Analyzing Patterns in Student SQL Solutions via Levenshtein Edit Distance

Analyzing Patterns in Student SQL Solutions via Levenshtein Edit Distance
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通过 Levenshtein Edit Distance 分析学生 SQL 解决方案中的模式

DOI:
10.1145/3430895.3460979
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发表时间:
2021
期刊:
Proceedings of the Eighth ACM Conference on Learning @ Scale
影响因子:
--
通讯作者:
Alawini, Abdussalam
Alawini, Abdussalam
中科院分区:
--
文献类型:
--
作者:
Yang, Sophia;Wei, Ziyuan;Herman, Geoffrey L.;Alawini, Abdussalam

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结构化查询语言(SQL)是关系数据库管理系统的标准语言,是软件开发人员、数据科学家和需要与数据库交互的专业人员的基本技能。SQL是高度结构化的,并为学习者提供了多种获得这种技能的方法。然而,尽管SQL对其他相关领域具有重要意义,但很少有研究来了解学生如何在家庭作业中学习SQL。在本文中,我们分析了学生的SQL提交的数据库系统课程在伊利诺伊大学香槟分校提供的家庭作业问题。对于每个学生,我们计算每次提交与最终提交之间的Levenshtein编辑距离,以了解学生如何达到最终解决方案,以及他们如何克服学习过程中的任何障碍。我们的系统可视化学生提交的SQL问题之间的编辑距离,使教师能够识别有趣的学习模式和方法。这些发现将帮助教师在未来将他们的教学目标定位在困难的SQL领域,并帮助学生更有效地学习SQL。
Structured Query Language (SQL), the standard language for relational database management systems, is an essential skill for software developers, data scientists, and professionals who need to interact with databases. SQL is highly structured and presents diverse ways for learners to acquire this skill. However, despite the significance of SQL to other related fields, little research has been done to understand how students learn SQL as they work on homework assignments. In this paper, we analyze students' SQL submissions to homework problems of the Database Systems course offered at the University of Illinois at Urbana-Champaign. For each student, we compute the Levenshtein Edit Distances between every submission and their final submission to understand how students reached their final solution and how they overcame any obstacles in their learning process. Our system visualizes the edit distances between students' submissions to a SQL problem, enabling instructors to identify interesting learning patterns and approaches. These findings will help instructors target their instruction in difficult SQL areas for the future and help students learn SQL more effectively.
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