Digital Smart Navigator Design and Implementation of an Academic Map Navigation System

Abstract

In the modern world, students are unable to find their way in the career development process and the academic planning of their studies is also not clear. The proposed paper will create a solution to the practical problems of the current college students by creating an Academic Graph Navigation System that will be implemented with a Digital Intelligence Learning Navigation system. It has front-end and back-end separation architecture. HTML5, CSS3, and JavaScript are used in the front end to develop a dynamic interface that responds to user inputs and the Flask framework is used in the back end to offer standard API services, as well as the Neo4j graph database to store knowledge graphs of academics. The system combines different data sources like professional training courses, curriculum systems, vocational skills, job demands, etc., and forms a four-layered model of academic knowledge graph, namely major-course-skill-position. This system offers its users intelligent question-answering features which include professional advice consultation, career direction exploration and course information retrieval, through the use of a natural language processing and rule matching engine based on native JavaScript. Moreover, this program can be offered to students in college who would have comprehensive guidance on academic planning and career growth in the university till they graduate and get employed, so it is quite effective in solving such issues as asymmetry of information and lack of personalization of the traditional approach to academic guidance. It is a good potential for advertising and implementation.