a study on exercise recommendation method using knowledge graph for computer network CORD-Papers-2021-10-25 (Version 1)

Title: A study on exercise recommendation method using Knowledge Graph for computer network course
Abstract: With the vast applications of massive online learning platforms during the coVID-19 outbreak, the personalized exercise recommendation methods play an import role on computer aided instruction(CAI) Most existing methods generates the exercises according to the contents and knowledge system structure, lacking semantic relationships between exercises and its knowledge Knowledge graph is widely used to represent the semi-structured and schemaless information (nodes) and their relation (edges), and indicate the sentence embedding grammatical structure and semantic relations, thus it can be applied on computer aided instruction to automatically generate the personalized exercises Aiming to improve the efficiency of exercise recommendation, this paper studies the feature information of computer network course, and proposes a content and knowledge graph based personalized exercise recommendation method More specifically, knowledge graph is firstly constructed from entities and relations of computer network course, and the information vectors of exercises are generated by combining the knowledge with the exercises content And then the learner's historical log data is analyzed, and the semantic similarity between exercises and their knowledge are generated for the wrong answers According the semantic similarity of knowledge, the final exercises are recommended for the learners Experimental results show that the proposed method can improve the efficiency of exercises recommendation 2020 IEEE
Published: 2020
Journal: Proc. - Int. Conf. Netw. Netw. Appl., NaNA
Author Name: Zhu, L
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zhu_l
Author Name: Liu, Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liu_y
Author Name: Hei, X
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hei_x
Author Name: Wang, Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wang_y
Author Name: Meng, H
Author link: https://covid19-data.nist.gov/pid/rest/local/author/meng_h
Author Name: Jiao, J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/jiao_j
Author Name: Pan, L
Author link: https://covid19-data.nist.gov/pid/rest/local/author/pan_l
license: unk
license_url: [unknown license]
source_x: WHO
source_x_url: https://www.who.int/
who_covidence_id: #1132789
has_full_text: FALSE
G_ID: a_study_on_exercise_recommendation_method_using_knowledge_graph_for_computer_network
S2 ID: 232042819