The essential and additional readings for block one of the course are available below. You will need to be logged in through EASE to access most of these sources. You can also link to the readings through the course Resources List here.
You will need to read the four essential readings over this 3-week block, alongside undertaking your weekly data visualisation task. The additional literature will provide some useful further reading, and in the case of the video, listening and watching, to support your exploration in this block. In particular, you are encouraged to read Eynon’s (2015) paper on the ‘quantified self’ in education during week 4.
Tsai, Y-S. Perrotta, C. & Gašević, D. 2020. Empowering learners with personalised learning approaches? Agency, equity and transparency in the context of learning analytics, Assessment & Evaluation in Higher Education, 45:4, 554-567, DOI: 10.1080/02602938.2019.1676396
This paper critically examines the extent to which technologies associated with ‘learning analytics’ offer ‘personalised learning’ for students. A central focus here is the tension between ’empowering’ students through the application of the technology and subjecting students to increasing ‘datafication’. The paper reports on research conducted with staff and students, analysed around the themes of ‘agency, equity and transparency’.
Bulger, M. 2016. Personalized Learning: The Conversations We’re Not Having. Data & Society working paper. Available: https://datasociety.net/pubs/ecl/PersonalizedLearning_primer_2016.pdf
Bulger’s paper provides a detailed examination of the notion of ‘personalised learning’, suggesting that while the phrase has become popular in recent years, there is little critical reflection on what the idea means, or whether it is actually beneficial. This is quite a long paper – the key aspects to focus on are the discussions of ‘data-driven’ personalisation, and the section on ‘concerns’.
Knox, J, Williamson, B & Bayne, S 2019, ‘Machine behaviourism: Future visions of “learnification” and “datafication” across humans and digital technologies‘, Learning, Media and Technology, 45(1), pp. 1-15.
In this paper Knox, Williamson, and Bayne examine links between Gert Biesta’s concept of ‘learnification’ and the rising notion of ‘datafication’ in education. They argue that, while ‘learnification’ constitutes an important critique of assumptions about the centrality of learners in education, the increasing use of data-driven technologies are reintroducing behaviourist theories of control that reduce student agency.
Friesen, N. 2019. “The technological imaginary in education, or: Myth and enlightenment in ‘Personalised Learning.” In M. Stocchetti (Ed.), The digital age and its discontents. University of Helsinki Press.
Friesen offers a useful philosophical and historical critique in this paper, questioning the long-held assumption that learning is most ‘authentic’ when practiced through a one-to-one relationship with a teacher. While data-driven educational software, particularly those claiming to be ‘AI’, are habitually promoted through the idea of providing automated one-to-one feedback, Friesen argues that, far from being the ultimate goal of the project of education, personalisation is better understood as an enduring myth.
Bulger, M. 2016. Personalized Learning: The Conversation We Need. Talk given by Monica Bulger, covering many of the issues discussed in the above paper.
(2015) The quantified self for learning: critical questions for education, Learning, Media and Technology, 40:4, 407-411,
Thompson, G. and Cook, I. 2017. The logic of data-sense: thinking through learning personalisation. Discourse: Studies in the Cultural Politics of Education. 38(5), pp. 740-754