Cluster and trajectory analysis of motivation in an emergency remote programming course

Area of Science:

• Education
• Psychology
• Sociology

Background:

• The COVID-19 pandemic necessitated a rapid shift to emergency remote teaching (ERT).
• Understanding student motivation is crucial for effective ERT, especially in STEM fields like programming.
• Previous research on ERT motivation during global health crises is limited.

Purpose of the Study:

• To analyze student motivation profiles in a university programming course during one semester of ERT.
• To investigate the evolution of student motivation throughout the semester.
• To determine the impact of COVID-19 concern on student motivation.

Main Methods:

• A survey methodology was employed, with university students in a programming course surveyed three times.
• Data collection focused on student motivation and concerns related to the COVID-19 pandemic.
• Latent profile analysis was used to identify distinct student motivation clusters.

Main Results:

• Three distinct student motivation profiles emerged: most adaptive, least adaptive, and intermediate.
• The most adaptive profile exhibited high motivation and preparedness but also the highest COVID-19 concern.
• The least adaptive profile showed low motivation and preparedness, mirroring the most adaptive group in reverse regarding pandemic concern.

Conclusions:

• Student motivation in ERT is complex and not solely determined by pandemic anxiety.
• The most resilient students may be those who can manage high external stressors, like COVID-19 concerns, while maintaining academic drive.
• Tailored support strategies considering both academic and psychological factors are essential for ERT success.