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Business Management Education in India has shown an upward growth trend in the last couple of decades. Due to the diverse nature of the course, students from diverse academic backgrounds are being admitted to the course. Therefore, differences in students’ abilities and their learning styles have a significant effect on their learning outcomes. Meanwhile, with the development of learning technologies, learners can be provided a more effective learning environment to optimise their learning. The purpose of this study was to develop a model to automatically detect the students’ learning styles from their personal, academic and social media data and make recommendations for students, teachers, educators and administrators for overall improvement of learning outcomes. Data analysis in this research was represented using data collected from post-graduate business management students in India. A 10-fold cross-validation was used to create and test the models. The data were analysed by R and R-Studio. Classification accuracy, Precision, Recall, Kappa, ROC curve and F measure were observed. The results showed that the accuracy of classification by the C4.5 technique had the highest value at 95.7%, and it could be applied to develop Felder-Silverman’s learning style while taking into consideration students’ academic, personal information and social media preferences. [ABSTRACT FROM AUTHOR]

Over the last few years there has been an increased emphasis on conceptualising, developing, and implementing virtual Learning initiatives across the Indian education sector. Effective and successful use of Virtual Learning Environments (VLEs) in academic setting requires identifying and solving many important social and behavioural issues. Without identifying and addressing these issues, their use can compound the mistakes of the past and leave the learner with a passive, un-engaging experience, leading to incomplete learning and low performance. Therefore, educators are required to recognise learner’s attitude, readiness, and learning style to take advantage of VLE. This study was conducted to find interrelationship of student attitude, readiness, and learning style towards the effective use of VLE. A total of 240 students who are using any form of VLE for their learning and research volunteered for the research, and the scales were filled via the convenience sampling method. The scales of learning readiness, attitude, and learning style were administered to the participants. The relationship among the variables of the research and the research hypotheses for the model were tested using different statistical tools like correlation,t-test and regression. The research result revealed that there is a correlation among learning readiness, attitude, and learning style, and each of these factors influence the effective use of VLE. [ABSTRACT FROM PUBLISHER]