Title: Advancement and research trends of smart learning environments in the mobile era

Authors: Gwo-Jen Hwang; Qing-Ke Fu

Addresses: Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan; School of Teacher Education, Huzhou University, Huzhou 313000, Zhejiang, China ' Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan; School of Teacher Education, Huzhou University, Huzhou 313000, Zhejiang, China

Abstract: Currently, the rapid development of modern technologies has been influencing and changing every aspect of our society, in an attempt to make our lives more convenient and intelligent. Constructing and applying Smart Learning Environments (SLEs) is such an effort to offer learners personalised learning experiences both effectively and efficiently. In the past half century, a steady development in the literature on SLEs has been identified. Moreover, most studies have been conducted in the fields of computer science, engineering, mathematics and social science. In the meantime, several technological components of SLEs have been identified as follows: overall, dynamic and open models of learners, mobile technologies and innovative technologies, intelligent cloud service, educational big data and learning analytics. Some salient pedagogical affordances of SLEs have also been presented, such as personalised learning content and paths, cognitive guiding, developing high-order abilities, facilitating diverse learning modes, and fostering autonomous learning and lifelong learning abilities. Finally, several future developmental trends or suggestions are proposed, such as taking learners' self-assessments into consideration when making decisions on personalised guiding, investigating the implementation of strategies and the application effects of the mixed learning modes based on SLEs in different teaching contexts, and so on.

Keywords: smart learning environments; trend analysis; educational big data; learning analytics; mobile learning.

DOI: 10.1504/IJMLO.2020.103911

International Journal of Mobile Learning and Organisation, 2020 Vol.14 No.1, pp.114 - 129

Received: 13 Feb 2019
Accepted: 19 Mar 2019

Published online: 02 Dec 2019 *

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