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Title: Mining SQL Problem Solving Patterns using Advanced Sequence Processing Algorithms
SQL is a crucial language for managing relational database systems, and is an essential skill for individuals in roles such as researchers, developers, and business professionals who work with databases. However, learning SQL can be a challenge, presenting an opportunity to study the various methods students use to arrive at semantically equivalent SQL queries. In this study, we examined students’ SQL submissions to homework assignments in the Database Systems course offered to upper-level undergraduate and graduate students at the University of Illinois Urbana-Champaign during the Fall 2022 semester. Our goal was to understand how students arrive at SQL solutions and overcome challenges in the learning process by building on prior research on line chart visualizations that instructors can use to increase visibility on students who are struggling. However, a major limitation of this approach was the difficulty for instructors to sift through a large number of visuals representing each student’s performance on a SQL problem and generate action items at scale, especially when dealing with enrollments of over 700 students. To overcome this limitation, we developed a novel technique to generate textual representations of the student submission sequence using global sequence alignment scores and regular expression algorithms to further compact these submission sequences. This allows instructors to gain insights quickly, on an aggregate level, and in an automated manner, enabling them to identify students who may be struggling with SQL based on their submission sequence characteristics and take appropriate action to improve database education. Our study discovered common textual submission patterns and pattern elements, and we present our recommendations to instructors to improve database education based on these findings.  more » « less
Award ID(s):
2021499
PAR ID:
10480316
Author(s) / Creator(s):
; ;
Publisher / Repository:
ACM
Date Published:
Journal Name:
DataEd '23: Proceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research
ISBN:
9798400702075
Page Range / eLocation ID:
37 to 43
Format(s):
Medium: X
Location:
Seattle WA USA
Sponsoring Org:
National Science Foundation
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