Big data 4 education

By Michaela Garberg

It has been argued by, for example, Schuurman[1] that information technologies and social media are transforming the way we learn and how our brains process knowledge.

Whatever one may think of such claims it seems evident that ICTs possess a great potential when applied within the areas of teaching and learning.

West[2] depicts a possible future scenario where Richard learns how to read with the help of a computerized software program, which monitors his progress, provides an automatic follow-up quiz and gives Richard instant feedback as well as links to additional learning resources. On top of all of this, Richard’s teacher will receive an automated transcript of Richard’s progress at the end of the session.

This is but one example of how big data can be applied within education. With the help of ICTs, the student is given individualized and instant feedback in a way that is almost impossible for a teacher to manage.

In many countries of the global South, big classes have been a constant obstacle for teachers and in many industrialized countries growing class sizes and more administrative work is putting higher burdens on teachers.

More than 25 million new teachers are expected to be needed globally by 2030, according to a report by UNESCO Institute for Statistics.

This figure accounts for both new teaching positions and replacement of existing teachers due to attrition, but the numbers are still startling. The situation is by far the worst in Sub-Saharan Africa.

In light of this situation, it could be tempting to rush towards trying to attract more new teachers to enter the classroom, but teachers remain the single most crucial aspect of quality teaching so we can’t neglect the need to take our time and properly educate them. So what can we do? 151005-wtd%20unesco%20infographic One initiative to provide quality education for children from low-income families was sparked by Bridge International Academies in 2009 when they opened a school in the Mukuru slum in Nairobi, Kenya. Five years later, in 2014, the academy had over 100,000 students enrolled. The concept is streamlined education based on research and facilitated through the use of technology such as tablets and smartphones which teachers receive with scripted lessons and assessments standards.

The systems also collect data through instructional monitoring and information on the individual students such as assessment scores, attendance and tuition payment. From the teacher’s tablet to the academy manager to the Bridge headquarters, all automatized and constantly updated.

This may seem as a harmless way of using big data for a good purpose, who would not applaud the effort to bring quality education to the children who need it the most? And as has been pointed out by West [2], data mining in education offers many opportunities to advance learning through the provision of formative assessment and instant feedback, for students and teachers.

This gathering of data does however also contain some possible risks regarding privacy.

  1. First of all, the data collected is on students who are minors and could not possibly give their informed consent.
  2. Second, it is possible that parents, who could consent on behalf of their children, are fully aware of the data collection and transmission, but it might just as well not be the case. Most of us today are transmitting a lot of data on a daily basis, most of which we’re probably not even aware.
  3. Third, considering these people represent some of the world’s poorest and most vulnerable citizens, also makes the data mining a bit more sensitive.

I don’t meant to argue that big data is a threat per se or that it should not be used; but currently there is an absence of a clear ethical framework for the use and sharing of big data, something that could be put in place to ensure big data is further explored in a way that benefits people without violating anyone’s rights.

References:

Schuurman, N. (2013). Tweet Me Your Talk: Geographical Learning and Knowledge Production 2.0. The Professional Geographer, 65:3, 369-377, 2013.

West, D. (2012). Big Data for Education: Data Mining, Data Analytics and Web Dashboards. Governance Studies at Brookings.

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3 comments

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