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H817 MA ODE Open University, Block 4 Week 22 Activity 7
On reviewing Google Analytics it becomes apparent that these data have potential to generate learning analytics.
Here are some examples
Active users: tracking learners to see that they are still active and to give early warning indicators of potential drop outs.
User explorer: would allow individual tracking through the learning experience.
Cohort Analysis: defining common learner characteristics such as first time students versus seasoned students would allow cohort behaviours to be compared.
Demographics: understanding the age and gender composition gives the opportunity to tailor content and interventions.
Geo (language and location): helps in understanding any potential difficulties experienced by non native language speakers.
Behaviour: measuring how often learners return to certain learning activities or links could give insight into what needs improvement or what learners preferences are.
Technology and Mobile: understanding how learners access content could be useful in ensuring design is fit for purpose and planning for the future.
User flow: understanding the path learners take through a site could enable designers to improve the learner experience
The challenges associated with this include
- data protection of learners information and online behaviour
- ethical issues around the gathering and application of some of the above data e.g. Geo and User explorer
- the ability to gather data against every possible analytic may lead to data being gathered because it’s there rather than being gathered for a purpose
- data can only show what has happened, skill is required in identifying trends for planning e.g. technology and mobile.