Monthly Archives: March 2017

Favourite tweets!

Studying different analytical tools allows us a better view of ‘the processes inherent to analysis itself‘ (Knox, 2015), allowing us to see what might be considered success under their terms.

Knox, J. (2014). Abstracting Learning Analytics. Code Acts in Education ESRC seminar series blog. http://codeactsineducation.wordpress.com/2014/09/26/abstracting-learning-analytics/

Tweet! Political geographies

This map makes visible a geography of academic achievement with inherent class and race implications and shows educational achievement as both marking and constructing divisions in society.

Mapping the geography of academic attainment

Big data can be harnessed for good or wielded as unimpeachable fact to direct our action in pursuit of anothers’ gain. As Enyon states,

as a community we need to shape the agenda rather than simply respond to the one offered by others

(Enyon, 2013, p.238)

Eynon, R. (2013). The rise of Big Data: what does it mean for education, technology, and media research? Learning, Media and Technology. pp.237-240.

You Tube! OpenEssayist

 

I watched a demonstration of this automated essay-improving software on YouTube and desperately want to try it out to see if it works. I thought it interesting that in these days of hypermedia one of the aims of OpenEssayist was to ensure student essays followed the traditional beginning, middle and end, showing how our narrative linear literacies have not been challenged here.

Tweet! Never a single view of anything

Learning analytics can add to our understanding of the conditions for learning when used in conjunction with human judgement and triangulated with information from other sources. More importantly, it is a measure of wider political and societal concerns such as the marketization of education led by Silicon Valley giant corporations.

Algorithms made manifest

Image from https://hellohart.com/2015/05/25/the-mathematics-of-crochet/

by crocheting computer-generated instructions of the Lorenz manifold: all crochet stitches together define the surface of initial conditions that under influence of the vector field generated by the Lorenz equations end up at the origin; all other initial conditions go to the butterfly attractor that has chaotic dynamics. The overall shape of the surface is created by little local changes: adding or removing points at each step

Art or craft can make complex mathematics ‘visible’ for the layperson revealing its beauty and intricacies and opening up ways of understanding what composes our black boxed technologies.

The mathematics of crochet