F5-O/LT3-4 - Surveying Motivation and Learning Outcomes of Advanced Learners in Online Engineering Graduate MOOCs

3. Research Work In Progress
Hillary E. Merzdorf1 , Kerrie A. Douglas1
1 Purdue University

Keywords: motivation, MOOCs, highly technical courses, advanced learners 

Topics: Distance, Open and Flexible Education, Open Educational Resources and Practices 

This Research category Work-in-Progress presents a survey of advanced engineering learners’ motivation in highly-technical advanced engineering MOOCs. Advanced engineering courses delivered as MOOCs are more prevalent in graduate and professional learning than ever. They are also gaining more importance in terms of credentialing and the opportunity to earn accredited degrees. However, being hosted on MOOC platforms makes these courses open to the public as well as formal learners, making it difficult to generalize experiences for all. To understand what prevents learners from reaching their goals and to better support them in meeting their goals, there is a need for more sensitive approaches to measuring motivation in MOOC engineering learners and practicing engineers. The Expectancy-Value-Cost (EVC) scale has been shown to be predictive of educational achievement in other settings. Previous research has shown the EVC scale to have a ceiling effect when used in MOOCs. We have revised the scale (PEVC) to improve its sensitivity and predictiveness of learner engagement and achievement, and demonstrate its validity in highly technical online engineering courses.  

This research examines advanced learners’ goals and motivation as they relate to learner background and course activity. Specifically, we wish to validate the use of the PEVC in assessing motivation in online engineering graduate MOOCs by investigating their predictive value in modeling learner subgroups. Our research questions are: 1) To what extent do PEVC scores predict learner engagement in advanced engineering MOOCs? 2) How predictive are motivation scores of learner achievement? And 3) Is the PEVC sensitive enough to differentiate between learner groups

This study analyzed the motivations, intentions, and course ratings of learners in highly technical engineering and nanotechnology graduate MOOCs offered by [blinded] through edX, available within a formal degree program and open access. Pre-course surveys asked learners’ course goals, degree and institution affiliation, and interest in the program. Mid-course surveys reviewed learning goals and assessed learners’ motivation using the PEVC Post-course surveys asked learners’ experiences and satisfaction with content and recommended improvements. Learner data on course material access was also collected. We conducted factor analysis and item response theory to test the performance of the instrument, and regression analysis to determine its predictiveness on course activity. We also examined motivation group mean differences by learner subgroups. 

Preliminary results show overall high reported motivation in learners, especially on the Expectancy and Value dimensions, but a wider range of responses on the Cost dimension. We also see the majority of learners intending to successfully learn all course content. Factor analysis show the PEVC to retain a three-factor structure, while item sensitivity is high. We observe that independent learners report higher Expectancy and Value than students in formal degrees, and formal learners have a wider range of Cost responses than independent learners.