Optimizing MOOCs for Student Engagement: Insights from Conjoint Analysis

Online education has gained significant importance in the twentieth century. Many universities have made MOOCs (Massive Open Online Courses) compulsory for students to enhance their skills. This study investigated the combination of MOOCs attributes most preferred by students using a Conjoint Analysis approach. The Orthogonal design in SPSS was used to identify the number of stimuli for which the preferences of the students were taken. Total of 25 stimuli were generated during this process. The study analyse various attributes of MOOCs, including course format, certification type, assessment method, instructor engagement, course duration, and content. The respondents were students who had already appeared for MOOCs examination. A total of 252 responses were collected, and students' preferences were analysed with the help of conjoint analysis. The Conjoint Analysis revealed that students prefer self-paced and scheduled live sessions, platform-provided certificates, offline tests, no instructor engagement, shorter-duration courses, and courses that incorporate real-life case studies.