Remarkable breakthroughs happen at public research universities everyday, but bridging the gap between early innovation and widespread adoption is a challenge that these institutions know all too well. This is especially the case when it comes to education technology and curricular innovation.
In 2015 the University of Michigan established the Digital Innovation Greenhouse (DIG) as part of the Office Of Academic Innovation—a group charged with fostering a culture of innovation in learning in order to reimagine the 21st century public research university. DIG works with faculty, staff, and student user communities to grow tools to maturity, and establish pathways to scale through collaboration across and beyond the U-M community. With a team of developers, designers, behavioral scientists, data scientists and student fellows, DIG helps translate digital engagement tools from innovation to infrastructure. In its first year of operation, DIG tools were used by more than 22,000 U-M students and will soon be used by more than a dozen institutions.
DIG has received a steady flow of inquiries and visits from peer universities and edtech innovators. They all ask the same question: How do you get from early-stage innovation and R&D to adoption across an an organization as complex as a public research university?
While it would be silly to offer an overly prescriptive recipe that fails to take each institution’s unique context into account, we think we’re onto something that works. We offer our colleagues at peer institutions and edtech companies nine considerations for cultivating innovation on campus and beyond.
1. Establish clear values and guiding principles.
DIG team members codified our approach in a set of guiding principles that articulates our values, commitments and approaches to fostering innovation. These principles include understanding users and creating a minimum viable product, for example, and we apply them to each project. As an agile partner to faculty innovators and academic units, the DIG team consistently navigates new terrain, and these principles and values provide clarity of purpose. (See how we recently applied the principles to a writing tool called M-Write.)
2. Be impractical. Then consider constraints.
We establish audacious goals in order to transition new digital engagement tools from innovation to infrastructure. Worrying over questions about culture, data and technology could easily constrain our thinking from the start. In order to scale tools to tens of thousands of users within the first 12 months we need freedom to think impractically.
We’ve been fortunate to attract a team with unique talents to cultivate these projects. They are comfortable with the ambiguity inherent to such an endeavor, and understand there is an appropriate time to layer constraints back into our design-thinking approach in order to address implementation and scale proactively.
3. Build a dynamic team.
DIG started with three lead developers who took on a unique set of projects. Part of our mission is to actively share what we learn across campus in order to stimulate new innovative experiments. As we shared our work, new innovators came forward and we quickly realized we needed additional talent to support them. The DIG team identified and prioritized additional needs and quickly added members with expertise in user experience design, behavioral science, data science, software development and innovation advocacy. We continue to grow our capabilities in these areas and more as we foster a culture of learning in innovation at U-M.
4. Welcome talented student contributors.
In addition to growing our full-time staff, we benefit from the engagement of students through our Student Fellows program. Over the course of a year, we hire approximately 20 undergraduate and graduate student fellows who are both mentored in and contribute to areas as diverse as software development, user experience design, graphic artistry, innovation advocacy and data science. Our experiences with our students have helped us to validate and prioritize new capabilities needed to grow our model, including UX design, software development in the MOOC space, and software development aligned with gameful learning.
5. Design a model for agile development that leverages opportunities for discovery and scale.
As a public research university with more than 40,000 students, U-M is one of the largest living laboratories for conducting experiments in academic innovation. By coupling rapid development and deployment with assessment we foster a virtuous cycle of innovation that leads to further discovery. These assessments take a variety of forms ranging from one-on-one interviews with end-users to using techniques from the emerging field of learning analytics.
6. Build products with—rather than for—users.
Instead of ROI, we measure our success by community engagement and educational impact.
As we build minimum viable products with faculty innovators and teams, we move quickly to create learning communities. This results in greater impact on campus and often accelerates knowledge sharing and adoption as well as our due diligence around options for commercialization. We build our tools with our community of users, not simply for them. This attention to community engagement in addition to adoption separates our approach from many off-campus models.
7. Recognize exit as opportunity and not a four-letter word.
We are also committed to ensuring that viable projects thrive once they leave DIG. From the earliest stages, exit plans and concomitant hardening-off plans are developed for all projects that enter the Greenhouse. In some cases the strategy involves commercialization; in other cases it could involve shifting responsibility to our information and technology services group; in a smaller number of cases it could involve closing the project or narrowing development around a particular use case. We find that our process of prototyping and iteration allows us to extract meaning from all projects and continue moving forward in pursuit of our mission.
8. Embrace emergence and continue to strengthen capabilities as new opportunities emerge.
The process of product development in lean startup environments and other highly innovative organizations often incorporates the notion of a “pivot,” which is a “structured course correction designed to test a new fundamental hypothesis about the product, strategy, and engine of growth." We embrace the concept of pivoting in DIG but we also engage in continuous assessment of our own capabilities, identify new needs, and respond by strategically hiring highly qualified personnel into new roles.
9. Provide links between research and practice.
Our work in DIG is both scholarly and practical. Much of the higher education sector draws a line between teaching and learning on one side, and research on the other. Our work straddles these worlds with a more unifying focus on discovery. As an example, in creating ECoach we are focused on easing the transition to college for all students. We developed this innovative tool, accelerated adoption across campus, and built upon this deployed effort to attract a National Science Foundation $1.9 million grant to further explore how personalization can advance equity on campus.
The approach we have adopted within DIG and across the Office of Academic Innovation—applying lean startup principles to promote academic innovation at a research university—is to the best of our knowledge, a novel one in the educational technology space. We see great promise in a scholarly and practical approach that aligns academic excellence, inclusion and innovation at its core.