DocumentCode :
2777685
Title :
Finding an optimal learning path in dynamic curriculum sequencing with flow experience
Author :
Katuk, Norliza ; Ryu, Hokyoung
Author_Institution :
Inst. of Inf. & Math. Sci. (IIMS), Massey Univ., Albany, New Zealand
fYear :
2010
fDate :
5-8 Dec. 2010
Firstpage :
227
Lastpage :
232
Abstract :
Computer applications in education are now common to complement a classroom teaching and learning activity. However, a reportedly obscure area in the computer-based instruction is how it can systematically implement the different learning path for the diverse levels of students. In this respect, the dynamic (or adaptive) curriculum sequencing is quick to admit its advantages, and shows the best way forward in the computer-based instruction, matching the content with each individual´s learning performance. This article further discusses this matching process with the `flow´ theory, by which one can draw upon a way to find an optimal learning path in Intelligent Tutoring Systems (ITSs). A computer-based learning system - `IT-Tutor´ was thus implemented and used to empirically investigate this issue further. The results of the study suggested that key to dynamic curriculum sequencing might be setting out optimal learning experience, in conjunction with both the knowledge level and challenge level of each individual.
Keywords :
intelligent tutoring systems; learning (artificial intelligence); IT-Tutor learning system; classroom learning activity; classroom teaching activity; computer-based instruction; dynamic curriculum sequencing; flow experience; intelligent tutoring systems; optimal learning path; Artificial intelligence; Education; Engines; Fluid flow measurement; Human computer interaction; Materials; Tutorials; challenge; computer-based instruction; curriculum sequencing; flow experience; intelligent tutoring systems (ITS);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-9054-7
Type :
conf
DOI :
10.1109/ICCAIE.2010.5735080
Filename :
5735080
Link To Document :
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