Depending on which courses you have taken prior to EDC, is it possible that the readings or authors listed below will already be familiar to you. The emphasis on recently-published articles and book chapters in our reading list reflects the currency of algorithmic culture within contemporary education, as scholars seek to understand how teaching, learning and other practices and spaces are affected by algorithms and their underlying biases and assumptions.
Core reading
Edwards, R. (2015). Software and the hidden curriculum in digital education. Pedagogy, culture and society, 23 (2), 265-279 https://doi.org/10.1080/14681366.2014.977809
As well as providing an engaging introduction to the presence of algorithms within contemporary education, Edwards argues that they contribute towards a kind of hidden curriculum, thereby challenging the tendency to regard technologies and computer-mediated communication simply as tools.
Kitchin, R. (2017). Thinking Critically about Researching Algorithms. Information, Communication and Society, 20(1), 14-29, DOI: 10.1080/1369118X.2016.1154087
Rob Kitchin uses this article to make a number of arguments around the need to think really critically around algorithms, while also proposing ways that we might go about doing so.
Knox, J., Williamson, B. and Bayne, S. (2020). Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies. Learning, Media and Technology, 45(1), 31-45. DOI: 10.1080/17439884.2019.1623251
The focus of this recent article by Knox, Williamson and Bayne is an examination of different visions of learning across humans and machines, considered in light of a near-future of intensive data analytics. Among other things, the authors argue that education in the future may tend towards behaviourist theories and machine-learning systems that conflict with ideas of student autonomy and participation.
Gaskins, N. R. (2019). Techno-Vernacular Creativity and Innovation across the African Diaspora and Global South. In Captivating Technology (pp. 252-274). Duke University Press.
This chapter, among other things, presents and defines the concept of techno-vernacular creativity (TVC) which ‘includes the integration of cultural or indigenous values identified in science and technology through the transfer of information such as metaphoric and iconic representations.’ The authors posits that historically marginalized, or under-resourced groups, routinely engage and remix the digital in ways that ‘challenge constructed meanings of “dominant” technology’. Algorithmic examples are presented that broaden the focus of this block of activity.
Secondary reading
Bayne, S., Evans, P., Ewins, R., Knox, J., Lamb, J., Macleod, H., O’Shea, C., Ross, J., Sheail, P., and Sinclair, C (2020). The Manifesto for Teaching Online. Cambridge MA (USA): MIT Press.
Two statements from the Manifesto for Teaching Online relate to the themes we are exploring in this part of the EDC course: Algorithms and analytics re-code education: pay attention! (section 13 of the book), and Automation need not impoverish education: we welcome our new robot colleagues (section 14).
Beer, D. (2017). The social power of algorithms. Information, Communication & Society, 20(1), 1-13. DOI: 10.1080/1369118X.2016.1216147
Approaching algorithms from a social science perspective, Beer argues that algorithms influence how we see the world, while at the same time playing a part our in social ordering processes.