Construction and visualization of “Python” programming language course knowledge graph
Zhou, Wenbin (2024)
Kandidaatintyö
2024
School of Engineering Science, Tietotekniikka
Kaikki oikeudet pidätetään.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2024051732289
https://urn.fi/URN:NBN:fi-fe2024051732289
Tiivistelmä
With the popularity of programming education, how to organize and teach programming knowledge efficiently has become particularly important. This article aims to promote the effectiveness of the teaching and learning process by constructing a course knowledge graph for the Python programming language and explore the application potential and effect of knowledge graphs in programming education.
The research uses Python web crawler technology to extract course data from online resources, uses Neo4j graph database to store and organize these data, and finally develops a dynamic knowledge graph visualization system by combining Django, Vue.js and d3.js technologies. This system not only enhances the interactivity and accessibility of the education platform, but also greatly improves the learning experience and educational effects by visually displaying the connections between course content.
Through this study, we demonstrate the potential of knowledge graphs in optimizing programming language education, providing a basis for future applications of knowledge graphs in other courses or in broader educational fields.
The research uses Python web crawler technology to extract course data from online resources, uses Neo4j graph database to store and organize these data, and finally develops a dynamic knowledge graph visualization system by combining Django, Vue.js and d3.js technologies. This system not only enhances the interactivity and accessibility of the education platform, but also greatly improves the learning experience and educational effects by visually displaying the connections between course content.
Through this study, we demonstrate the potential of knowledge graphs in optimizing programming language education, providing a basis for future applications of knowledge graphs in other courses or in broader educational fields.