Massive open online courses for professional certificate programs? Perspectives on professional learners’ longitudinal participation patterns
DOI:
https://doi.org/10.14742/ajet.5768Keywords:
MOOCs, longitudinal clustering, professional certificate, temporal dimension, participation, performanceAbstract
Massive open online courses (MOOCs) have been integrated into higher education systems as an option for delivering online professional degree and certificate programs; however, concerns about whether employed professionals actively participate in MOOCs remain unresolved. Some researchers have described learners’ employment as the major cause of attrition from MOOCs, but research has not addressed how employed learners interact with MOOCs over time. Understanding employed professionals’ trajectory of participation patterns across course time is thus essential to improving the effectiveness of MOOCs. This study investigated the log data of learner participation to explore how attrition occurs in a professional MOOC, focusing on whether students’ employment status was associated with learner participation. The results revealed learners’ longitudinal participation patterns and confirmed the impact of sustained engagement on course performance. The study also found that employed learners were more likely than their peers without jobs to become cramming learners with initially infrequent engagement in a course but investing intensive time at the end for certificates. We discuss practical implications for designing and facilitating large-scale professional degree and certificate programs in higher education institutions.
Implications for practice or policy:
- Educators can apply MOOCs with a lower weekly workload and a slower pace to support employees’ professional development.
- Educators should develop professional learners’ interests in the course topic to avoid only cramming for the course certificates.
- Educators may consider longitudinal patterns of learner participation when assessing learner performance.
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Copyright (c) 2021 Hengtao Tang, Wanli Xing
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