Learning analytics 101
Published on Jan 09, 2019
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PRESENTATION OUTLINE
Why this topic?
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I have something to...
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Q: Why analytics?
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Q. As is?
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We need a
new mindset
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Q. Where do you get your data?
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Data is everywhere!
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Q. Benefits of
good analytics
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Descriptive
- What has happened?
- Who did what?
- More than 80%
- 'What courses did Mathias enrolled for?'
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Descriptive
- How many users logged in today?
- What are the completion rates?
- How much time are people spending per session?
- How many users never returned?
- Which pages do they like best?
- How many people are passing the courses?
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Predictive
- What might happen?
- If this, then that...
- Statistics & data models
- 'In what courses will Mathias enroll next year?'
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Predictive
- Cf. Amazon / recommendations
- Claimed by lots of LMSs
- Likeliness of ...
- Personalization
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Prescriptive
- What should happen?
- Links insights to actions
- A tough one :-)
- 'What courses should Mathias take to take the next step?'
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And in L&D?
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Statements?
- Mathias - Actor
- Bored - Verb
- The crowd - Object
- Set of statements = activity stream
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And now what?
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"We learn to create adaptive, personalized learning designs based on the interactions among learning experiences, content, and performance information."
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"Learners are able to motivate themselves to own their own learning if
we give them the means and the measures to engage and stay inspired."
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"Our organization will able to use learning as
the strategic organizational asset we claim it to be."
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