A Learning Analytical Model for Higher Educational Data Using Artificial Neural Networ

Abstract

Learning analytics is an emerging educational technology that involves measuring, collecting, analyzing and reporting learner-related data to monitor and predict learner’s academic performance. Learning analytics provides early interventions to improve learners’ learning and performance. This study aims to design and develop A learning analytics model by analyzing learner-related information based on artificial neural network using MATLAB to predict the variable that determine the students’ performance rate. A number of variables that may possibly influence the performance of students’ in e-learning are outlined. Such variables are login into the system, scorm view, assignment attempt, resource view and quiz exam score of students’ in the online course of introduction to civic and ethical studies in Law department students are used as input variables for the ANN model. A model based on the Multilayer Perceptron and feed-forward artificial neural network Topology to develop the architecture of the research. The successful prediction rate of variables that determine the students’ performance using ANN model (Multilayer Perceptron and feed-forward artificial neural network) was 99.3%.