Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University
This study was conducted to develop a predictive model of the learning productivity of the students collaborating in the CSCL platform. This study integrates three main theories and two models, namely; Transactional Distance Theory, Social Presence Theory, Online Collaborative Learning Theory follow...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2015
|
Online Access: | http://psasir.upm.edu.my/id/eprint/65642/1/FPP%202015%2055IR.pdf http://psasir.upm.edu.my/id/eprint/65642/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.upm.eprints.65642 |
---|---|
record_format |
eprints |
institution |
Universiti Putra Malaysia |
building |
UPM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Putra Malaysia |
content_source |
UPM Institutional Repository |
url_provider |
http://psasir.upm.edu.my/ |
language |
English |
description |
This study was conducted to develop a predictive model of the learning productivity of the students collaborating in the CSCL platform. This study integrates three main theories and two models, namely; Transactional Distance Theory, Social Presence Theory, Online Collaborative Learning Theory following the Constructivist School of Thought, Input-Process-Output Model and The Learning Productivity Model.The independent variables were the students’ self-construal, students’ prior CSCL experience and technology’s usability. The learning productivity was measured by the learning performance, learning gain and learning satisfaction of the students. The level of collaboration was examined as the mediating factor between the independent and dependent variables. The level of collaboration was analysed via quantitative discourse analysis. In this descriptive survey study, the survey was administered using a questionnaire, adapted from previously validated scales. The validity of the instrument was approved by a panel of subject-matter experts. A pilot study was rendered on 24 undergraduate students which yielded Cronbach’s alpha coefficient ranging from 0.87 to 0.3 indicating good reliability. Data were then gathered from 103 undergraduate distance learners, who formed 24 different groups from 11 subjects, selected using cluster sampling. From discourse analysis, 12 groups were found to be highly collaborative among each other, where they had participated in the online discussion roughly equally among each other. Multiple regression analysis was conducted to identify the predictors of the highly collaborated groups (12 groups, n=43). Structural equation modeling (SEM) was employed to test the overall fit for the proposed model (24 groups, n=103). The current study produced several significant findings apart from generated a model predicting the learning productivity of distance learners in a computer-supported collaborative learning platform. Five out of seven hypotheses were supported where the paths were proven significant. The significant paths were: 1) students’ self-construal
has a significant effect on the levels of collaboration of the distance learners (β=-0.743,
p>.001); 2) prior CSCL experience has a significant effect on the levels of
collaboration of distance learners (β=-0.610, p<.001); 3) technology’s usability has a
significant effect on the levels of collaboration (β=-0.651, p<.001); 4) the levels of
collaboration have a significant effect on the learning productivity of the distance
learners (β=.45, p<.001); 5) the levels of collaboration have a full mediating effect on
prior CSCL experience and learning productivity (β=-0.642, p<.001). The negative
standardized estimates were due to the highest level of collaboration was represented
with score 1 and vice versa.
However, two hypotheses were not supported, which were: 1) the levels of
collaboration did not have a full mediating effect on students’ self-construal and
learning productivity; and, 2) the levels of collaboration did not have a full mediating
effect on technology’s usability and learning productivity. The theoretical model was
able to explain 76.1% of the variance of the distance learner’s learning productivity
collaborating on the CSCL platform.
