Effectiveness of Personalised Learning Paths on Students Learning Experiences in an e-Learning Environment
Mohammad Issack Santally [m.santally@uom.ac.mu],
Virtual Centre for Innovative Learning Technologies, University of Mauritius, Mauritius,
Alain Senteni, School of e-Education, Hamdan Bin Mohammed e-University, United
Arab Emirates
Abstract
Personalisation of e-learning environments is an interesting research area in which the learning experience of learners is generally believed to be improved when his or her personal learning preferences are taken into account. One such learning preference is the V-A-K instrument that classifies learners as visual, auditory or kinaesthetic. In this research, the outcomes of an experiment are described after students in the second year of university were exposed to a unit that was redesigned to fit in the V-A-K learning styles. It was found that the was no performance improvement when the students were exposed to that specific personalised learning environment and it was surprisingly noted from the statistical evidence that they underperformed in general both with respect to their previous performances and their performances in the same course but for a different unit that served as a control. The personalisation framework used an adaptive method to generate learning paths for each student and it was found that the method performed satisfactorily in its selection process. The findings of this research adds to the existing body of discourse and consolidates the belief that learning styles as determined by self-assessment instruments do not necessarily improve performances. On the other hand, it brings an interesting observation with respect to e-learning environments and the use of multimedia. A pedagogical method of instructional design that brings a sound balance in the use of different elements can indeed be of universal application and each and every learner will find his or her space in it. Indeed working towards more flexibility and adaptability of the environment might be a better approach rather than to work on the adaptivity of the environment.
If you would like to read the entire contribution, please click here.