Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/25043
Title: Personalised e-learning
Authors: Montebello, Matthew
Keywords: Artificial intelligence
Human computation
Distance education
Open learning
Issue Date: 2017
Publisher: ICEL
Citation: Montebello, M. (2017). Personalised e-learning. 12th International Conference on e-Learning - ICEL17, Orlando. 152-158.
Abstract: This paper reports on a case study whereby a novel e-learning environment was employed and tested during an empirical study within a higher education institution. The proposed dynamic environment investigates the pedagogical effect of personalising e-learning through the combination of a number of techniques, user profiling, customisation and use of social networks. Each technique employed addresses a specific e-learning issue while strongly grounded within a distinctive learning theory. These three theories of learning bring together the three aspects of personal learning environments, portfolios and networks to form an interesting educational phenomenon that is worth investigating from an academic and pedagogical point of view. The case study reports how the empirical study was conducted including participant recruitment, data collection instruments employed, data analysis methods applied, and the full set of results extracted. A strong correlation between the techniques employed and the effectiveness of the proposed e-learning system was reported as the participants indicated an overwhelming bias towards the use of the dynamic environment especially as the learners’ motivation increased over the period of the empirical study. The results also gave a positive indication towards an enhanced effectiveness of the dynamic e-learning environment as the combination of investigated variables have shed light on this intricate and multifaceted matter. The outcomes from this case study are not intended to simplify or curtail the complexities of e-learning; they have barely scratched the surface of an intricate concept that at face value helps and assists future researchers in investigating the evolution of this learning medium.
URI: https://www.um.edu.mt/library/oar//handle/123456789/25043
ISBN: 9781510845183
Appears in Collections:Scholarly Works - FacICTAI

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