Mobile Learning Recommender System based on Learning Styles

Saryar, Shivam and Kolekar, Sucheta and Pai, Radhika M and Pai, Manohara M.M. (2019) Mobile Learning Recommender System based on Learning Styles. In: Soft Computing and Signal Processing, 2019, 22/06/2018, Hyderabad.

[img] PDF
1416.pdf - Published Version
Restricted to Registered users only

Download (411kB) | Request a copy


With the evolution of the Internet era in today’s world, more and more learners now have the option of using multimedia to engage in a learning environment forexamplevideos, text,picturesetc.Theyalsoprefe morecontrolovertheir learning sessions, i.e. being able to choose which topics, which mode of multimedia etc., as that is one thing which classroom learning cannot provide. Classroom learn ingdoesnotgivethefreedomofchoosingapace,alearningstyleorasuitable medium for learning. Moreover, the existing teaching methods does not encourage from exploring other possible means of learning which could turn out to be more helpful. Also, classroom learning or learning over the Internet, most learners are stillnotwellawareoftheirlearningstyles.Inthispaper,anapproachisproposedto develop a Mobile Learning Android application which implements a learning style model to identify the learning styles of each user. Based on the identified learning style as well as the user’s other in-app activities, it uses a recommendation system to recommend relevant course material to the user which s/he might find useful. Thisgivesthelearneragreaterinsightintohis/herownlearningpatternandbecome self aware about what mode of learning suits them more or what might be more useful to them. This mobile learning application provides seamless availability of course material to the learners on the go. As opposed to the e-learning platforms, thisapproachhasbeenimplementedasamobileapplication,whichallowslearners to access course material whenever, wherever they want

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: MobileLearning,Felder-SilvermanLearningStyleModel,Recommendation System, Learning Styles, Index of Learning Styles.
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 04 Jul 2019 09:43
Last Modified: 04 Jul 2019 09:43

Actions (login required)

View Item View Item