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

2026-08-07

AI Summary

This study addresses the unclear mechanisms underlying the formation and evolution of student preferences for instructors in large-scale introductory computer science courses. Leveraging a novel learning platform that supports student choice among multiple instructors’ content, the research presents the first dynamic, end-to-end tracking and quantification of instructor preferences within a real-world CS1 course. By integrating platform log data with student background surveys and employing longitudinal modeling and statistical analyses, the study finds that initial preferences are unrelated to individual characteristics, whereas final preferences exhibit significant differences by gender and prior programming experience. These findings highlight the formative role of learning experiences in shaping instructor preferences and provide empirical support for collaborative, multi-instructor teaching models in computing education.

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.

Problem

• student instructor preferences
• preference dynamics
• CS1 course
• computer science education
• learning platform

Innovation

• instructor preference
• longitudinal analysis
• CS1 education
• learning platform
• student-instructor relationship