Assessing Student Learning Across Various Database Query Languages

Zepei Li, Sophia Yang, Kathryn Cunningham, Abdussalam Alawini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Previous research has shown that students encounter difficulties when learning database systems and their corresponding languages. Researchers have categorized these challenges into syntax and semantic errors and have identified common error types and overall learning obstacles among students. However, most existing studies have primarily focused on quantitatively assessing students' overall performance in an aggregated manner' which may overlook valuable insights into individual-level knowledge transfer. In this study, we scrutinized over 250,000 submissions to query language programming assignments, their corresponding error messages, and the performance data of 702 students who took a database course in the Fall 2022 semester at the University of Illinois Urbana-Champaign to gain a comprehensive overview of each student's performance. We followed each student's progress in semantic and syntax errors across three query languages to determine their overall learning experience and whether knowledge transfer had occurred. Consequently, we discovered that many students may still encounter difficulties when transferring their knowledge from one language to another, despite having already learned and practiced the same abstract data operation concepts in one language. On the other hand, the majority of students were able to reduce syntax errors through practice in one language, but the rate of improvement varied among individuals. This study seeks to investigate two key aspects: the potential transfer of abstract data operation concepts among different database languages, and the possibility of a decrease in syntax errors through consistent practice within a single query language.

Original languageEnglish (US)
Title of host publication2023 IEEE Frontiers in Education Conference, FIE 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350336429
DOIs
StatePublished - 2023
Event53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023 - College Station, United States
Duration: Oct 18 2023Oct 21 2023

Publication series

NameProceedings - Frontiers in Education Conference, FIE
ISSN (Print)1539-4565

Conference

Conference53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023
Country/TerritoryUnited States
CityCollege Station
Period10/18/2310/21/23

Keywords

  • MongoDB
  • Neo4j
  • Structured Query Language (SQL)
  • knowledge transfer
  • semantic errors
  • syntax errors

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications

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