A Quantitative Analysis of Student Solutions to Graph Database Problems

A Quantitative Analysis of Student Solutions to Graph Database Problems
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对学生图数据库问题解决方案的定量分析

DOI:
10.1145/3430665.3456314
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发表时间:
2021
期刊:
Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education
影响因子:
--
通讯作者:
Alawini, Abdussalam
Alawini, Abdussalam
中科院分区:
--
文献类型:
--
作者:
Chen, Mei;Poulsen, Seth;Alkhabaz, Ridha;Alawini, Abdussalam

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随着数据在大小和连接性方面的增长,在行业中使用图形数据库的兴趣一直在激增。然而,目前对图形数据库教育的研究还很少。针对向大学生介绍图形数据库的需要,本文首次分析了学生在提交用Cypher语言编写的查询时所犯的错误,Cypher语言是Neo4j--最著名的图形数据库的查询语言。本文基于某大学高级计算机科学数据库课程的40,093份学生家庭作业提交的数据,对学生解决图数据库问题时的学习情况进行了定量分析。数据显示,学生的斗争最正确地使用Cypher的WITH子句定义变量名引用之前,在WHERE子句和这些错误持续多个家庭作业的问题,需要相同的技术,我们建议进一步改进的句法错误的分类。
As data grow both in size and in connectivity, the interest to use graph databases in the industry has been proliferating. However, there has been little research on graph database education. In response to the need to introduce college students to graph databases, this paper is the first to analyze students' errors in homework submissions of queries written in Cypher, the query language for Neo4j---the most prominent graph database. Based on 40,093 student submissions from homework assignments in an upper-level computer science database course at one university, this paper provides a quantitative analysis of students' learning when solving graph database problems. The data shows that students struggle the most to correctly use Cypher's WITH clause to define variable names before referencing in the WHERE clause and these errors persist over multiple homework problems requiring the same techniques, and we suggest a further improvement on the classification of syntactic errors.
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