Title :
Intelligent reflective e-portfolio framework supported by Problem Based Learning
Author :
Jaryani, Frahang ; Daneshvar, Hooman ; Sahibudin, Shamsul
Author_Institution :
Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Kuala Lumpur, Malaysia
Abstract :
The aim of this paper is to present the role of Artificial Intelligence techniques to enhance reflective e-portfolios quality. Some AI techniques such as expert system; scheduling; Data Mining can support us to enhance our reflective e-portfolios quality. To get better result the designed portfolio has been supported by Problem Based Learning as an effective educational method. These tools together will define new intelligent Reflective e-portfolio that provides intelligent and customized learning method for each student based on their backgrounds and their realities. The final vision of intelligent reflective e-portfolio is to act as an expert to consult students and support them to make Right decisions for their learning complexities.
Keywords :
business data processing; data mining; expert systems; learning (artificial intelligence); scheduling; artificial intelligence techniques; data mining; expert system; intelligent reflective e-portfolio framework; problem based learning; reflective e-portfolio quality; scheduling; Artificial intelligence; Computational modeling; Databases; Educational institutions; Portfolios; Artificial Intelligence; Data Mining; Problem Based Learning; Reflective e-portfolio;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579347
