Asian Journal of Computer Science and Technology (AJCST)
Personalization of E-Learning Systems: Determination of Most Preferred Learning Style Using Conjoint AnalysisAuthor : J. Saul Nicholas and F. Sagayaraj Francis
Volume 7 No.3 October-December 2018 pp 91-95
Identifying user preferences is a very important activity before offering a suggestion or a product. E-learning systems also follow suit in identifying the user preferences of learning style before offering the e-learning contents. There are several methods discussed in the literature for identifying the user preferences for e-learning contents. This paper presents a new method for the same purpose. The core of the new method is Conjoint Analysis, which is based on the type of the contents, preferred volume for each type of content and the ranking for the various combinations of the contents and their preferred volumes. The outcome of this method is the most preferred learning style of an individual learner.
Adaptive Systems, Personalized Learning, Learning Styles, Adaptive Framework, Conjoint Analysis, FSLSM, Time Factor, Frequency Factor
 R. Panneerselvam, Research Methodology, Second Edition, Prentice-Hall of India, New Delhi, 2014.
 A. Hamdy Taha, Operations research: an introduction, Prentice Hall of India, New Delhi, 1999.
 S. C. Gupta and V. K. Kapoor, Fundamentals of Mathematical Statistics, Sultan Chand & Sons, New Delhi, India, 2014.
 K. Chrzan and B. Orme, “An Overview and Comparison of Design Strategies for Choice Based Conjoint Analysis”, Sawtooth Software Research Paper Series, 2000.
 R. VithalaRao, Applied Conjoint Analysis, Springer, 2014.
 D.Agbenyegah, “Tell Me What You Want: Conjoint Analysis Made Simple Using SAS”, SAS Global Forum, Paper 3042, 2015.
 B. Vermeulen, P. Goos and M. Vande broek, “Models and optimal designs for conjoint choice experiments including a no choice option”, International Journal of Research in Marketing, Elsevier, Vol. 25, No. 2, pp. 94-103, 2008.
 D. Raghavarao, B. James Wiley and P. Chitturi, Choice-Based Conjoint Analysis, Models and Designs, Taylor and Francis Group, 2010.