Personalized E-Learning Based on Ant Colony Optimization

Abstract

With the advancement in technology, the approach to learning has also been modified. “Standardization” and “One-size-fits-all” has become an outdated concept. To adjust to the changing learning approaches, e-learning came into being, but this was not as per the knowledge and intelligence of users. This created a hurdle in the achievement of better learning and acquisition of skills. This calls for the provision of personalization in e-learning. Successful implementation of personalized e-learning in the present education system will lead to better and faster learning by adapting as per the preferences and knowledge of students. The core idea behind this research is to make an application using Android, which provides a personalized and adaptable route of e-learning using Ant Colony Optimization and recommendations from similar peers. This research will cater to the needs of many students, and it will help in decreasing the time taken to complete any subject or course. It will also help in attaining better and efficient learning as the learning route is determined as per the user. Also, the collection of records of every user will help in improving efficiency and accuracy in the determination of the learning path. The developed app aiming for adaptative e-learning can act as a promising solution during the Covid-19 scenario.