Although we're currently nowhere near this idea, how can businesses, educational institutions, and governments alike not consider the importance of giving individuals control over their digital archives? Or their learning analytics data?17

more than just a student's schoolwork; they should also include personal photos, videos, transcripts, X-rays, dental records, police records, and a million other digital life-bits.

institutional demands for enterprise services such as e-mail, student information systems, and the branded website become mission-critical

privacy concerns

A simple search function allows teachers to search for specific text strings found in either the xAPI statements or in the text responses typed in by students.

While the teacher can correlate individual responses with the children’s names, no one else—not the app, not the museum—has any personal information about the learners.

creates a highly personalized experience for the children while simultaneously alleviating privacy concerns.

it's important to consider what could happen if a student does ask for their data

self-regulating effect

As higher education professionals, we would be remiss if we left out one of the most important potential benefactors of xAPI and learning analytics: students.

If you used our Physical web beacon today to login, you were generating xAPI statements.

institutionally controlled assessment and collection of data

Mount St. Mary’s use of predictive analytics to encourage at-risk students to drop out to elevate the retention rate reveals how analytics can be abused without student knowledge and consent

Kroton, the country’s largest university, has about 2 million students

Obviously, securing student data is critical. There are a lot of data sharing services that shouldn’t be offered until that security can be guaranteed.

And I see no good reason why we should require the production of educators and students to be fair game for resellers who want to pluck it for free out of the commons and charge money for it to those not lucky enough to be a part of our community.

Adoption should not be ‘one-or-the-other’, instead it is a ‘horses-for-courses’ decision;

Add xAPI -> https://h5p.org/documentation/x-api Tiki should become a Learning Record Store or a FLOSS solution picked for WikiSuite.

By giving student data to the students themselves, and encouraging active reflection on the relationship between behavior and outcomes, colleges and universities can encourage students to take active responsibility for their education in a way that not only affects their chances of academic success, but also cultivates the kind of mindset that will increase their chances of success in life and career after graduation.

The learning analytics and education data mining discussed in this handbook hold great promise. At the same time, they raise important concerns about security, privacy, and the broader consequences of big data-driven education. This chapter describes the regulatory framework governing student data, its neglect of learning analytics and educational data mining, and proactive approaches to privacy. It is less about conveying specific rules and more about relevant concerns and solutions. Traditional student privacy law focuses on ensuring that parents or schools approve disclosure of student information. They are designed, however, to apply to paper “education records,” not “student data.” As a result, they no longer provide meaningful oversight. The primary federal student privacy statute does not even impose direct consequences for noncompliance or cover “learner” data collected directly from students. Newer privacy protections are uncoordinated, often prohibiting specific practices to disastrous effect or trying to limit “commercial” use. These also neglect the nuanced ethical issues that exist even when big data serves educational purposes. I propose a proactive approach that goes beyond mere compliance and includes explicitly considering broader consequences and ethics, putting explicit review protocols in place, providing meaningful transparency, and ensuring algorithmic accountability. Export Citation: Plain Text (APA

My own response has been to focus on personal analytics, but this has been a hard sell.