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  • 标题:Towards motivation-based adaptation of difficulty in e-learning programs
  • 本地全文:下载
  • 作者:Anke Endler ; Gunter Daniel Rey ; Martin V. Butz
  • 期刊名称:Australasian Journal of Educational Technology
  • 印刷版ISSN:1449-3098
  • 电子版ISSN:1449-5554
  • 出版年度:2012
  • 卷号:28
  • 期号:7
  • DOI:10.14742/ajet.792
  • 语种:English
  • 出版社:Australasian Society for Computers in Learning in Tertiary Education
  • 摘要:The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of motivational states. This data was then utilised to extract rules for an adequate motivation-based adaptation to maximise expected learning success. A learning classifier system was used for the data analysis, generating rules for suitable and unsuitable adaptations based on current user motivation data. We extracted a set of twelve rules which suggest particular adaptation strategies based on real-world data. These rules could generally be embedded into existing psychological theories, namely the Zone of Proximal Development and the Yerkes-Dodson Law. In future research, we intend to evaluate these rules on further studies and develop concrete sets of adaptation strategies based on user motivation measurements.
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