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Research/Solution - Assessment Analytics Recycling Bin

Assessment analytics
see http://publications.cetis.ac.uk/2013/750
Much of the research in this area has been carried out, but a wider questions are still out standing, some of which are listed in projects already on this site.
The benefit of focusing on this area is that it will provide greater benefit to 'blended' courses, and target data collection on maximising the type of data needed to make a deeper analysis of... more »

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Focus on Social Learning Analytics Recycling Bin

We need to move away from seeing Learning Analytics as being 'just' about diagnostics (spotting when a student is likely to fail so that we can make an intervention) and start to develop the use of analytics as a tool to support us in assessing students' competences, dispositions, and trajectory within their community of learning. This is about analytics as a tool to help us develop more authentic, 'real world' relevant... more »

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Research: generating analytics questions Recycling Bin

'Human readiness' for learning analytics isn't a given. It's important to ask under what circumstances learning analytics might be welcomed by teaching staff, students, and other decision-makers - in principle and practice.

The work of Anna Lea Dyckhoff advances a view of learning analytics as answering action research questions posed by teaching staff. Carrying out similar studies for other stakeholders - particularly... more »

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Solution: Learning estates and staff workloads Recycling Bin

The most expensive resources for most institution are the estates and infrastructure. The approach would be to develop a set of tools that allow institutions to examine use of estates for learning (i.e. teaching rooms) to ensure efficient use of rooms; explore staff workloads to help manage and costs courses.

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Research: Data warehousing and metrics guide

A report to inform institutions on what specific data they need to gather to do effective learner analytics. Combined with the metrics this will avoid all institutions from gather vast amounts of data unnecessarily and wasting time doing their own analytics to determine what correlations are significant for predicting student attainment.

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Research: Analytics Metrics

Research existing learner analytics and produce a basic summary of the metrics (what data matters and how to analyse it). This study would also provide some key learning from existing learner analytics that could be used by institutions to make informed decisions about their choice of analytics tools and how to interpret information. The report would also support a more DIY solution to the course/student dashboard.

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16 votes
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