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Looking for solutions in wrong places

By Audrey Watters, journalist, founder of Hack Education.

A writer specialized in education technology with her own blog on that topic — called Hack Education —, Watters believes that regarding the learning process we should focus on the individual level, rather than the massive one. Is big data going to give us the measure of “learning”, no matter how subjective the word is? Has this measure necessarily to be a number? By focusing on big data, wouldn’t be looking for the solutions in the wrong places? Get Watters’ reflections in the short video below, which was recorded at the EDEN Conference held in Barcelona.

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Big Data needs a human network

By David Weinberger, senior researcher, Berkman Center for Internet & Society, Harvard University.

Big Data certainly makes smarter the fields of science and scholarship that use it. But does it make society smarter? For that we need to look at the network that connects our giant computing machines to data, to other machines, and to society.

If we had today’s stupendously powerful computers but no network connecting them, we could still do some forms of Big Data analysis. But real-time analysis of data would be severely hampered, and the vital work being done on data coming from the worldwide arrays of sensors would be all but impossible.

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For personalized education big data is a must

By Nuria Oliver, scientific director at Telefónica R&D.

According to computer scientist Nuria Oliver, there are three main key elements regarding big data in education, being the first one the so promised personalization, so that teachers could get precise information of how students are doing and thus adapt their methodology to specific needs. Secondly, large scale data could also be extremely useful for official statistics: e.g., how a city, a specific region or even a whole country is doing in terms of education. And, finally, we also need to make sure students’ data is securely stored and kept under high privacy standards. We would like to thank the TEDxBarcelona Education event for this contribution.

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Big Data, Learning Analytics and Distance Education

By Terry Anderson, professor in Distance Education, Athabasca University.

As an educational technologist, I seem always infatuated with the latest tools, even as I grow increasingly alert to what is lost as well as what is gained from their use.

Learning analytics joins the family of mostly commercial applications based on “big data”. These tools promises — perhaps too optimistically — to replace metaphors of information overload, info glut and obesity with the more optimistic sense that, although “big” we can effectively gather and interpret the torrent of digital information traces left by distance teachers and learners.

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Sharing best practice to make the most of big data

By Phil Richards, Chief Innovation Officer, Jisc.

So far perhaps big data and analytics are not shaping a wiser society: the way many people experience analytics is when they see personalised adverts for things they have just bought, and are not likely to want to buy again so soon! By analogy, using analytics to present more online resources for things that have just been learnt is not so useful, but as the predictive nature of analytics gets smarter — so that people are presented with what they want to buy next, or learn next — then I think that will assist a wiser society.

From our point of view, Jisc’s traditional strengths lie at each end of the modern digital stack: at one end, our data traversing Janet network, helping world-class research and discoveries such as the Higgs boson at the Large Hadron Collider (LHC) in CERN; at the other, modern digital content, data and metadata around academic publications and online learning materials.

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Getting to Know Ourselves (Really)

By Alyssa Wise, Associate Professor, Faculty of Education, Simon Fraser University.

How much do you really know about how you learn best? While most of us would like to think that we know ourselves pretty well, research shows that our recollections of how we go about learning something (or studying for a test or writing an essay) are actually quite poor.

This is an area in which learning analytics can be especially helpful by providing us with accurate data about what we do when learn online and whether or not how we are currently going about things is effective for us.

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Towards a gender neutral curriculum

By Anne-Marie Imafidon, founder and head of Stemettes.

Big data and analytics are here to stay, and they certainly can allow us to make smarter decisions, but what could they imply regarding STEM education? As founder of Stemettes, an organisation promoting women into science and tech fields, Imafidon sees those areas as an opportunity to advance into a more inclusive curriculum, making STEM fields more attractive to everyone. Don’t miss her reflections on the topic in the short video below. Imafidon’s contribution was possible thanks to the kind collaboration of the TEDxBarcelona Education event.

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About the Question
Are Big Data & Analytics shaping a smarter society?

Every day we generate a huge amount of big data, but we need to resort to analytics to make abstract information meaningful and get valuable knowledge from it. In education, learning platforms let us easily gather an immense quantity of data regarding students’ behaviour, interactions, preferences and opinions. When properly analysed — through learning analytics — all these data might provide useful insight on how to make learning processes more adaptive, attractive and efficient.

Are these techniques allowing us to provide better support to our students? Are we taking advantage of big data and analytics to help shape the citizens of the future?

Big Data and Simheuristics
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