Research trends in self-regulated learning research in online learning environments: A review of studies published in selected journals from 2003 to 2012

2013 ◽  
Vol 44 (5) ◽  
pp. E107-E110 ◽  
Author(s):  
Chia-Wen Tsai ◽  
Pei-Di Shen ◽  
Ya-Ting Fan
2018 ◽  
Vol 35 (4-5) ◽  
pp. 356-373 ◽  
Author(s):  
Jacqueline Wong ◽  
Martine Baars ◽  
Dan Davis ◽  
Tim Van Der Zee ◽  
Geert-Jan Houben ◽  
...  

Author(s):  
Eric Araka ◽  
Robert Oboko ◽  
Elizaphan Maina ◽  
Rhoda K. Gitonga

Self-regulated learning is attracting tremendous researches from various communities such as information communication technology. Recent studies have greatly contributed to the domain knowledge that the use self-regulatory skills enhance academic performance. Despite these developments in SRL, our understanding on the tools and instruments to measure SRL in online learning environments is limited as the use of traditional tools developed for face-to-face classroom settings are still used to measure SRL on e-learning systems. Modern learning management systems (LMS) allow storage of datasets on student activities. Subsequently, it is now possible to use Educational Data Mining to extract learner patterns which can be used to support SRL. This chapter discusses the current tools for measuring and promoting SRL on e-learning platforms and a conceptual model grounded on educational data mining for implementation as a solution to promoting SRL strategies.


Author(s):  
Bruce R. Harris ◽  
Reinhard W. Lindner ◽  
Anthony A. Piña

The primary purpose of this chapter is to present techniques and strategies that can be incorporated in online courses to promote students’ use of self-regulated learning strategies. In addition, the authors discuss why self-regulated learning skills are particularly critical in online learning environments, present a model of self-regulated learning, discuss issues related to measuring self-regulated learning, address the issue of whether or not self-regulated learning can be taught, and discuss why online learning environments are ideal environments to scaffold self-regulation. The authors present several strategies and techniques they have found successful for promoting self-regulated learning that can be readily incorporated and implemented in online courses. These strategies are organized by the three main components of the Self-Regulated Learning Model: Executive Processing, Cognitive Processing, and Motivation. The chapter concludes with a scenario that represents an idealized model of how to promote self-regulated learning in an online learning environment by employing an intelligent tutoring component as a tool to support students’ use and development of self-regulated learning tactics and strategies.


2013 ◽  
Vol 48 (1) ◽  
pp. 45-69 ◽  
Author(s):  
Buncha Samruayruen ◽  
Judith Enriquez ◽  
Onjaree Natakuatoong ◽  
Kingkaew Samruayruen

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