Tamsyn Gilbert
William Cope
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Heather A OchmanNew Learning’s Updates
Evidence of Learning - What 'Big Data' Means
We've just published two articles that discuss the impact of new techologies on assessment of learning and research into learning. They summarize our thinking over the past several years as we have been developing Scholar. We've been imagining where all this ed tech stuff is heading.
- Sources of Evidence-of-Learning: Learning and assessment in the era of big data
- Interpreting Evidence-of-Learning: Educational research in the era of big data
We'd love to hear what you think. (Also, if you're picking this up via our Facebook and Twitter feeds, do sign up to Scholar and join this New Learning community here.)
Nice post..
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Thanks for these comments, Jon. I think you'd agree, we've barely scratched the surface of what is possible - and all sorts of challenges, dangers even, lie ahead. Still, it's an exciting time to be in education, things are very fluid.
Bill & Mary,
Thanks for sharing these
Sources is an excellent & stimulating account of the consequences of big data on assessment practices.
In grappling with this new era of big data I'm also interested in the kinds of questions that are emerging ... & the questions not (yet) being asked. Related topics of data governance, adaptive systems, metadata, and complexity also seem highly relevant.
With the rollout of learning analytics in the university sector it is common to encounter upside narratives concerning new sources of evidence of learning - particularly as an organizational strategy that links neatly with increasing student retention rates. While the cautionary narratives are also there they seem less prominent at this stage. Your paper strikes a nice balance.
While the Sources paper is not explicitly concerned with scrutiny of the relationship between data and learning content it seems that big data enables another function of data beyond evidencing: data (about the learner, the learning platform, and the learning content, etc.) is itself becoming a new genre of learning resource. Reflexively and recursively. This situation is strikingly different to the first waves of innovation in online learning in which the learning content and any data associated with it (metadata) were quite distinct. As your subsequent paper explores, this has significant impact upon developing learning platforms with sharable or interoperable data models and vocabularies. This is where data governance becomes important -- but it seems that any viable and sustainable framework will need to be both distributed and federated. That sounds hard.
Interpreting the consequences is likewise stimulating & I like the notion of practice-integrated research and the advocacy for a new generation of ‘educational data sciences’ [that] might require a reconceptualization of the nature of evidence and the dimensions of our research practices. The section on the reconfiguration of ethics should be on the recommended reading list of university ethics committees.
The key challenge here is the collection, curation, and analysis of vast quantities of disparate data -- and because of provenance and privacy issues data governance may need to enter the purview of research ethics.
... Having said that, I'm going to read your articles again!