What does it mean for kids in schools to have every moment of their lives datafied? How can institutions, edtech platforms, parents, teachers, and researchers preserve children’s privacy while leveraging technologies to improve education? Here are my thoughts…

“This technology is being promoted by tech vendors, not educators, and it’s certainly not being promoted by parents,” Monica Bulger, a senior fellow at the Future of Privacy Forum’s Education Privacy Project told me. Despite federal statistics that show schools are among the safest places for children, the public believes that schools are more dangerous than ever. “School administrators feel they need to provide a solution. The tech seems to provide a quick, easy fix,” Bulger said. “Schools aren’t considering whether it is the best fit; they’re choosing the fastest one.” New York Times, July 2019
“There’s a powerful fear narrative happening,” said Bulger. Earlier this year, Bulger co-authored a report on the legacy of inBloom, a student data-management project supported by the Bill & Melinda Gates Foundation and the Carnegie Corporation of New York. The project, launched in 2013, shut down a year later after vocal opposition. In contrast to the developers of inBloom, she said, Summit has been trying to engage with school communities and respond to parent concerns. But in any any ed-tech implementation involving student data, she said, uncertainty can give way to fear. EdWeek, December 2017
Review of The Legacy of InBloom: Throughout its brief history, the organization and the product seemed to embody contradictory business models, software development approaches, philosophies and cultures,” the report stated. “There was a clash between Silicon Valley-style agile software development methods and the slower moving, more risk-averse approaches of states and school districts. At times, it was as though a team of brilliant thinkers had harvested every ‘best practice’ or innovative idea in technology, business and education — but failed to whittle them down to a manageable and cohesive strategy. THE Journal, February 2017
Review of The Legacy of InBloom: Based on interviews with 18 key actors, “The Legacy of inBloom” is a must-read for those interested in a detailed, insider account of what went wrong—and why ambitious ed-tech initiatives often fail to take root.
Ultimately, the Data & Society researchers contend, “the legacy of inBloom seems evolutionary, not revolutionary.” Its failures helped prompt a broad public discussion of student privacy, including the introduction of more than 400 bills in state legislatures around the country, they wrote. “It also surfaced the public’s low tolerance for risk and uncertainty, and the vulnerability of large-scale projects to public backlash,” the researchers said.
Education Week February 2017
Review of The Legacy of InBloom: “The story of inBloom is not one of straightforward failure, but rather of shooting for the sun and being scorched during the journey,” write the authors.
The intentions, misunderstandings, concerns and failures of inBloom captured in the report reflect issues that afflict the wider education technology industry. “No large-scale educational technology initiatives have ever succeeded in the U.S. K-12 space,” the authors claim. Yet inBloom’s collapse have spurred companies, districts,
data advocacy groups and governments to develop best practices for collecting, sharing and using education data. More than 400 state-level legislation concerning student data have since been introduced. EdSurge February 2017
“Although inBloom closed in 2014, it ignited a public discussion of student data privacy that resulted in the introduction of over 400 pieces of state-level legislation. The fervor over inBloom showed that policies and procedures were not yet where they needed to be for schools to engage in data-informed instruction. Industry members responded with a student data privacy pledge that detailed responsible practice. A strengthened awareness of the need for transparent data practices among nearly all of the involved actors is one of inBloom’s most obvious legacies.
Instead of a large-scale, open source platform that was a multi-state collaboration, the trend in data-driven educational   technologies since inBloom’s closure has been toward closed, proprietary systems, adopted piecemeal. To date, no large-scale educational technology initiative has succeeded in American K-12  schools. This study explores several factors that contributed to the demise of inBloom and a number of important questions: What were the values and plans that drove inBloom to be designed the way it was? What were the concerns and movements that caused inBloom to run into resistance How has the entire inBloom development impacted the future of edtech and student data?” The Legacy of InBloom
Why do we still talk about inBloom? “Ultimately, inBloom lacked a clear story of its benefits for teaching and learning,” said Monica Bulger, one of the coauthors of the report, “so it did not get the necessary buy-in from parents and schools. The legacy of inBloom matters because most current edtech platforms would fail the rigorous checklist applied to inBloom. Most current iterations are not transparent about their data use, do not resolve issues of data security, and fail to provide interoperability across platforms.”
