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

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.

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Publication Details

Published
2025-02-12
DOI
https://doi.org/10.1145/3641554.3701804
Primary Topic
Innovative Teaching Methods
Type
article
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article

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

Geoffrey Challen, Yiqiu Zhou, Luc Paquette
Innovative Teaching Methods
article

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

Geoffrey Challen, Yiqiu Zhou, Luc Paquette
article en

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.

University of Illinois Urbana-Champaign (US)
Quality Education
Openalex Percentile: Top 97%
Innovative Teaching Methods
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