Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3458
Title: PREDICTING LEARNERS’ ATTITUDE AND PREFERNCE IN E-LEARNING USING ARTIFICIAL NEURAL NETWORKS
Authors: B, Shanthini
Keywords: E-Learning
E-learners
Attitude and Preference
Multilayer Perceptron (MLP)
Issue Date: Jan-2021
Publisher: International Journal of Management and Social Science Research Review
Abstract: E-Learning is a web based learning that uses information and communication technology as a platformto facilitate teaching and learning process for e-learners’. The present study felt the need to predict learners’ attitude and preference in E-Learning using artificial neural network (ANN) which was specifically designed to analyze non-linear temporal series through multilayer perceptron (MLP). The research was conducted among 125 respondents of Vellalar College for Women (Autonomous), Erode, of self financing wing with the students who have completed minimum of two E-Learning modules and underwent assessment. The study is descriptive in nature and ensures random sampling method for data collection. A well designed questionnaire was prepared and data was collected through Google forms. The tools used for the analysis include descriptive statistics and artificial neural network (ANN) with the statistical package SPSS 16.0. It was found from the classification table that accuracy rate was high, with 82.8% in classifying the e-learners’ attitude in recommending E-Learning to others in “yes” and “no” category. The study also recommends future researchers to concentrate on diverse academic perspectives and with more samples.
URI: http://ijmsrr.com/downloads/130120211.pdf
ISSN: 2349-6746
Appears in Collections:International Journals

Files in This Item:
File Description SizeFormat 
PREDICTING LEARNERS’ ATTITUDE AND PREFERNCE IN E-LEARNING USING ARTIFICIAL NEURAL NETWORKS.docx265.32 kBMicrosoft Word XMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.