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Learning Analytics and AI: one of BJET’s top 10% downloads

Learning Analytics and AI: Politics, Pedagogy and Practices

This was the editorial by CIC’s Director Simon Buckingham Shum and UCL Knowledge Lab Professor Rose Luckin, to the final issue of the 50th Anniversary of the British Journal of Educational Technology. We’ve just heard that of all papers 2018-19, this is one of the top 10% downloaded articles in the year following online publication.

Buckingham Shum, S. & Luckin, R. (2019), Learning Analytics and AI: Politics, Pedagogy and Practices. British Journal of Educational Technology, 2019. 50(6), 2785-2793. https://doi.org/10.1111/bjet.12880

The following is an extract to give you a feel, but read the whole piece — it’s open access…

Politics, pedagogy and practices

This special issue provides resources to tackle this challenge, by engaging with these concerns under the banner of three themes: Politics, Pedagogy and Practices:

1. The politics theme acknowledges the widespread anxiety about the ways that data, algorithms and machine intelligence are being, or could be, used in education. From international educational datasets gathered by governments and corporations, to personal apps, in a broad sense ‘politics’ infuse all information infrastructures, because they embody values and redistribute power. While applauding the contributions that science and technology studies, critical data studies and related fields are making to contemporary debates around the ethics of big data and AI, we wanted to ask, how do the researchers and developers of LA/AI tools frame their work in relation to these concerns?

2. The pedagogies theme addresses the critique from some quarters that LA/AI’s requirements to formally model skills and quantify learning processes serve to perpetuate instructivist pedagogies (eg, Wilson & Scott, 2017), branded somewhat provocatively as behaviourism (Watters, 2015). While there has clearly been huge progress in STEM-based intelligent tutoring systems (see du Boulay, 2019; Rosé, McLaughlin, Liu, & Koedinger, 2019), what is the counter-argument that LA/AI empowers more diverse pedagogies?

3. The practices theme sought accounts of how these technologies come into being. What design practices does one find inside LA/AI teams that engage with the above concerns? Moreover, once these tools have been deployed, what practices do educators use to orchestrate these tools in their teaching?

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