BLOCK 1: BIG DATA AND ITS DISCONTENTS
Big data is abundant, and it is everywhere. But what are the consequences, whether designed or unintended, of this mass datafication for the present and future of education and society?
Big data refers to “data of a very large size, typically to the extent that its manipulation and management present significant logistical challenges”.
OED
What is big data? What is big about big data?
Simply put, data is words and numbers. Big data usually refers to data sets with sizes beyond the ability of commonly available software tools to capture, manage, store and process data within a tolerable elapsed time. Fundamentally, it requires a set of techniques and technologies with new forms of integration to generate insights from data sets that are diverse, complex, and of a massive scale.
Big data is commonly described in terms of four key characteristics:
VOLUME
Volume refers to the quantity of data generated and stored. The volume of the data often determines the value and potential insight to be produced, and whether or not it can be considered big data.
VARIETY
Variety refers to the type and nature of the data. Words or numbers, or a combination of both. Big data draws from text, images, audio, video, plus it fills in missing pieces through data fusion.
VELOCITY
There are in fact two kinds of velocity related to big data: the frequency of data generation, and the frequency of collecting, handling, recording, and publishing.
VERACITY
Veracity refers to the quality and value of data being generated and analysed. The quality of data can vary greatly, affecting its accurate analysis and interpretation.
The Birth of Datafication
Datafication is a technological trend whereby many aspects of our everyday lives are rendered into data, transferred into information realised as a new form of value. In this first video, Kenneth Cukier, outlines the rise of datafication and the 'becoming-informational' of the human experience.
Big Data and the Datafication of Everyday Life
The datafiction of everyday life continues at a relentless pace. The lure and pull of big data is immense: We are presented with endless visions of life and learning made better by big data in any of its current incarnations—data mining, predictive analytics, machine learning, deep learning, pattern recognition, statistical modelling, recommender systems, and, in education, learning analytics and educational data mining. Data is increasingly abundant, in often very mundane forms, generated, recorded, stored, processed manipulated and distributed at an unprecedented scale. This technological trend—and the tools, technologies, systems and processes which comprise it—renders aspects of life and learning into data, subsequently processed, quickly sifted and sorted, and translated into information and realised as a new form of value. It frequently goes unnoticed or overlooked, but exerts influence and power, designed or unintended, over our behaviour and thought.
READING
Williamson, B. (2018, March 17) 10 definitions of datafication in education, code acts in education [blog], https://codeactsineducation.wordpress.com/2018/03/17/10-definitions-datafication/
This blog post from Ben Williamson considers some potential definitions of datafication, with particular reference to education. He attempts to define the term historically, technically, epistemologically, ontologically, socially, politically, culturally, imaginatively, dystopically, and legally and ethically. As you read these definitions. consider which elements intersect with your own experience, particularly in the context of education. How would you define datafication? What is your own experience of datafication and how does this shape your definition?
Big Data in Education
In this second video, Cukier discusses how big data can potentially improve learning and why he feels the education sector has been slow to embrace it.
READING
Corrin, L., Kennedy, G. & de Barba, P. (2017, February 27) Asking the right questions of big data in education, Pursuit [blog], https://pursuit.unimelb.edu.au/articles/asking-the-right-questions-of-big-data-in-education
This short blog post considers some of the major challenges higher education faces with respect to trends in big data, learning analytics and educational data mining. We can count every click in a learning management system these days. Bit how does that actually help us to improve learning? How does that change the way we understand learners and learning? The authors argue that "[t]o enable education to be enhanced using learning analytics, educators need to focus on the right questions". But what are the right questions?
“Whilst capturing and analysing all of these kinds of data could have positive effects for research and practice, we need to think carefully about the social implications of this kind of use of the data. What happens to students who are most likely to drop out? Do we tell them, support them (which has economic implications), or let them sign up and take their money, knowing they will prob- ably fail? What happens to serendipity in a system where all educational choices are based on recommender systems? What kinds of learning can a student truly keep ‘private’? Does the potentially highly public and trackable nature of learning have impacts for the learning process? There are any number of questions of this kind, which need to be asked and critically considered every time data is analysed and used. Data, particularly Big Data, have a kind of kudos that needs to be treated with care, as the values that are designed in to the analysis process are not always properly considered or made explicit. ”
Rebecca Eynon, 'The Rise of Big Data' (2013)
ACTIVITY 1: REFLECTION
The Sources and Uses of Big Data in Everyday Life
Before moving on to Block 2, you might like to record some thoughts on the effects, both positive and negative, of big data on your everyday life. What are the main sources and uses of big data in your everyday life? How do you use and interact with data? How does big data influence your perception and your experience of everyday life? How might big data help or hinder learning in your own educational setting?
Post your thoughts to the Padlet below.