CategoriesDigital learningEducation

Big Data in Education - Learning Outcomes

Written for Lilab.eu

BigDatainEducation

The first episode in of Big Data in Education introduced the opportunities arising by programmatically collecting and analysing educational data. The second episode detailed the Dimensions of Education Data, the so-called input space of the Big Data in Education. As anticipated before, this session talks about learning outcomes measurement, or namely how to transform learning performance and assessment indicators to take into account when deploying Big Data techniques in Education.

But if we now know where to collect data, why bother about the output at all? The output space is as important as the input as most of the supervised Big Data techniques consists in model or pattern discovering, through which is possible to perform automatic predictions or classifications.

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Continue the reading at lilab.eu

Published by daniele

Daniele is the owner and inventor of Dimstudio. All views are his own.

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