A Quantitative Analysis of Student Solutions to Graph Database Queries

As data grow both in size and in connectivity, the interest to use graph databases in industry has been growing rapidly. 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 their submissions writing different types of queries in Cypher, the query language for Neo4j--the most prominent graph database. Based on 40,093 student submission from homework assignments in an upper-level computer science database course at University of Illinois at Urbana-Champaign, this paper provides qualitative insights and quantitative analysis about students' learning when solving graph database problems. The data shows that writing more complex queries initially takes students more time and more attempts to write more complex queries correctly. Additionally, students struggle 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.