Modelling the Effectiveness of Curriculum in Educational Systems Using Bayesian Networks

TL;DR

This paper develops a Bayesian network-based model to evaluate and simulate the effectiveness of curriculum planning in online education by analyzing user behavior and success rates.

Contribution

It introduces a novel Bayesian network model for curriculum effectiveness assessment based on server logs and student success data.

Findings

Parameters significantly influence curriculum success

Model accurately predicts student success rates

Insights for optimizing curriculum design

Abstract

In recent years, online education has been considered as one of the most widely used IT services. Researchers in this field face many challenges in the realm of Electronic learning services. Nowadays, many researchers in the field of learning and eLearning study curriculum planning, considering its complexity and the various numbers of effective parameters. The success of a curriculum is a multifaceted issue which needs analytical modelling for precise simulations of the different learning scenarios. In this paper, parameters involved in the learning process will be identified and a curriculum will be propounded. Furthermore, a Curriculum model will be proposed using the behavior of the user, based on the logs of the server. This model will estimate the success rate of the users while taking courses. Authentic Bayesian networks have been used for modelling. In order to evaluate the proposed model, the data of three consecutive semesters of 117 MS IT Students of E-Learning Center of Amirkabir University of Technology has been used. The assessment clarifies the effects of various parameters on the success of curriculum planning.