Investigation of multiple human factors in personalized learning

Sherry Y. Chen, Pei Ren Huang, Yu Cheng Shih, Li Ping Chang

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

In the past decade, a number of personalized learning systems have been developed and they mainly focus on learners' prior knowledge. On the other hand, previous research suggested that gender differences and cognitive styles have great effects on student learning. To this end, this study examines how human factors, especially gender differences and cognitive styles, affect learners' reactions to a personalized and non-personalized learning systems based on learners' prior knowledge. Forty-four university students participated in this study. The results show that females and Serialists show positive reactions to the personalized learning system, while males and Holists demonstrate similar reactions to the personalized learning system and the non-personalized learning system. The implications of these results for the design of personalized learning systems are discussed.

Original languageEnglish
Pages (from-to)119-141
Number of pages23
JournalInteractive Learning Environments
Volume24
Issue number1
DOIs
StatePublished - 2 Jan 2016

Keywords

  • cognitive styles
  • gender differences
  • personalized learning
  • prior knowledge
  • web-based Learning

Fingerprint

Dive into the research topics of 'Investigation of multiple human factors in personalized learning'. Together they form a unique fingerprint.

Cite this