An Automated Intelligent E-learning Approach for Ensuring Learning Outcomes

Abstract

E-learning is an innovative and effective way to perceive knowledge in the modern world. The web-based interactive system has become one of the most common needs in our generation. Thus E-learning has achieved enormous popularity in the world since this decade. Most of the universities are using web-based systems to provide interactive systems to students which can make a faster communication to grow up the knowledge in every academic section. Many advantages come out with the adoption of e-learning systems majorly paperless environment, low cost, freedom of time and geographic locations, web materials are accessible in any order, in any devices even in smartphones. In advanced countries, e-learning systems play a major role in an economy to raise productive output in the industries without having paid a huge amount for personal staff that is locating physically and also provides big advantages to peoples of developed countries who cannot attend physically courses either afford experts in a professional domain. This is an immense achievement of e-learning based systems to promote education online. In this dissertation, it has been proposed some helpful and efficient technique to design a web-based intelligent e-learning system for academic institutions like university and high school. The learning contents may be presented in different advantageous ways to teach any topic efficiently. Contents can be presented in text, video, audio or in form of animation. Apart from that, also a model is prepared to ensure the learning outcome. Evaluation part of an e-learning system is very critical. Most of the e-learning website use multiple-choice questions for evaluation which cannot guarantee learning outcome because a student may get good marks by with random selection. Here, some proficient ways are proposed which would enforce a student to learn. In artificial intelligence based games player follows several levels where players go to the final level step by step. In this proposed model follows the same to teach a student, that means system also examines the student step by step. That is why a student can hardly pass only by selecting the answer randomly. This system has analyzed the design of proposed e-learning system consists of use case diagrams, sequence diagrams, class diagrams and database diagrams. As an intelligent system, this system is going to apply some machine learning techniques like "Multiple Linear Regression Algorithm" which not only guide us to define most effective exam approach but also will ensure student outcome.