inBloom’s collapse undermined personalized learning and data standards efforts
Personalized learning is all the rage. Tech magnates keep pointing to it as the “solution” to all sorts of educational challenges. Gates. Zuckerberg. Of course, when you drill down into what they’re talking about, it quickly becomes clear that there’s nothing at all clear about what “personalized learning” is or should be. But even if we stabilize our definition to focus on how data might inform educational processes, there’s a huge elephant in the room: where’s the data going to come from?
In 2013, a company called inBloom was launched with tremendous financial support from the Bill and Melinda Gates Foundation. inBloom promised to solve one of the most difficult problems facing data-oriented educational development — it was going to harmonize the data ecosystem by developing and implementing standards. For any data geek out there who drools over standards and infrastructure building, inBloom represented the fantastic equivalent of building the Suez Canal or the interstate highway system. Geeks started to imagine all that could be built on top of inBloom, and imagining all kinds of technical systems that could aid students. This hype fed the egos of those involved with inBloom, as well as the fears of those who were worried that the dream held by hubristic geeks was more likely going to result in electric sheep being sent to slaughter. All came tumbling down a year later as school districts around the country pulled out from participation and the company folded.
What happened?
How did inBloom go from being the promised solution to a major infrastructure challenge to being cast aside and demonized?
Over the last year, Monica Bulger, Patrick McCormick, and Mikaela Pitcan have interviewed all sorts of folks involved in the inBloom fiasco to understand what went awry. Their report — “The Legacy of inBloom” — is a phenomenal accounting of the organizational, political, technical, economic, and cultural factors that played a role in the collapse of inBloom. This case study reveals the interplay between these different factors and the mistakes of different actors along the way.
Above all else, what the collapse of inBloom reveals is the lack of broad buy-in to efforts that promise that data can solve educational challenges. Not only is the technology not mature, but many of the organizations seeking to build it turn a blind eye to the unintended consequences of their actions in the pursuit of a more perfect technical union. Furthermore, for often justified reasons, parents, teachers, and community members have a widespread distrust of companies coming in to “fix” education. All too often, hyped top-down solutions end up costing communities tremendously and doing little to improve the major problems on the ground. For many on the ground, inBloom was nothing more than another example of rich tech elites projecting their values onto their communities with no contextual understanding.
Truth be told, inBloom kinda deserved this reputation. Built out of Silicon Valley with the cultural logics of a startup, neither the company nor its funders put effort into getting buy-in from communities, focusing instead on selling to experts in governmental agencies to secure agreements.
In the end, the collapse of inBloom felt like a win for communities who were frustrated by how their data was being used and how technology was being introduced into the classroom. At the same time, it was a loss for data standardization in education. Regardless of whether or not visions of personalized learning can be realized, the need for data standards is real. Although the rhetoric of data often centers on efficiency and accountability, data standards also make more interoperable education tools possible. Data standards are an agreed set of ways to communicate values, so that datasets from different sources can be used together. Data standards make it possible for schools to not have to reinvent the wheel. Data standards make it possible to improve data security, support students as they transfer schools, and work with other actors invested in the health and well-being of students. The thing is that data standards can’t be done right from a top-down perspective. Those who are affected need to be a part of the process.
Governance of data is going to be one of the hardest problems going forward. Data standards need to be developed with a governance model in mind. Who gets to decide which data should be collected? How it should be stored and cleaned? Who should have access to it? Who is watching out for the ways in which data is systemically biased against certain groups of people? Who is guaranteeing the security of the data from both inappropriate access and potential manipulation?
These are hard and important questions, especially in the world of education data.
inBloom should’ve been taking the governance part of standards development seriously from the getgo. It did not, focusing instead on the glitz and glam of becoming a Silicon Valley darling, egotistically imagining that they could build the standards without community buy-in. The project of inBloom was widely misunderstood and, as a result of its explosion, the need for data standards is neither understood nor appreciated. This is perhaps my biggest frustration in what all went down. We need data standards, but to do standards right, we need community involvement in making those standards happen. Because of the highly visible explosion of inBloom, there’s very little room for people to come together to reimagine what data standards in education should look like and how that process should be governed. This is a lost opportunity and one that I hope leaders in education take up because we’re long overdue for thinking through.
Points: This piece is part of a series of responses and reflections on the new report, “The Legacy of inBloom,” which draws on interviews and research to trace the closure of inBloom, and analyzes the factors that contributed to its demise. See also:
- inBloom: Analyzing the Past to Navigate the Future by Brenda K Leong and Amelia Vance
- The inBloom Legacy by Olga Garcia-Kaplan
- inBloom — Data, Privacy, and the Conversations We Could Have Had by Bill Fitzgerald
- Rationalizing Those “Irrational” Fears of inBloom by Audrey Watters
