Skip to main content
Social Sci LibreTexts

7.1: Case Study- The Datafication of Education

  • Page ID
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

    ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\id}{\mathrm{id}}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\kernel}{\mathrm{null}\,}\)

    \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\)

    \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\)

    \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    \( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

    \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

    \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vectorC}[1]{\textbf{#1}} \)

    \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

    \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

    \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

    \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    Datafication sounds like a complex term – or perhaps something in the realm of conspiracy theorists – but it’s alarmingly simple for companies and developers to collect data about many aspects of our lives. With the rise of 1:1 devices in schools and the increased prevalence of students carrying their own phones, it becomes even easier. In fact, some educational apps collect an incredible amount of data on students.

    A study by Atlas VPN found that 98% of iOS educational apps gather user data, with each app on average collecting information from over 8 data segments. This can include names, emails, phone numbers, location, payment information, and search history, among others. Duolingo, a popular language learning app, topped the list by collecting user data across 19 segments. Other notable data-hungry apps include Busuu, another language learning app, and Google Classroom, a learning platform, both of which collect data from 17 segments.

    The study analysed the App Store privacy labels of 50 popular iOS apps in the education category, ranking them based on the number of personal user information segments collected. However, it should be noted that some apps collect data that cannot be linked back to a user’s identity, and these data segments were not included in the total count. The primary purposes for collecting data were app functionality (86%), analytics (80%), personalisation (56%), and developer’s advertising or marketing (54%). However, 24% of the apps also used collected data for third-party advertising, passing user information on to other organisations.

    It’s worth noting of course that Atlas VPN has its own agenda for the research: Virtual Private Networks are used to circumvent data gathering for all kinds of purposes, and Atlas VPN uses its research to support the sales of its own products. Nevertheless, there’s still a huge quantity of personal and identifying data being gathered by these apps.

    7.1: Case Study- The Datafication of Education is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by LibreTexts.

    • Was this article helpful?