DEVELOPMENT OF PERSONALISED MOBILE LEARNING SYSTEM USING FUZZY LOGIC TECHNIQUE

Abstract

The increasing development in the world of Information Technology (IT) has improved as well as providing a better way of teaching and learning. Learners now have preferred methods by which they learn and remember what they learned with the use of mobile devices anywhere and anytime. Felder and Silverman model is a common learning model used to determine learners' preference but has been criticized due to the limitation of dichotomous responses in its ILS model. Hence, this research developed a personalised mobile learning system that combines Felder and Silverman learning model with fuzzy logic. In the research, the dichotomous ILS questionnaire was expanded from the standard Two (2) option ILS questionnaire to a Five (5) option questionnaire in order to accommodate learners whose attributes fall in different dimensions. Stegano fuzzy logic was applied to determine the degree of learner’s preference or learning style. The practicality of the developed personalised mobile learning system was carried out as Twenty-two (22) undergraduate students from the College of Education were made to take a test without the use of the model and later with the use of the model. The experimental result showed an increase in students’ performance from 50.95% (without the model) to 81.36% (with the model). The mobility of the system has also been a major advantage to the system user. The system only runs on android operating system and could be ported to run on other platforms. The system could also be enhanced in the future in terms of context aware.