Hence, the study proposed that the students’ self-construal, students’ prior CSCL
experience and technology’s usability will aid the students in achieving higher levels of
collaboration, and in turn gain a favourable learning productivity. This study had
looked within the collaboration among the distance learners by analyzing the levels of
collaboration, and relating these levels of collaboration to the learning productivity of
the distance learners. This study can contribute towards a more empirical
understanding of learning productivity in an online collaborative platform, thus
providing productive directions to the stakeholders in achieving the nation of lifelong
learning and globalised online learning. |
format |
Thesis |
author |
Shaikh Ali, Siti Haryani |
spellingShingle |
Shaikh Ali, Siti Haryani Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University |
author_facet |
Shaikh Ali, Siti Haryani |
author_sort |
Shaikh Ali, Siti Haryani |
title |
Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University |
title_short |
Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University |
title_full |
Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University |
title_fullStr |
Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University |
title_full_unstemmed |
Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University |
title_sort |
predictive model for learning productivity in a computer-supported collaborative learning platform among students in a malaysian public university |
publishDate |
2015 |
url |
http://psasir.upm.edu.my/id/eprint/65642/1/FPP%202015%2055IR.pdf http://psasir.upm.edu.my/id/eprint/65642/ |
_version_ |
1643838367154044928 |
spelling |
my.upm.eprints.656422018-10-04T08:29:36Z http://psasir.upm.edu.my/id/eprint/65642/ Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University Shaikh Ali, Siti Haryani This study was conducted to develop a predictive model of the learning productivity of the students collaborating in the CSCL platform. This study integrates three main theories and two models, namely; Transactional Distance Theory, Social Presence Theory, Online Collaborative Learning Theory following the Constructivist School of Thought, Input-Process-Output Model and The Learning Productivity Model.The independent variables were the students’ self-construal, students’ prior CSCL experience and technology’s usability. The learning productivity was measured by the learning performance, learning gain and learning satisfaction of the students. The level of collaboration was examined as the mediating factor between the independent and dependent variables. The level of collaboration was analysed via quantitative discourse analysis. In this descriptive survey study, the survey was administered using a questionnaire, adapted from previously validated scales. The validity of the instrument was approved by a panel of subject-matter experts. A pilot study was rendered on 24 undergraduate students which yielded Cronbach’s alpha coefficient ranging from 0.87 to 0.3 indicating good reliability. Data were then gathered from 103 undergraduate distance learners, who formed 24 different groups from 11 subjects, selected using cluster sampling. From discourse analysis, 12 groups were found to be highly collaborative among each other, where they had participated in the online discussion roughly equally among each other. Multiple regression analysis was conducted to identify the predictors of the highly collaborated groups (12 groups, n=43). Structural equation modeling (SEM) was employed to test the overall fit for the proposed model (24 groups, n=103). The current study produced several significant findings apart from generated a model predicting the learning productivity of distance learners in a computer-supported collaborative learning platform. Five out of seven hypotheses were supported where the paths were proven significant. The significant paths were: 1) students’ self-construal has a significant effect on the levels of collaboration of the distance learners (β=-0.743, p>.001); 2) prior CSCL experience has a significant effect on the levels of collaboration of distance learners (β=-0.610, p<.001); 3) technology’s usability has a significant effect on the levels of collaboration (β=-0.651, p<.001); 4) the levels of collaboration have a significant effect on the learning productivity of the distance learners (β=.45, p<.001); 5) the levels of collaboration have a full mediating effect on prior CSCL experience and learning productivity (β=-0.642, p<.001). The negative standardized estimates were due to the highest level of collaboration was represented with score 1 and vice versa. However, two hypotheses were not supported, which were: 1) the levels of collaboration did not have a full mediating effect on students’ self-construal and learning productivity; and, 2) the levels of collaboration did not have a full mediating effect on technology’s usability and learning productivity. The theoretical model was able to explain 76.1% of the variance of the distance learner’s learning productivity collaborating on the CSCL platform. Hence, the study proposed that the students’ self-construal, students’ prior CSCL experience and technology’s usability will aid the students in achieving higher levels of collaboration, and in turn gain a favourable learning productivity. This study had looked within the collaboration among the distance learners by analyzing the levels of collaboration, and relating these levels of collaboration to the learning productivity of the distance learners. This study can contribute towards a more empirical understanding of learning productivity in an online collaborative platform, thus providing productive directions to the stakeholders in achieving the nation of lifelong learning and globalised online learning. 2015-06 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/65642/1/FPP%202015%2055IR.pdf Shaikh Ali, Siti Haryani (2015) Predictive model for learning productivity in a computer-supported collaborative learning platform among students in a Malaysian Public University. PhD thesis, Universiti Putra Malaysia. |
score |
13.214268 |