Predictors of Student Performance in HyFlex Environment: Insights from multilevel modeling

• In Event: AERA Poster Session Wednesday 1:45pm
  In Poster Session: Data-Driven Decision Making in Education SIG Poster Session

Abstract

HyFlex instruction has been a recognized method of instructional delivery for nearly two decades and has expanded significantly in the past five years. This study examined predictors of student performance in HyFlex environment using multilevel beta regression modelling. We investigated how individual and contextual factors, such as attendance mode, motivation, team effectiveness, and community of inquiry, influence final course grades. Results show that higher remote attendance and amotivation negatively affect individual performance, while stronger community sense and moderate team engagement are positively associated. At the classroom level, average remote attendance and community sense enhance individual performance, highlighting the role of peer and instructor dynamics. These findings offer critical instructional insights for designing practical HyFlex courses.

Authors

• Elnara Mammadova, Purdue University

• Michel Cordoba, Purdue University

• Nathan Mentzer, Purdue University