DocumentCode :
578450
Title :
A mashup-based adaptive learning system
Author :
Chang, Yi-Hsing ; Chen, Yen-Yi
Author_Institution :
Dept. of Inf. Manage., Southern Taiwan Univ., Taiwan
Volume :
5
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
1721
Lastpage :
1726
Abstract :
This study aims to build, using Felder and Silverman´s Learning Style Theory and Mashup technology, an adaptive learning system to help students improve their learning effect. In this system, Felder and Silverman´s Learning Style Theory is used to gain an understanding of students´ learning styles to enable them to engage in adaptive learning according to their respective learning styles. Additionally, this learning system also allows learners to use a Mashup search engine to search for related supplementary teaching materials to achieve better learning results. After its completion, the learning system was used to conduct an experiment on the freshmen of two computer programming classes in the university´s Information Management Department to compare the difference in students´ learning effect. Moreover, a questionnaire was designed based on Technology Acceptance Model to carry out qualitative and quantitative analyses. The results showed that compared with the control group, students in the experiment group made more significant improvement in their academic performance and all of them had a positive evaluation for the learning system.
Keywords :
computer aided instruction; search engines; Felder and Silverman learning style theory; computer programming classes; e-learning; information management department; learning effect; mashup search engine; mashup-based adaptive learning system; supplementary teaching materials; Abstracts; Blogs; Education; Mashups; Materials; Social network services; Mashup; adaptive learning; learning style; programming language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2160-133X
Print_ISBN :
978-1-4673-1484-8
Type :
conf
DOI :
10.1109/ICMLC.2012.6359634
Filename :
6359634
Link To Document :
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