Construction and Application of Teaching System Based on Crowdsourcing Knowledge Graph

TL;DR

This paper presents a novel teaching system that leverages crowdsourcing to construct a hierarchical knowledge graph, enabling personalized learning and visualization of teacher and student data, with high acceptance among users.

Contribution

It introduces a crowdsourcing-based method for building a comprehensive teaching knowledge graph and applies it to personalized education and visualization.

Findings

High acceptance among students and teachers.

Effective construction of hierarchical knowledge graph.

Personalized exercise recommendations based on the graph.

Abstract

Through the combination of crowdsourcing knowledge graph and teaching system, research methods to generate knowledge graph and its applications. Using two crowdsourcing approaches, crowdsourcing task distribution and reverse captcha generation, to construct knowledge graph in the field of teaching system. Generating a complete hierarchical knowledge graph of the teaching domain by nodes of school, student, teacher, course, knowledge point and exercise type. The knowledge graph constructed in a crowdsourcing manner requires many users to participate collaboratively with fully consideration of teachers' guidance and users' mobilization issues. Based on the three subgraphs of knowledge graph, prominent teacher, student learning situation and suitable learning route could be visualized. Personalized exercises recommendation model is used to formulate the personalized exercise by algorithm based on the knowledge graph. Collaborative creation model is developed to realize the crowdsourcing construction mechanism. Though unfamiliarity with the learning mode of knowledge graph and learners' less attention to the knowledge structure, system based on Crowdsourcing Knowledge Graph can still get high acceptance around students and teachers