The week's pick
Random Articles
Reseach Article
A Soft Computing Approach for User Preference in Web based Learning
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 61 - Number 21 |
| Year of Publication: 2013 |
| Authors: L. Jayasimman, E. George Dharma Prakash Raj |
10.5120/10205-5082
|
L. Jayasimman, E. George Dharma Prakash Raj . A Soft Computing Approach for User Preference in Web based Learning. International Journal of Computer Applications. 61, 21 ( January 2013), 25-29. DOI=10.5120/10205-5082
Abstract
The web-based learning system has emerged as a new means of skill training and knowledge acquisition, encouraging both academia and industry to invest resources in the adoption of this system. Users have been widely recognized as being a key group in influencing the adoption of such systems. Thus, their attitudes toward this system are pivotal. It is required to design the web layout to user satisfaction based on the fields of human–computer interaction and information systems. Cognitive theory is widely used to predict the effectiveness of the web based and multimedia learning. Questionnaires are one common form of measuring cognition. This study investigates to identify a user's need based on the cognitive behavior of the user based on the questionnaire. The cognitive attributes are used as the training input for the Multilayer Perceptions and proposed parallel Neural Network.
References
- Georgieva, G. , Todorov, G. , &Smrikarov, A. (2003). A model of a Virtual University some problems during its development. In Proceedings of the 4th international conference on Computer systems and technologies: e-Learning. Bulgaria: ACM Press.
- Hamdi, M. S. (2007). MASACAD: A multi-agent approach to information customization for the purpose of academic advising of students. Applied Soft Computing, 7, 746–771.
- Chen, C. M. , Lee, H. M. , & Chen, Y. H. (2005). Personalized e-learning system using item response theory. Computers & Education, 44, 237–255.
- Huang, M. J. , Huang, H. S. , & Chen, M. Y. (2007). Constructing a personalized elearning system based on genetic algorithm and case-based reasoning approach. Expert Systems with Applications, 33, 551–564
- Xu, D. , & Wang, H. (2006). Intelligent agent supported personalization for virtual learning environments. Decision Support Systems, 42, 825–843.
- Economides, A. A. (2005). Personalized feedback in CAT (computer adaptive testing). WSEAS Transactions on Advances in Engineering Education, 3(2), 174–181.
- Economides, A. A. (2006). Emotional feedback in CAT (computer adaptive testing). International Journal of Instructional Technology and Distance Learning 3(2).
- Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285.
- Chandler, P. , &Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332.
- Chandler, P. , &Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied Cognitive Psychology, 10, 151–170.
- Chen, S. Y. ,Magoulas, G. D. &Dimakopoulos, D. (2004). Cognitive styles and users' responses to structured information representation. Journal of the American Society for Information Science and Technology, 56(1), 70–83.
- Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press.
- Niegemann, H. M. (2001). Neuelernmedien: Konzipieren, entwickeln, einsetzen [New instructional media: Conceptualize, develop, implement]. Bern, Switzerland: Huber.
- Susan Feinberg and Margaret Murphy; Applying Cognitive Load Theory to the Design of Web-Based Instruction; Usability Testing and Evaluation Center, Illinois Institute of Technology, Illinois. US.
- Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: ACER Press.
- Gerjets, P. ,&Scheiter, K. (2003). Goal configurations and processing strategies as moderators between instructional design and cognitive load: Evidence from hypertext-based instruction. Educational Psychologist, 38, 33–41.
- Renkl, A. , & Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective. Educational Psychologist, 38, 15–22.
- Jan L Plass; Design and Evaluation of the User Interface of Foreign Language Multimeda software: A Cognitive Approach; Language Learning & Technology, Volume 2, Number 1, July 1998.
- Mihalca, L. , Salden, R. J. , Corbalan, G. , Paas, F. , &Miclea, M. (2011). Effectiveness of cognitive-load based adaptive instruction in genetics education. Computers in Human Behavior, 27(1), 82-88.
- Baylari, A. , &Montazer, G. A. (2009). Design a personalized e-learning system based on item response theory and artificial neural network approach. Expert Systems with Applications, 36(4), 8013-8021.
- Fausett, L. (1994). Fundamentals of neural networks. Englewood Cliffs, NJ: Prentice-Hall.
- Wu, D. , Yang, Z. , & Liang, L. (2006). Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank. Expert Systems with Applications, 31, 108-115.
- Reiterer, H. The development of design aid tools for a human factor based user interface design. International Conference on Man and Cybernetics Systems, 1993. page 361
Index Terms
Keywords