TY - GEN
T1 - Investigating the Presence and Development of Student Instructor Preferences in a Large-Scale CS1 Course
AU - Zhou, Yiqiu
AU - Paquette, Luc
AU - Challen, Geoffrey
N1 - This study was supported by the National Science Foundation. Any conclusions expressed in this material do not necessarily reflect the views of the NSF.
PY - 2025/2/18
Y1 - 2025/2/18
N2 - 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.
AB - 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.
KW - Clickstream data
KW - Computer Science Education
KW - Instructor Preference
KW - Log Analysis
KW - Student-Faculty Relationship
UR - http://www.scopus.com/inward/record.url?scp=86000217222&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=86000217222&partnerID=8YFLogxK
U2 - 10.1145/3641554.3701804
DO - 10.1145/3641554.3701804
M3 - Conference contribution
AN - SCOPUS:86000217222
T3 - SIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education
SP - 1337
EP - 1343
BT - SIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education
PB - Association for Computing Machinery
T2 - 56th Annual SIGCSE Technical Symposium on Computer Science Education, SIGCSE TS 2025
Y2 - 26 February 2025 through 1 March 2025
ER -