Student Course Behaviors Influencing Performance in a Flipped CS1 Classroom Model

Prior research has explored the impact of various demographic and psychological factors in introductory computer science courses (CS1), but there remains a gap in understanding how course engagement patterns relate to students' performance and how these behaviors are influenced by demographic characteristics. This study investigates the relationships between student characteristics, course behaviors, and performance in a CS1 course taught using a flipped classroom model. We analyzed data from 410 engineering students, examining factors including gender, prior programming experience (PPE), grade point average (GPA), and learning self-efficacy (LSE). The study focused on four key course behaviors and attitudes: engagement with pre-class recorded lectures, self-reported class attendance, perceived availability of support, and perceived quality of in-class activities, exploring how these related to exam performance and student characteristics. Analysis indicated significant positive correlations between exam performance and three factors: students' engagement with pre-class recorded lectures, perceived availability of support, and perceived quality of in-class activities. Self-reported class attendance did not relate to exam scores. Female students reported significantly higher engagement with pre-class recorded lectures compared to male students, but lower perceptions of available support. Students with higher GPAs reported lower engagement with pre-class lectures, yet indicated higher perceptions of available support and found in-class activities more helpful. These findings highlight important behavioral and perceptual differences in how students engage with CS1 flipped classrooms. Understanding these patterns could enhance learning environments that better support all students, particularly those who may feel less included in computing education.