Archive - March 2014

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Quantifying deeper learning dispositions for the future data cloud
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Assessing learning dispositions/academic mindsets

Quantifying deeper learning dispositions for the future data cloud

The Big Data in Education workshop in George Mason University, Washington DC, is asking: How might we, from scratch, design digital platforms to model multiple data streams from multiple sources in a generalized ecosystem of learning to make predictions about learning based on changes to instruction? We envision MOORs as digital terrains traversed by learners across formal and informal education (e.g., schooling, museums, the internet), and across the lifespan. Slides from my intro talk, which connected Ruth and Chris’s research at Bristol University and Incept Labs, with emerging concepts of the future learner’s personal data cloud, in which I manage the release of my behavioural and somatic data to boost my learning analytics… Learning Analytics : quantifying deeper learning dispositions? from[…]

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Assessing learning dispositions/academic mindsets

A few years ago Ruth and I spent a couple of days with the remarkable Larry Rosenstock at High Tech High, and were blown away by the creativity and passion that he and his team bring to authentic learning. At that point they were just beginning to conceive the idea of a Graduate School of Education (er… run by a high school?!). Yes indeed. Now they’re flying, running the Deeper Learning conference in a few weeks, and right now, the Deeper Learning MOOC [DLMOOC] is doing a great job of bringing practitioners and researchers together, and that’s just from the perspective of someone on the edge who has only managed to replay the late night (in the UK) Hangouts and[…]

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