Design of Evaluation and Recommendation System for High School Physics Learning Based on Knowledge Graph

The physics subject examination is an effective way to test how much knowledge the students master. It is important to dig out the information which is beneficial to teaching from students' scores and test papers. Taking classes online is very popular because of COVID-19 this year, and the network teaching evaluation system emerges as the times require. In order to review the qualities of learning by the final examination paper, we designed an intelligence learning evaluation and recommendation system to detect qualities of learning, which is based on knowledge graph and machine learning algorithm. The system analyses test papers and gives reports in detail, so that it's clearly to know pain points and obstructions of physics learning, and gets easy to figure things out. Corresponding personalized teaching content recommendation can improve learning in an efficient way.