This is the first week of our first theme: ‘learning’ with data, in which we’ll consider the implications of using data in education in terms of their impact on our understanding of ‘learning’. As suggested in the outline to this block, there are a number of ways we can approach this theme, from thinking about how student learning is shaped by data, to what kinds of learning we need to undertake in order to become ‘data literate’, to the specific kind of ‘learning’ now undertaken by machines.
We’ll accompany these considerations with some dedicated reading, particularly around the idea of ‘personalised’ learning provided by data-driven educational technology. The focus of this week is to look beyond the straightforward promise of ‘personalisation’ – that analytic or artificially intelligent software can straightforwardly individualise educational pathways and experiences in the most effective way – and explore how such technologies function, what ideas about learning are already embedded in their functioning, and what the implications are for automating student activity in such ways.
Our reading will be supported with our first ‘tweetorial’ – some intensive tweeting about the readings and associated concepts. The tweetorial will take place on Tuesday, Wednesday, and Thursday this week, with each day guided by a central question, as follows:
Tuesday question: How is ‘learning’ understood, promoted, and produced through data-driven technologies in education?
Wednesday question: What is ‘personalisation’ and how is data involved in producing it?
Thursday question: Who learns from ‘big data’ in education?
Your key tasks this week will be to:
- Read the core (and secondary) literature for block 1
- Participate in the Tweetorial on Twitter using #msccde (Tuesday to Thursday)
- Complete your weekly data visualisation