A Knowledge Engineering Method to Represent and Optimize Learning Processes and its Empirical Validation

Author

Knauf, Rainer ; Sakurai, Yoshitaka ; Takada, Kohei ; Tsuruta, Setsuo

Author_Institution

Fac. of Comput. Sci. & Autom., Ilmenau Univ. of Technol., Ilmenau, Germany

fYear

2010

fDate

15-18 Dec. 2010

Firstpage

203

Lastpage

210

Abstract

Modeling, processing, evaluating and refining processes with humans involved like (not only, but also e-) learning is an exciting new application of Knowledge Engineering. A formerly developed concept called storyboarding has been applied at Tokyo Denki University to model the various ways to study at this university and visualize them in a graphical way, that allows to keep an overview by a hierarchy of nested graphs. The paper reports the development and validation of a data mining technology to estimate success chances of curricula based on storyboarding. Further, it discusses chances to improve these results by implementing a formerly introduced learner profiling concept that represents the students´ individual properties, talents and preferences for personalized data mining.

Keywords

computer aided instruction; data mining; data visualisation; educational institutions; graph theory; learning systems; Tokyo Denki university; curricula; data mining; e- learning; empirical validation; evaluating process; graphical visualization; knowledge engineering; learner profiling; learning process optimization; nested graph; refining process; storyboarding; student individual property; Bars; Data mining; Decision trees; Estimation; Knowledge engineering; Training; data mining; modeling Processes with humans involved; storyborading; validation;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal-Image Technology and Internet-Based Systems (SITIS), 2010 Sixth International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-9527-6

Electronic_ISBN

978-0-7695-4319-2

Type

conf

DOI

10.1109/SITIS.2010.43

Filename

5714553