a analýzy učení ke zlepšení vzdělávání
Type
conference paper
Language
English
Authors
Keywords

gamification; dynamic difficulty adjustment; personalized learning; multimodal learning analytics

Abstract

This paper discusses the opportunities for gamification and dynamic difficulty adjustment based on multimodal learning analytics in assignments. Altogether this covers a broader term of personalized education, which is getting more attention among the researchers in recent years. The difference of this work from other similar researches is that it suggests combining several domains to achieve better results: gamification (in order to improve student's motivation and involvements), and dynamic difficulty adjustment. All this is made possible by applying multimodal learning analytics and creating useful learning dashboards for the teachers.

Published
2019
Pages
47–53
Proceedings
Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play Companion
Series
Extended Abstracts
ISBN
978-3-319-77711-5
Publisher
Association for Computing Machinery
Place
Barcelona
DOI
UT WoS
000518428000008
EID Scopus
BibTeX
@inproceedings{BUT161461,
  author="Olena {Pastushenko}",
  title="Gamification in Assignments: Using Dynamic Difficulty Adjustment and Learning Analytics to Enhance Education",
  booktitle="Extended Abstracts of the Annual Symposium on Computer-Human Interaction in Play Companion",
  year="2019",
  series="Extended Abstracts",
  pages="47--53",
  publisher="Association for Computing Machinery",
  address="Barcelona",
  doi="10.1145/3341215.3356335",
  isbn="978-3-319-77711-5",
  url="https://www.fit.vut.cz/research/publication/12063/"
}
Files
Back to top