@inproceedings{e112d9ab24ef4163be172c67944e5b67,
title = "A Quantitative Analysis of Student Solutions to Graph Database Problems",
abstract = "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.",
keywords = "Neo4j, database education, online assessment",
author = "Mei Chen and Seth Poulsen and Ridha Alkhabaz and Abdussalam Alawini",
note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 26th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2021 ; Conference date: 26-06-2021 Through 01-07-2021",
year = "2021",
month = jun,
day = "26",
doi = "10.1145/3430665.3456314",
language = "English (US)",
series = "Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE",
publisher = "Association for Computing Machinery",
pages = "283--289",
booktitle = "ITiCSE 2021 - Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education",
address = "United States",
}