| Summary: | Disruptive innovations are used to lower costs and augment access to high-quality, affordable higher education, but little systematic research is available on the topic. Higher education institutions use disruptive innovations to save students time and money. To understand the process of disruptive innovation, I investigated the rapid diffusion of Massive Open Online Courses (MOOCs), which are free or low-cost college courses available online. Specifically, I examined the drivers of disruptive innovation over time and by institution type, and augmented the existing theory on the diffusion of disruptive innovation in higher education. The key for this systematic study was to have a dataset that encompassed a large sample of adopters and non-adopters. I constructed a new dataset merging 4 years of IPEDS data with MOOC data (n = 1,470). Analytically, I used competing drivers of institutional change, specifically prestige-seeking versus economic competition, to investigate rate and drivers of adoption, how drivers varied over time, and which institutions were most and least likely to innovate. I employed time-series inferential statistics, specifically discrete time hazard modeling (DTHM), and latent class analysis (LCA), as well as descriptive statistics.
Three research questions guided this dissertation.
1. When is MOOC adoption most likely? How does prestige-seeking behavior compared to economic competition influence the adoption of MOOCs?
2. Does partnership with a for-profit versus nonprofit provider differ by prestige-seeking behavior or economic competition? Do these partnerships change over time?
3. To what extent does a typology of institutional innovators based on prestige-seeking behavior and economic competition exist? To what extent does this typology of innovators relate to MOOC adoption? How does the adoption of innovation by institutional subgroup vary over time?
The findings suggested that rate of adoption, at its height, was a little over 3% in academic year 2013, 2 years after the launch of MOOCs. Both prestige-seeking behavior and economic competition were important predictors of innovation, although institutions most likely to innovate were very prestigious and strategic about the markets they chose for competition. Specifically, the most likely adopters of disruptive innovation were highly competitive in distance education and in pursuing private grants and contracts from industry, but often did not cut costs (e.g., replacing full-time faculty with adjuncts or expanding managerial capacity) to streamline affairs on campus or manage market expansion. By contrast, institutions that did not innovate often exhibited the opposite characteristics. Finally, because the first two results suggested different adopters, I found five different types of institutional innovators (Accelerators, Wealth Managers, Pragmatists, Opportunists, and Laggards). Approximately 15% of colleges were Accelerators (primed to be disruptive innovators), while the rest were characterized by limited motivate to change or limited institutional capacity to innovate.
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