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 in | Computers and education Vol. 56; no. 2; pp. 495 - 504 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.02.2011
Elsevier |
Subjects | |
Online Access | Get full text |
ISSN | 0360-1315 1873-782X |
DOI | 10.1016/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. |
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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 |
Author_xml | – sequence: 1 givenname: Daniel surname: Stricker fullname: Stricker, Daniel email: daniel.stricker@psy.unibe.ch organization: Department of Psychology, University of Bern, Muesmattstrasse 45, 3012 Bern, Switzerland – sequence: 2 givenname: David surname: Weibel fullname: Weibel, David email: david.weibel@psy.unibe.ch organization: Department of Psychology, University of Bern, Muesmattstrasse 45, 3012 Bern, Switzerland – sequence: 3 givenname: Bartholomäus surname: Wissmath fullname: Wissmath, Bartholomäus email: bartholomaeus.wissmath@psy.unibe.ch organization: Department of Psychology, University of Bern, Muesmattstrasse 45, 3012 Bern, Switzerland |
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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 |
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