Even as Basecamp and countless other tech-centered programs have taken off, there are few independent studies of the programs’ effectiveness, researchers say. “We really don’t know that much about personalized learning,” said Monica Bulger, senior researcher at the Data and Society Research Institute in New York. Washington Post, October 2016
The resulting uncertainty alone could have a big impact on schools and families, said Monica Bulger, a senior researcher at Data & Society, a New York City-based research institute focused on the social and cultural issues arising from increasing use of data-based technologies. “My concern is that right now there is a lot of fear and speculation,” Bulger said. “In an anti-immigrant environment, any data can become fair game to penalize families.” Education Week, January 2017
“The landscape of marketing in schools and among students has become an increasingly complex field. New technologies exist alongside traditional sponsorship contracts. Students are logging in to third-party platforms from school computers and doing research on Wikipedia, The New York Times, and YouTube alike. At the same time, parents, teachers, as well as local and federal lawmakers are all wrestling with the complications of new technologies and old regulations. What follows is a consideration of four major challenges in this area: the changing boundaries of “the school,” the difficulties of transparency, the murky legality of certain marketing practices, and a confusion of terms and practice with regards to data collection and use.” Advertising in Schools September 2016
Brief by co-author Alexandra Mateescu: Disentangling the Real and Potential Risks of Advertising in Schools
“The main problem is that researchers have done a poor job explaining the value of collecting and using student data for educational research. Much of the contributions of research to practice are invisible, especially when they are successful. There are no signposts to flag how early education becomes a priority, or a school starts serving breakfast, or why early-career teachers are paired with veteran mentors.” How Can Educational Researchers Better Communicate the Value of Our Work to the People We Study? August 2016
“Over the past couple years, the collection and use of student data has become increasingly controversial. The potential for data-driven learning analytics to improve student learning competes with concerns about safeguarding student privacy. As of January 2016, 188 student data privacy bills had been introduced nationwide (Anderson, 2015; Vance, 2015). Yet, while the use of student data has been a focus of discussion and critique, the promise of personalized learning remains mostly unchallenged. Key questions explored in this primer include: what, exactly is the rhetoric that claims personalized learning is promising, and why? Can an analysis show whether this technology is delivering what it promises? And what other concerns, absent from the discourse, do we need to be most attendant to when the educational sphere imports a framework of data collection from the world of start-ups and tech giants? This primer presents a typology of personalized learning systems that draws from media coverage, research, interviews, and informal discussions.”
Personalized Learning: The Conversations We’re Not Having, July 2016
“This study focuses on the role of highly active participants in online learning communities on Facebook. These people, often known as “power users” in the literature on social computing, are a common feature of a wide range of online learning groups, and are responsible not only for creating most of the content but also for getting discussion going and providing a basis for other’s participation. We test whether similar dynamics hold true in the context of online learning. Based on a transactional dataset of almost 10,000 interactions with an online community of 32 postgraduate students who were following the same online course, we find evidence that power users also exist in the context of online learning. However, whilst they do create a lot of content, we find that they are not fundamental to keeping the group together, and in fact are less adept at creating content which generates responses than other “normal” users. This suggests that online learning communities may have different dynamics to other types of electronic community: it also suggests that design efforts should not be focused solely on attracting a small core of “power learners.” Rather, diverse types of users are needed for online learning communities to survive and prosper.”
Proceedings of the Learning International Networks Consortium (LINC)’s seventh meeting held at Massachusetts Institute of Technology, 2016.
“Technologists like Nicholas Negroponte promote the idea that in the hands of a child a laptop can transform their world. Perhaps it can, but unfortunately, these anecdotal claims have caused many to believe they can simply drop laptops into a classroom, add internet access, parachute a variety of devices into poor, rural areas, and magically, learning outcomes will improve. This myth of an easy technical fix has led to misspent resources in struggling school districts as well as large ones. As demonstrated in the US by the failure of iPads in the Los Angeles Unified School District and New York City School’s recent ending of their relationship with Pearson, evaluations of technology use must be paired with consideration of the broader ecosystem of support and training.
When the OECD seeks to explain learning scores with high or low use of technology, they are pursuing a limited view of how learning happens. Much of the interesting work around technology and education looks at the broader picture of how children’s everyday social and digital practices impact their education (see, for example, It’s Complicated, The Class, Leveling Up, The Digital Edge).”
Is Using Technology for Learning a Good Idea? November 2015
“Massive open online courses (MOOCs) offer the possibility of entirely virtual learning environments, with lectures, discussions, and assignments all distributed via the internet. The virtual nature of MOOCs presents considerable advantages to students in terms of flexibility to learn what they want, when they want. Yet despite their virtual focus, some MOOC users also seek to create face-to-face communities with students taking similar courses or using similar platforms. This paper aims to assess the learner motivations behind creation of these offline communities. Do these face-to-face meetings represent an added extra to the learning experience, with students taking advantage of the context of the MOOCs to create new personal and professional connections? Or, are offline meetups filling a gap for students who feel that not all learning can take place online? We also assess the extent to which these patterns vary between developing and industrialised regions, thus testing the claim that MOOCs are helping to democratise access to education around the world. Our research is based on a unique source of socially generated big data, drawn from the website ‘meetup.com’, which gives us a data set of over 4000 MOOC related events taking place in over 140 countries around the world over a two year period. We apply a mixed methods approach to this data, combining large-scale analysis with more in-depth thematic hand coding, to more fully explore the reasons why some learners add a ‘real’ component to their virtual learning experience.” Information, Communication & Society, 2015

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