Educatorr: Personalized Study Material Analysis Framework for E-Learning

Abstract

In the current Internet Era, we have observed the ongoing evolution of the Internet over the last few decades. The development of growing volumes of online knowledge resources had an impact on the industry of education, making E-Learning becomes more engaging and effective. This eventually contributed to an issue of overloading knowledge. When students are unable to handle that amount of study materials they obtain in various formats and have trouble in maintaining with their stressful lifestyles at the same period. Leading to this with weak organizational and time management skills, present-day students have a tight timetable to handle all their educational and personal activities. In the attempt to resolve this problem, a tool implemented to analysis study materials that incorporates a novel strategy to text summarization and information extraction. There for ‘Educatorr’ has aimed to present a proper solution to go through and get the knowledge of the study material in a limited time span. In order to corporate with summarization and information extraction, algorithms are designed and implemented based on the observations of the literature review. During a crucial evaluation of intend end users and professional specifications, an extensible architecture was developed. As a result, aiming high accuracy as well as performance tool with the combination of both NLP and semantic information approaches. 'Educatorr' has reflected in remarkable feedback from both professionals and end users with highly efficient rates.