Investigating the Presence and Development of Student Instructor Preferences in a Large-Scale CS1 Course

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

Abstract

Prior research has established the importance of student instructor preferences and identified various influencing factors. However, the dynamics of how student instructor preferences develop and change are less well understood, due to the limitations of common course structures and reliance on one-time measurements. To bridge this gap, we utilize data from a novel learning platform that provides students with access to instructional content created by multiple instructors. This platform enables the quantification of preference emergence and evolution throughout an entire semester, as students repeatedly select content from different instructors. Examining both initial and final student instructor preferences suggests that preference is a dynamic construct continually shaped by experiences. Furthermore, our analysis of the associations between preferences and student characteristics reveals a nuanced picture: while student attributes did not significantly correlate with initial preferences, substantial differences emerged in final preferences across genders and self-reported prior programming experience. This analysis contributes to the existing body of knowledge by expanding our understanding of student instructor preferences and student-instructor relationships in computer science education. We also provide practical insights that institutions and instructors can draw on when multiple instructors collaborate on a course.

Original languageEnglish (US)
Title of host publicationSIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education
PublisherAssociation for Computing Machinery
Pages1337-1343
Number of pages7
ISBN (Electronic)9798400705311
DOIs
StatePublished - Feb 18 2025
Event56th Annual SIGCSE Technical Symposium on Computer Science Education, SIGCSE TS 2025 - Pittsburgh, United States
Duration: Feb 26 2025Mar 1 2025

Publication series

NameSIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education
Volume1

Conference

Conference56th Annual SIGCSE Technical Symposium on Computer Science Education, SIGCSE TS 2025
Country/TerritoryUnited States
CityPittsburgh
Period2/26/253/1/25

Keywords

  • Clickstream data
  • Computer Science Education
  • Instructor Preference
  • Log Analysis
  • Student-Faculty Relationship

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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