Mining Key Formative Assessment Rules based on Learner Profiles for Web-based Learning Systems

Currently, online learning is becoming more and more important, but there is still lack of an effective learning performance assessment mechanism on it. Traditional summative evaluation only considers final learning outcomes. However, the use of learning portfolios in a web-based learning environment can be beneficially applied to record the procedure of the learning, evaluate the learning performance of learners, and feed information back to learners in ways that enable the learner to learn better. Accordingly, this study proposes a formative assessment approach using data mining techniques to identify the key formative assessment rules based on the web-based learning portfolios of an individual learner. Moreover, the factor analysis provides benefit in terms of obtaining simple and clear learning assessment rules.

[1]  Hsiao-Fan Wang,et al.  Factor analysis in data mining , 2005 .

[2]  M. Narasimha Murty,et al.  Genetic K-means algorithm , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[3]  Witold Pedrycz,et al.  Fuzzy clustering with partial supervision , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[4]  Petr Cintula,et al.  Fuzzy class theory , 2005, Fuzzy Sets Syst..

[5]  C. S. George Lee,et al.  Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems , 1996 .

[6]  Tzung-Pei Hong,et al.  Mining association rules from quantitative data , 1999, Intell. Data Anal..

[7]  Chih-Ming Chen,et al.  Learning Performance Assessment Approach Using Web-Based Learning Portfolios for E-learning Systems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[8]  Chih-Ming Chen,et al.  Personalized curriculum sequencing utilizing modified item response theory for web-based instruction , 2006, Expert Syst. Appl..

[9]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[10]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .