Algorithmic Play
Education and Digital Culture 2020
University of Edinburgh-Digital Education
s1891551
Algorithms
Reading through Ben Williamson's initial chapter in Big Data and Education. The digital future of Learning, Policy and Practice (2017), together with another contribution of his in Startup Schools, Fast Policies, and Full Stack Education Companies (2018), it dawned on me how the relationship between Silicon Valley entrepreneurs, governments and philanthropists has grown stronger as efforts to personalize education and provide tailor-made solutions are being advertised as the new face of education.
This has also been facilitated by the shortcomings associated with classical forms of schooling, such as a 'one-standard for all' methodology or the limitations imposed by learning systems dependent on fixed institutions bound by the political and economic legislations of the country.
Images:
Above: PublicDomainPictures at https://pixabay.com
Above right: cherylt23 at https://pixabay.com
How do you go about Personalizing something? Google, Ebay, Amazon, Booking.com, Netflix and many more have given autonomy to buyers by providing them with the choices necessary to make better and more educated guesses. Shorter routes, better prices, more economical accommodation and more popular entertainment have liberated the public from the need to study large quantities of available data in order to find a winning solution. Before the advent of big data collection, this was not possible.
When a company has found its winning solution, it is only natural that it will apply it to as many spheres within its capacity as possible. Others will do likewise, either by jumping on the bandwagon and 'renting' the services of these giants or by growing into giants themselves.
Our previous block in Digital Education and Digital Cultures has been an occasion to observe how online communities are born and survive, yet it has also been proof of how companies like EdX, Coursera, Futurelearn and others use similar techniques to collect, study, develop and provide the public with learning solutions that suit the needs of modern societies. by providing learning whenever and wherever it is needed.
Over the next few pages, I have tried to experiment with different algorithms embedded in a number of online platforms to understand how corporations are 'applying algorithmic processes, such as machine learning, predictive analytics, and adaptive systems to engineer better‐managed and more efficient systems of personalized learning (Williamson et al, 2018).