Unified MOOC utilization model: UMUM Model

What is it about?

By integrating the two theoretical strands of DeLone & McLean’s IS success model and fit-related constructs of task technology fit model this study puts forward the unified MOOC utilization model (UMUM). The proposed UMUM model also comprises quality and fit variables to explain the students’ intention to re-use MOOCs. Further, UMUM model proposed that the intention to re-use MOOCs ultimately maximizes MOOC’s overall utilization. The UMUM research model was empirically validated by employing the PLS-SEM approach, using data collected from 370 students registered in a MOOC based study program. Findings confirmed that the proposed quality-related factors of the UMUM model (i.e. system, information, service, and ELIQ) and task characteristics positively influence fit factors. Likewise, the association between users’ self-reported satisfaction with MOOC and their intention to re-use it is also positive and significant. Finally, intention to re-use, task-technology fit (i.e. fulfilling the technical expectations of users for their learning tasks), and task-service fit in the UMUM model positively influence and predict overall MOOC utilization. Future studies concerning MOOCs and educational technology can employ the UMUM model for the assessment of MOOC utilization and students’ intention to re-use MOOCs.

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Why is it important?

By integrating the two theoretical strands of DeLone & McLean’s IS success model and fit-related constructs of task technology fit model this study puts forward the unified MOOC utilization model (UMUM). The proposed UMUM model also comprises quality and fit variables to explain the students’ intention to re-use MOOCs. Further, UMUM model proposed that the intention to re-use MOOCs ultimately maximizes MOOC’s overall utilization. The UMUM research model was empirically validated by employing the PLS-SEM approach, using data collected from 370 students registered in a MOOC based study program. Findings confirmed that the proposed quality-related factors of the UMUM model (i.e. system, information, service, and ELIQ) and task characteristics positively influence fit factors. Likewise, the association between users’ self-reported satisfaction with MOOC and their intention to re-use it is also positive and significant. Finally, intention to re-use, task-technology fit (i.e. fulfilling the technical expectations of users for their learning tasks), and task-service fit in the UMUM model positively influence and predict overall MOOC utilization. Future studies concerning MOOCs and educational technology can employ the UMUM model for the assessment of MOOC utilization and students’ intention to re-use MOOCs.

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