Big Data

Critical Educational Questions for Big Data, Part 2

Thursday, September 08, 2016 Comment server

I started a list of critical questions for big data in education earlier this week. This is a big topic, raising lots of big questions and serious topics and problems for further debate and discussion. Here, I focus on questions about big data ownership, divides, algorithmic accountability, issues about voice and literacy, and, finally, ethical implications and challenges of big data in education. Who “owns” educational big data? The sociologist Evelyn Ruppert has asked, “who owns big data?” noting that numerous people, technologies, practices and actions are involved in how data is shaped, made and captured.


Critical Educational Questions for Big Data

Monday, September 05, 2016 Comment computer wires

Big data has arrived in education. Educational data science, learning analytics, computer adaptive testing, assessment analytics, educational data mining, adaptive learning platforms, new cognitive systems for learning and even educational applications based on artificial intelligence are fast inhabiting the educational landscape, in schools, colleges and universities, as well as in the networked spaces of online learning. I was recently asked what I thought were some the most critical questions about big data in education today. This reminded me of the highly influential paper “Critical questions for big data” by danah boyd and Kate Crawford, in which


The Secret Sauce in Pokémon Go: Big Data

Thursday, July 14, 2016 Comment Pokemon Go screen shots

Unless you’ve been holed-up in a cave playing Minecraft, you’ve heard about (and possibly even played) the new augmented reality (AR) mobile game sweeping the globe, Pokémon Go. For sure, AR can be exciting and compelling, when properly designed, offering us an experience of co-presence with a virtual character or object. And, it’d be understandable if you attributed Nintendo’s success to its use of the AR camera. But, you’d be wrong. The game’s AR succeeds, in fact, because it turned big data into a game. With Pokémon Go, we are offered the opportunity to pretend our


The Boundaries of Data Collection

Thursday, January 28, 2016 Comment magnified data codes depicting privacy issue

I want to take a moment to examine how data collection has changed for us who teach and assess students. In the digitally augmented classroom, there should be concern for both corporate privacy and interpersonal privacy. While we have limited control over the corporate tracking and data-collection that takes place, it is possible to allow varying levels of interpersonal privacy in the digital classroom. To make participation highly visible, down to seeing who contributed what line in a paper or slide in a slideshow, brings in echos of the dreaded panopticon. Often, when I speak to


Turning Digital Learning Into Intellectual Property

Monday, January 25, 2016 Comment Human shadow made of codes depicting online privacy issue

The world’s largest publisher of educational textbooks and resources, Pearson, recently extended its work into digital media and learning. As well as producing innovative new digital learning resources and platforms, Pearson is also positioning itself as a major center for the analysis of educational big data. This has implications for how learning is going to be conceptualized in the near future, and begs big questions about how the private ownership of educational data might impact emerging understandings and explanatory theories of the learning process itself. The Big Data Gatekeeper Originally established in 1844, by 2014 Pearson


Learning in the Digital Microlaboratory of Educational Data Science

Monday, November 30, 2015 Comment close up of calculator keys

In the last few years, Educational Data Science has emerged as a new field of inquiry in educational research. Where did it come from, what is its likely future impact on the production of knowledge about educational practices and learning processes, and how might it affect studies in digital media and learning? In sociological research, it has become quite fashionable to conduct studies of particular academic fields, their historical origins and development, and their methods of knowledge production. Influential research has been conducted, for example, to trace the development of psychology, neuroscience, behavioural sciences, and the


Feeling Machines: The Psychopedagogies of Emotion-maximizing Media

Monday, September 14, 2015 Comment lego character with different paper faces depicting emotions

It is now possible to measure and manage emotions through mobile apps and other digital devices. As part of my current research exploring the expert practices and knowledge base of the emerging field of “educational data science,” I have been gathering examples of educational technologies that are designed to both monitor learners’ emotions through data mining techniques, and also to manipulate their feelings. I term these “psychopedagogies” of emotional maximization that are based on insights from the psychological sciences and delivered through digital media. They are also part of a wider trend in the digital control


Eating Robots: Data Diets and Hungry Algorithms

Thursday, July 02, 2015 Comment small robot holding computer chip next to laptop

What do robots eat? Contemporary digital data analytics systems feed on a diet of data produced through human activity. Through this feeding, robotic machines receive the informational nutrition required for their own development: to become smarter, more aware of their environment, more responsive and adaptive in their interactions with people. By eating human data, robots are learning. Feeding Societies The claim that we now live in a consumer society has become commonplace in academic research. People have become voracious consumers, but also, through their participation in social media environments, present themselves as desirable commodities for the


Making Education as Machine-readable as Digital Data

Thursday, June 04, 2015 Comment tattered coiled ruler

Data have long been used to manage education. Data appear to make the messy complexity of schools and schooling more easy to understand, and help policymakers in their decision making. Now, with the rise of “big data” and associated data processing, mining and analytics software, a new style of digital education policymaking is making education increasingly machine-readable. In particular, education policy is now being influenced to a significant degree by the design of the devices through which educational data are collected, calculated, analysed, interpreted and visualized. As a result, schools and classrooms are being configured as


Computing Brains: Neuroscience, Machine Intelligence and Big Data in the Cognitive Classroom

Monday, December 08, 2014 Comment detailed graphic of human brain function lights numbers

The human brain has become a major topic in education. The field of educational neuroscience, or neuroeducation, is flourishing. At the same time, a number of initiatives based in computer science departments and major technology companies are also taking the brain seriously. Computer scientists talk of developing new brain-inspired cognitive learning systems, or of developing new theoretical and computational understandings of the brain in order to then build new and more effective forms of machine intelligence. The important aspect of these synchronous developments in neuroscience and brain-based systems is that they are beginning to come together