Expectancy and Value as Drivers for Participation and Persistence in an Open-access Online Scientific Computing Training in Seismology

Wednesday 1:50 PT / 2:50 MT / 3:50 CT / 4:50 ET Online

Authors

Mike Brudzinski, Miami University-Oxford
During the summer of 2020, the Incorporated Research Institutions for Seismology (IRIS), in collaboration with Miami university, offered a free, 3-month, certificate-granting online workshop. This workshop sought to increase undergraduates' knowledge, skills, self-efficacy, and interest in observational seismology and scientific computing. 760 advanced STEM undergraduates, representing 60 different countries registered to participate. The access provided by open workshops may broaden participation in seismology specifically and STEM more broadly as U.S. participants consisted of 59% women and 29% from populations traditionally underrepresented in geoscience. Performance data revealed 58% of registrants completed at least one assignment, 30% completed at least 80% of assignments, and 25% completed all assignments. The initiation rate, or percentage of registrants who complete the first assignment, and completion rate are both significantly higher than most comparable large-scale, open-access courses (e.g., MOOCs). However, these rates seem unnecessarily low and have some variability across populations (e.g. URM status, and academic major). To identify factors associated with persistence, registration and pre/post survey data are analyzed through the lens of the expectancy-value theory (EVT) and compared to initiation and completion rates. Results from preliminary analysis of initiation rates map well to most EVT constructs: intrinsic value factors (p<.001), utility value factors (p<.001), attainment value factors (p=.24), and expectancy factors (e.g., completion intentions for the workshop [p<.001], prior computing experience [p<.001], seismology research experience [p=.01], seismology self-efficacy [p=.84]). Participants who did not persist identified factors, or costs, which negatively impacted their persistence. We will use regression analysis to further probe the degree to which these factors influence persistence throughout the workshop and evaluate the explanatory value of EVT for advanced undergraduate performance in an online workshop focused on technical skill development. Results will also drive the development of interventions to enhance student persistence in future workshop iterations.

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