Pedagogy driven analytics

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Ted Major. Dilemma

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Analytics and pedagogy

The Innovating Pedagogy report, Sharples et al (2015) lists 10 types of pedagogy that may transform education in the future. Here I explore three of them and look at how they could be supported by learning analytics.

Crossover learning

Crossover learning links educational content to those things that matter to learners in their everyday lives. It takes place in informal settings such as museums and field trips and these experiences are enriched by adding in knowledge from the classroom whilst educational experience is enriched by this everyday experience. These connected experiences spark further interest and motivation to learn.

Learners could be supported through analytics on users flow – quickly accessing paths they have previously followed. Teachers could be supported through being able to see where learners were active and how they related their informal surroundings back to classroom learning. This would enable individual follow-up and customisation.

Incidental learning

Incidental learning is informal learning that takes place outside the formal classroom and is unplanned and unintentional. Learning analytics could support the capturing of this learning through analysis of websites visited, how long the visits lasted, which pages were viewed and what was downloaded. Social networking could be analysed to help highlight the breadth of social learning taking place and device use could be assessed to understand which devoces were being used most for informal learning. Ultimately, through analysis, this type of learning may become more ‘visible’ to the leaner and offer a broader picture of the whole learning experience.

Adaptive teaching

Adaptive teaching recognises the unique qualities of learners and aims to offer a bespoke learning experience which engages each individual. Learning analytics could help educators offer a more bespoke learning experience rather than a one size fits all approach. Analysing learners’ previous and current learning creates a personalised path through educational content e.g. suggesting where to start new content and when to revisit and review previously viewed content. Learning analytics can also show and monitor progress. Educators could use this knowledge to ensure their students are on track and as an early warning sign for problems. It may also be possible to deduce which parts of the content are working and overall where students struggle and so can be harnessed to develop and improve the educational content and the overall learning experience.

H817 Week 22 Activity 8: Analytics and Pedagogy

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