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12.02.2020 | Ausgabe 2/2020

Journal of Computers in Education 2/2020

Moderating effects of gender differences on the relationships between perceived learning support, intention to use, and learning performance in a personalized e-learning

Zeitschrift:
Journal of Computers in Education > Ausgabe 2/2020
Autoren:
Charoenchai Wongwatkit, Patcharin Panjaburee, Niwat Srisawasdi, Pongpon Seprum
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Abstract

Current endeavors to integrate students’ personal characteristics with e-learning environments designed for the delivery of content to individual students are growing. However, few studies have been conducted to investigate how gender differences moderate the relationships between students’ perceived personalized learning support and learning performance, and between the intention to use a system and the users’ learning performance. Drawing together perspectives from the literature on developing effective e-learning systems, technology acceptance, and gender differences, this research proposes a conceptual model to examine the influences of the relationships among students’ attitudes, acceptance, gender differences, and learning performance. Moreover, a personalized learning system was developed by taking learners’ to-be-enhanced concepts and learning preferences into account. An experiment was conducted with four classes of Thai high-school students studying the same topic of simple electricity to examining the proposed conceptual model as well as evaluate the performance of the personalized learning system. The Partial Least Square technique was employed to analyze data collected from school settings in Thailand. The path coefficient results showed that the perceived usefulness of the mastery learning support and intention to use had direct effects on the students’ learning performance in the personalized e-learning environment, and that gender moderated the relationship between perceived usefulness of conceptual learning suggestions and learning performance, and between intention to use and learning performance. These findings suggest that there are direct attitudinal and gender moderating factors affecting learning performance in personalized e-learning environments.

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