Significance of knowledge graph in SMART learning

• Published in: 2023 2nd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) pp. 1 - 6
• Main Authors: Nithya, S., Apinayaprethi, K N
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.06.2023
• Subjects: Computer science; Data Scraping; Educational technology; Encyclopedias; Knowledge graphs; MRotatE; Natural language processing; Visualization
• DOI: 10.1109/ICAECA56562.2023.10200739

The information available today is scattered everywhere. The traditional method of learning which is completely text-based takes more time to understand. Students must learn more in less time and also have good knowledge of the concepts which are not only present in the textbooks, but also from external sources. Visual learning techniques are the most well-known effective way to learn more information in less time. When information is presented visually, it is easy to understand the concepts and remember them for a long time. The knowledge graph is used to represent the information with the relationship between the different topics in a visually comprehensive manner. Our project aims in helping students to learn visually with the help of knowledge graphs (or concept maps). The Graphs for various subjects will be available separately and can be used by students to learn interactively. Our project is mainly focused on subjects from the computer science domain. For the knowledge graph construction, the required data is scraped from the internet using Wikipedia and Google Knowledge APIs. Natural language processing (NLP) is used to process scrapped data from the internet which is then processed using a graph database to display the knowledge graph with the data and the relationship connecting the data. All graphs are made in such a way to make a visual impact on learners such that it is easy to read and interpret.