Cluster analysis on self-regulated learning to anticipate the success of online learning

2020 ◽  
Vol 14 (5) ◽  
Keyword(s):  
Cluster Analysis ◽  
Online Learning ◽  
Self Regulated Learning ◽  
Regulated Learning

How Much Can Computers and Internet Help?

2011 ◽  
Vol 7 (1) ◽  
pp. 67-81 ◽  
Author(s):  
Chia-Wen Tsai
Keyword(s):  
Online Learning ◽  
Teaching Method ◽  
Problem Based Learning ◽  
Vocational Schools ◽  
Long Term Effects ◽  
Computing Education ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Computing Skills

Computing education in Taiwan is ineffective. Most teaching efforts in private vocational schools have been devoted to helping students pass tests through a “spoon-feeding” teaching method. Under such constraints, students may lose their long-term competence in practical terms. In this study, the author conducted a series of quasi-experiments to examine the long-term effects of web-mediated problem-based learning (PBL), self-regulated learning (SRL), and their combinations on students’ computing skills over three years. The author re-examined students’ long-term computing skills three years after the start of the related course. Results reveal that effects of web-mediated PBL, SRL, and their combinations on students’ long-term computing skills are significant. The implications for scholars and teachers engaged in online learning were also discussed.

scholarly journals Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review

2018 ◽  
Vol 35 (4-5) ◽  
pp. 356-373 ◽  
Author(s):  
Jacqueline Wong ◽  
Martine Baars ◽  
Dan Davis ◽  
Tim Van Der Zee ◽  
Geert-Jan Houben ◽  
...  
Keyword(s):  
Systematic Review ◽  
Online Learning ◽  
Learning Environments ◽  
Online Learning Environments ◽  
Self Regulated Learning ◽  
Regulated Learning

A Conceptual Educational Data Mining Model for Supporting Self-Regulated Learning in Online Learning Environments

2021 ◽  
pp. 278-292
Author(s):  
Eric Araka ◽  
Robert Oboko ◽  
Elizaphan Maina ◽  
Rhoda K. Gitonga
Keyword(s):  
Data Mining ◽  
Online Learning ◽  
Learning Environments ◽  
Domain Knowledge ◽  
Educational Data Mining ◽  
Online Learning Environments ◽  
Student Activities ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
E Learning

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.

Preparing Online Learning Readiness with Learner-Content Interaction

2016 ◽  
pp. 586-614
Author(s):  
Juhong Christie Liu ◽  
Elaine Roberts Kaye
Keyword(s):  
Online Learning ◽  
Learning Environments ◽  
Online Courses ◽  
Learning Readiness ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Content Interaction ◽  
Online Learning Readiness ◽  
Synchronous Online

Online learning readiness is fundamental to student successful participation, presence, and interaction in online courses. Effective facilitation of these key components depends on sound instructional design. In self-directed online environments, learner-content interaction and scaffolding self-regulated learning have been found of primary importance to generate meaningful learning. To provide a solution to the challenges of interoperability of various functions in synchronous online learning environments, this chapter presents a case study about the design and development of a self-paced orientation to help students acquire online learning readiness. Learner-content interaction is strategically utilized in the design to scaffold self-regulated learning. The results of the case study demonstrate that this orientation positively prepares students to be ready for learning in a synchronous online environment. The approach can be of practical use to individuals and groups.

Can Self-Regulated Learning Intervention Improve Student Reading Performance in Flipped Classrooms?

2020 ◽  
Vol 10 (4) ◽  
pp. 1-13
Author(s):  
Christopher C. Y. Yang ◽  
Irene Y. L. Chen ◽  
Anna Y. Q. Huang ◽  
Qian-Ru Lin ◽  
Hiroaki Ogata
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Self Efficacy ◽  
Learning Strategy ◽  
Learning Performance ◽  
Book Reading ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Student Reading ◽  
Reading System

The advancement in network technology has stimulated the proliferation of online learning. Online learning platforms, such as the learning management systems (LMS) and e-book reading systems, are widely used in higher education to enhance students' reflection and planning of the learning process. Although many studies have explored the relationships between students' reading patterns and learning performances, few have examined the effects of self-regulated learning, learning strategy, and self-efficacy on the learning performance of students. Here, the authors collected the reading logs from an e-book reading system BookRoll and investigated the correlations between students' abilities of self-regulated learning, learning strategy, self-efficacy, and learning performance. The results of this study provide valuable insights to the teachers in higher education regarding designing courses helpful for students to improve their learning performance.

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