TY - JOUR
T1 - The success of ePortfolio-based programming learning style diagnosis
T2 - Exploring the role of a heuristic fuzzy knowledge fusion
AU - Huang, Angus F.M.
AU - Wu, John T.H.
AU - Yang, Stephen J.H.
AU - Hwang, Wu Yuin
N1 - Funding Information:
This work is supported by National Science Council, Taiwan under Grants NSC98-2511-S-008-006-MY3, NSC98-2511-S-008-007-MY3, NSC99-2511-S-008-006-MY3, and the Research Center for Science & Technology for Learning of the University System of Taiwan.
PY - 2012/8
Y1 - 2012/8
N2 - Computer programming is a high-level thinking activity. In the educational area, using learning styles to understand how students learn is a significant issue. The electronic Portfolio (ePortfolio) is a popular educational management and assessment tool. Unfortunately, few researchers investigate programming learning style diagnosis. This paper addresses this gap in research: this study constructs an ePortfolio-based programming learning style diagnosis to detect students' styles. The fusion of multiple fuzzy-based diagnosis knowledge is the main contribution of this work. This paper built a heuristic optimization method to integrate multiple diagnosis knowledge bases. Performance evaluations and empirical studies were implemented to verify the proposed algorithm and fusion solution. Experimental results showed that the proposed heuristic optimization firms the validity and stability of a diagnostic system, and the ePortfolio-based programming learning style diagnosis is highly accepted by students. Furthermore, teachers agreed that the knowledge fusion mechanism and diagnosis system were usable.
AB - Computer programming is a high-level thinking activity. In the educational area, using learning styles to understand how students learn is a significant issue. The electronic Portfolio (ePortfolio) is a popular educational management and assessment tool. Unfortunately, few researchers investigate programming learning style diagnosis. This paper addresses this gap in research: this study constructs an ePortfolio-based programming learning style diagnosis to detect students' styles. The fusion of multiple fuzzy-based diagnosis knowledge is the main contribution of this work. This paper built a heuristic optimization method to integrate multiple diagnosis knowledge bases. Performance evaluations and empirical studies were implemented to verify the proposed algorithm and fusion solution. Experimental results showed that the proposed heuristic optimization firms the validity and stability of a diagnostic system, and the ePortfolio-based programming learning style diagnosis is highly accepted by students. Furthermore, teachers agreed that the knowledge fusion mechanism and diagnosis system were usable.
KW - Evaluation methodologies
KW - Intelligent tutoring systems
KW - Programming and programming languages
KW - Teaching/learning strategies
UR - http://www.scopus.com/inward/record.url?scp=84862778893&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2012.01.212
DO - 10.1016/j.eswa.2012.01.212
M3 - 期刊論文
AN - SCOPUS:84862778893
SN - 0957-4174
VL - 39
SP - 8698
EP - 8706
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - 10
ER -