scholarly journals Correlation Research on the Application of E-Learning to Students’ Self-Regulated Learning Ability, Motivational Beliefs, and Academic Performance

2016 ◽  
Vol 12 (4) ◽  
Author(s):  
Hsu Kuan Jonathan LIU
Keyword(s):  
Academic Performance ◽  
Learning Ability ◽  
Motivational Beliefs ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
E Learning

Impact of self-regulated learning on academic performance and satisfaction of students in the online environment

2019 ◽  
pp. 345-363 ◽  
Keyword(s):  
Academic Performance ◽  
Goal Setting ◽  
Positive Impact ◽  
Social Dimension ◽  
Online Environment ◽  
Self Regulated Learning ◽  
Five Factors ◽  
Regulated Learning ◽  
Students Satisfaction ◽  
Important Milestone

The concept of self-regulated learning (SRL) hasn’t been researched enough in Bosnia and Herzegovina (B&H) and hence this study represents an important milestone in understanding this concept in this context. The conducted research was initiated with the presupposition that SRL had a positive impact on satisfaction and academic performance of students. In order to prove the goals of the research, two main hypotheses were formulated. The results of the exploratory factor analysis (EFA) have shown that the statements within SRL are grouped into five factors: goal-setting, metacognition, environment structuring, computer self-efficacy and social dimension. Multiple regression analysis proved that 4 of 5 factors have a positive impact on satisfaction and academic performance of students. Only goal-setting yielded no significance on the two aforementioned variables, while remaining four factors showed a significant influence on students’ satisfaction and academic performance.

scholarly journals The relationship between self-regulated learning strategies and students' academic performance in English course

2021 ◽  
Vol 15 (7) ◽  
pp. 2261-2263
Author(s):  
Helia Nodeh
Keyword(s):  
Academic Performance ◽  
Learning Strategies ◽  
Learning Strategy ◽  
Pearson Correlation ◽  
Statistical Population ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Education Academic ◽  
Keywords Education ◽  
The Relationship

This study examines the relationship between self-regulated learning strategies and students' academic performance in English courses. The research method is descriptive-correlational. The statistical population includes all students of Azad University, Gorgan branch in the period 2020-2021. convenience sampling based on the Morgan table is used to select 384 people. The data collection tool is Zimmerman and Martinez-Pons Self-Regulated Learning Interview Schedule (1998), and for academic performance, the average grade in English course in two semesters was taken into account. Pearson correlation analyzes the data. The results show a significant relationship between self-regulated learning strategies and the academic performance of English course students. Keywords: education, academic performance, learning strategy

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.

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