Efficient learning using a virtual learning environment in a university class

This study examines a blended learning setting in an undergraduate course in psychology. A virtual learning environment (VLE) complemented the face-to-face lecture. The usage was voluntary and the VLE was designed to support the learning process of the students. Data from users ( N = 80) and non-use...

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Published inComputers and education Vol. 56; no. 2; pp. 495 - 504
Main Authors Stricker, Daniel, Weibel, David, Wissmath, Bartholomäus
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.02.2011
Elsevier
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Online AccessGet full text
ISSN0360-1315
1873-782X
DOI10.1016/j.compedu.2010.09.012

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Abstract This study examines a blended learning setting in an undergraduate course in psychology. A virtual learning environment (VLE) complemented the face-to-face lecture. The usage was voluntary and the VLE was designed to support the learning process of the students. Data from users ( N = 80) and non-users ( N = 82) from two cohorts were collected. Control variables such as demographical data, attitude towards the learning subject, computer literacy, motivation, learning effort and available infrastructure were captured by means of a self-report. As a learning outcome, the grade in the final exam was included. For the VLE-users, the mean performance in the VLE was taken as a predictor for success in the final exam. Two different groups of VLE-users were observed and classified into ’light and ’heavy’ users. The results showed that among those students who had spent two or more hours per week for pre- and post processing of the lectures, ‘heavy’ VLE-users performed better than non-users in the final exam. Additionally, the ‘heavy’ users’ performance in the VLE was the best predictor for the grade in the final exam. We discuss the results in the context of self-regulated learning competence.
AbstractList This study examines a blended learning setting in an undergraduate course in psychology. A virtual learning environment (VLE) complemented the face-to-face lecture. The usage was voluntary and the VLE was designed to support the learning process of the students. Data from users (Naa=aa80) and non-users (Naa=aa82) from two cohorts were collected. Control variables such as demographical data, attitude towards the learning subject, computer literacy, motivation, learning effort and available infrastructure were captured by means of a self-report. As a learning outcome, the grade in the final exam was included. For the VLE-users, the mean performance in the VLE was taken as a predictor for success in the final exam. Two different groups of VLE-users were observed and classified into 'light and 'heavy' users. The results showed that among those students who had spent two or more hours per week for pre- and post processing of the lectures, 'heavy' VLE-users performed better than non-users in the final exam. Additionally, the 'heavy' users' performance in the VLE was the best predictor for the grade in the final exam. We discuss the results in the context of self-regulated learning competence.
This study examines a blended learning setting in an undergraduate course in psychology. A virtual learning environment (VLE) complemented the face-to-face lecture. The usage was voluntary and the VLE was designed to support the learning process of the students. Data from users (N = 80) and non-users (N = 82) from two cohorts were collected. Control variables such as demographical data, attitude towards the learning subject, computer literacy, motivation, learning effort and available infrastructure were captured by means of a self-report. As a learning outcome, the grade in the final exam was included. For the VLE-users, the mean performance in the VLE was taken as a predictor for success in the final exam. Two different groups of VLE-users were observed and classified into "light" and "heavy" users. The results showed that among those students who had spent two or more hours per week for pre- and post processing of the lectures, "heavy" VLE-users performed better than non-users in the final exam. Additionally, the "heavy" users' performance in the VLE was the best predictor for the grade in the final exam. We discuss the results in the context of self-regulated learning competence. (Contains 6 tables and 5 figures.)
This study examines a blended learning setting in an undergraduate course in psychology. A virtual learning environment (VLE) complemented the face-to-face lecture. The usage was voluntary and the VLE was designed to support the learning process of the students. Data from users ( N = 80) and non-users ( N = 82) from two cohorts were collected. Control variables such as demographical data, attitude towards the learning subject, computer literacy, motivation, learning effort and available infrastructure were captured by means of a self-report. As a learning outcome, the grade in the final exam was included. For the VLE-users, the mean performance in the VLE was taken as a predictor for success in the final exam. Two different groups of VLE-users were observed and classified into ’light and ’heavy’ users. The results showed that among those students who had spent two or more hours per week for pre- and post processing of the lectures, ‘heavy’ VLE-users performed better than non-users in the final exam. Additionally, the ‘heavy’ users’ performance in the VLE was the best predictor for the grade in the final exam. We discuss the results in the context of self-regulated learning competence.
Audience Higher Education
Author Stricker, Daniel
Wissmath, Bartholomäus
Weibel, David
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Snippet This study examines a blended learning setting in an undergraduate course in psychology. A virtual learning environment (VLE) complemented the face-to-face...
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SubjectTerms Blended learning
C (programming language)
Comparative Analysis
Computer Assisted Instruction
Computer Literacy
Data Collection
Demographics
Education
Educational Environment
Evaluation methodologies
Grades (Scholastic)
Interactive learning environments
Learning
Learning Processes
Lecture Method
Lectures
Mathematical analysis
Mathematical models
Media in education
Psychology
Quality
Students
Tests
Undergraduate Students
Universities
Title Efficient learning using a virtual learning environment in a university class
URI https://dx.doi.org/10.1016/j.compedu.2010.09.012
http://eric.ed.gov/ERICWebPortal/detail?accno=EJ904359
https://www.proquest.com/docview/855684146
Volume 56
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