Analyses of Individual Differences in Social Demographic Variables to set up Adult Self-Regulated Learning Literacy Norm and Implications to Adult Online Learning

2007 ◽  
Vol 3 (1) ◽  
pp. 105-115 ◽  
Author(s):  
Chengyun WANG
Keyword(s):  
Online Learning ◽  
Individual Differences ◽  
Demographic Variables ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Adult Online Learning ◽  
Set Up ◽  
Social Demographic

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

Individual Differences and Learning Contexts: A Self-Regulated Learning Perspective

2017 ◽  
Vol 119 (13) ◽  
pp. 1-20
Author(s):  
Adar Ben-Eliyahu
Keyword(s):  
Individual Differences ◽  
Self Regulation ◽  
Goal Orientations ◽  
Goal Structure ◽  
Learning Context ◽  
Mastery Goal ◽  
Self Regulated Learning ◽  
Learning Contexts ◽  
Achievement Outcomes ◽  
Regulated Learning

This article examines how individual differences (giftedness) interact with learning contexts (favorite versus least favorite courses) to influence learning processes and outcomes. The findings show that gifted and typically developing students differ solely in their expectancies for success and grades among a large variety of measures, including motivation (goal orientations, expectancies, and values) and self-regulated learning (self-regulated emotions, behaviors, and cognitions). These results imply that the learning context can override individual differences. Through the lens of the integrated self-regulated learning model (iSRL; Ben-Eliyahu & Bernacki, 2015), the article discusses why there are contextual differences in learning. By bridging the literature on mastery goal structure and self-determination theory, it is proposed that learning contexts focused on development and self-progress (i.e., mastery goal structured contexts) lead to adaptive achievement outcomes because competing basic needs are satisfied, competition decreases, and resources for learning are freed. Given the importance of self-regulated learning, students should be encouraged to develop learning habits and strategies based on self-regulation, which should be considered a 21st-century skill that can be scaffolded by educators in formal and informal learning settings.

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.

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