Higher Education and Big Data: Vision, Ongoing Research, and Pragmatic Perspectives

Invited Talk at NWO/MinOCW meeting on Big Data in Higher Education

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Higher education is at a crossroads in the 21st century. Around the world, the student body is massivizing and diversifying, the industry is requiring more complex skills, the educators feel overwhelmed and under-recognized. In the Netherlands, the 200th ministerial report on the Status of Education ("De Staan van Onderwijs") reveals a high-quality system, but also with an increasing gap to the international top-level, and having to respond to changes in demographics and societal challenges. To address problems of scale and complexity, various domains of human activity have adopted IT and more recently Big Data capabilities. The question "How can Big Data help alleviate the challenges of modern higher education?" arises naturally, and is the focus of this talk.

To answer this question, we first warn that Big Data is not just "lots of data" or a universal panaceum. Instead, we identify a variety of opportunities and threats when using Big Data, considering technological, ethical, and legal perspectives. We propose our view of what Big Data is, from technology that automates, to transformative approach in how we understand and answer complex questions, to threat if left unchecked or in malicious hands.

We then focus on the use of Big Data in education, and survey use-cases from pilot-projects in the Netherlands, and studies done in conjunction with Khan Academy, Coursera, and edX. Although some of these are still at ideation stage, we discuss, among other benefits, how: (1) learning analytics (educational data mining) could help with guiding students to achieve more even when the higher education is becoming more international and otherwise diverse, (2) automated feedback and dynamic recognition for achievement could help increase accountability and reduce discrimination for both students and educators, (3) student log-books and student portfolios could create new opportunities for teaching, (4) adaptive use of learning objects could guide a new generation of learning design and enable new didactics, and (5) data-driven workflows could optimize education processes and reduce the burden of bureaucracy. We also explain the gap between the state-of-the-art in Big Data technology and what support for innovation is needed to address the emerging technology challenges of higher education.

Last, we make various predictions about the use of big data in higher education over the next decade, based on our personal experience and also on lessons drawn from recent studies in the Netherlands.