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The Research of Applying Big Data to Improving Moocs Learning Analytics:An Empirical Study of College Calculus(1/3)
Yang, Stephen J.H.
(PI)
Department of Computer Science and Information Engineering
Overview
Fingerprint
Research output
(2)
Project Details
Status
Finished
Effective start/end date
1/08/17
→
31/07/18
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Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Student Academic Performance
Keyphrases
100%
Learning Analytics
Keyphrases
87%
Principal Components
Computer Science
66%
Multiple Linear Regression
Keyphrases
50%
Principal Coordinate Analysis (PCoA)
Keyphrases
50%
Early Prediction
Keyphrases
50%
Academic Performance
Keyphrases
50%
Blended Learning
Keyphrases
50%
Research output
Research output per year
2018
2018
2018
2
Article
Research output per year
Research output per year
Applying learning analytics for the early prediction of students' academic performance in blended learning
Lu, O. H. T., Huang, A. Y. Q., Huang, J. C. H., Lin, A. J. Q., Ogata, H. &
Yang, S. J. H.
,
2018
,
In:
Educational Technology and Society.
21
,
2
,
p. 220-232
13 p.
Research output
:
Contribution to journal
›
Article
›
peer-review
Learning Analytics
100%
Student Academic Performance
100%
Blended Learning
100%
Early Prediction
100%
Academic Performance
100%
217
Scopus citations
Predicting students’ academic performance using multiple linear regression and principal component analysis
Yang, S. J. H.
, Lu, O. H. T., Huang, A. Y. Q., Huang, J. C. H., Ogata, H. & Lin, A. J. Q.,
Jan 2018
,
In:
Journal of Information Processing.
26
,
p. 170-176
7 p.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
Principal Coordinate Analysis (PCoA)
100%
Student Academic Performance
100%
Multiple Linear Regression
100%
Principal Components
100%
Component Analysis
100%
70
Scopus citations