Education Technology and Student Privacy

Elana Zeide, Education Technology and Student Privacy, 70–84 (Evan Selinger, Jules Polonetsky, & Omer Tene eds., 2018) The Cambridge Handbook of Consumer Privacy

15 Pages Posted: 30 Mar 2018

See all articles by Elana Zeide

Elana Zeide

University of California, Los Angeles

Date Written: March 21, 2018

Abstract

Education is increasingly driven by big data. New education technology (ed tech) creates virtual learning environments accessible online or via mobile devices. These interactive platforms generate a previously unimaginable array and detail of information about students’ actions both within and outside of classrooms. This information not only can drive instruction, guidance, and school administration, but also better inform education-related decision-making for students, educators, schools, ed tech providers, and policymakers. This chapter describes the benefits of these innovations, the privacy concerns they raise and the relevant laws in place. It concludes with recommendations for best practices that go beyond mere compliance.

Data-driven education tools have the potential to revolutionize the education system – and, in doing so, provide more access to better quality, lower-cost education and broader socioeconomic opportunity. Learners can access world-class instruction online on demand without having to be physically present or enroll in expensive courses. “Personalized learning” platforms, for example, use detailed, real-time learner information to adjust instruction, assessment, and guidance automatically to meet specific student needs. Information collected during the learning process gives researchers fodder to improve teaching practices.

Despite their potential benefits, data-driven education technologies raise new privacy concerns. The scope and quantity of student information has exploded in the past few years with the rise of the ed tech industry. Schools rely on educational software created by private companies that collect information about students both inside and outside of classroom spaces.

Three characteristics of the education context call for more stringent privacy measures than the caveat-emptor consumer regime.

First, student privacy protects particularly vulnerable individuals – maturing children and developing learners. Traditional rules seek to prevent students’ early mistakes or mishaps from foreclosing future opportunities – the proverbial “permanent record.”

Second, students rarely have a choice regarding educational privacy practices. In America, education is compulsory in every state into secondary school. Most schools deploy technology on a classroom- and school-wide basis due to practical constraints and a desire to ensure pedagogical equality.

Third, the integration of for-profit entities into the school information flow is still novel in the education system. American education institutions and supporting organizations such as test providers and accreditors have traditionally been public or non-profit entities with a primary mission to promote learning and academic advancement.

This chapter suggests best practices to cultivate the trust necessary for broad acceptance of new ed tech and effective learning spaces. These include accounting for traditional expectations that student information stays in schools, in contrast to the caveat emptor underpinning of the commercial context, as well as providing stakeholders with sufficient transparency and accountability to engender trust.

Keywords: ed tech, student privacy, FERPA, SOPIPA, student data

Suggested Citation

Zeide, Elana, Education Technology and Student Privacy (March 21, 2018). Elana Zeide, Education Technology and Student Privacy, 70–84 (Evan Selinger, Jules Polonetsky, & Omer Tene eds., 2018) The Cambridge Handbook of Consumer Privacy . Available at SSRN: https://ssrn.com/abstract=3145634

Elana Zeide (Contact Author)

University of California, Los Angeles ( email )

Los Angeles, CA
United States

HOME PAGE: http://www.elanazeide.com

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