what everyday teachers will learn from analytics in 2013

What everyday teachers will learn from analytics in 2013

Phillip DawsonOffice of the PVC (Learning & Teaching)

Monash University

“the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (SoLAR)

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“In praise of pessimism” (Selwyn)

• Educational technology as a “positive project”• Educational technology as a “computerisation

movement”• Focused on “proof of concept”• “State of the art” vs “State of the actual”

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[we should be] “refocusing the imaginations of educational technologists away from some of the wilder ‘science fictions’ of their particular areas of technological interest and instead encouraging greater engagement with the ‘social facts’ of education, technology and society” (Selwyn, 2011, p. 717)

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Sci-fi LA vs Mundane LA

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Sci-fi vs Mundane LA

Sci-fi:• Promises• Vaporware• “Proof of concept”• Closed (or magic)• Amazing• Optimistic• Expensive

Mundane• Realities• Available now• Enterprise• Open (source or algos)• Unimpressive• Pessimistic• Free/cheap

What are the affordances of mundane LA for everyday teachers?

• In groups, 10 minutes

• Lots of affordances• Tools must be:

– real – available – enterprise

• We will share back

Eg:• Count the number of

accesses of a resource• Tells you who has

submitted their assignments

Mundane affordances

• <this slide will be used during presentation to write down the affordances of mundane LA tools>

A typical mundane LA tool

• Gathers data on student use of parts of LMS• No integration with Student Management

Systems• Teacher dashboards• Reports• Some synthesis• Inconsistent design and language

– At code + UI levels

State of the Actual:Free/open/built-in LA

• Open-source tools– Engagement Analytics (documentation, demo vid)– Gismo– Analytics and Recommendations

• Vendor-supplied reports – (eg Desire2Learn)

The following are real-life challenges a university teacher has faced in 2013

It’s the end of week 2 and “student X” hasn’t ever logged in.

What do we do?

Issues

• How can we make follow-up effective– Personal or robotic?– Paint a grim picture?– Refer on or see personally?– Specific guidance

It’s the week of the census and modeling suggests “student X” is 70% likely to fail.

What do we do?

Issues

• Do students have a– Right to try (and fail?)– Right to give up– Right to be strategic

• Will draconian measures lead to ‘gaming’?• Student-identified triggers

It’s week 10 and “student X” already has 60% of the course grade but hasn’t logged in for two weeks.

What do we do?

“I think a lot of us have good intentions,

we just don't have the time” – science

lecturer

What will everyday teachers will learn from analytics in 2013?

Problem!Solution?

Teaching/Learning

Assessment

Objectives/Outcomes

(Biggs, 1999)

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[we should be] “refocusing the imaginations of educational technologists away from some of the wilder ‘science fictions’ of their particular areas of technological interest and instead encouraging greater engagement with the ‘social facts’ of education, technology and society” (Selwyn, 2011, p. 717)

What are the “‘social facts’ of education, technology and society” analytics will highlight in 2013/14?

More information

http://philldawson.com

This presentation includes ideas from research supported by the Australian government Office for Learning and Teaching, and the NetSpot Innovation Fund

References• Biggs, J. (1999). What the Student Does: teaching for

enhanced learning. Higher Education Research & Development, 18(1), 57-75. doi: 10.1080/0729436990180105

• Selwyn, N. (2011). Editorial: In praise of pessimism—the need for negativity in educational technology. British Journal of Educational Technology, 42(5), 713-718. doi: 10.1111/j.1467-8535.2011.01215.x

• Society for Learning Analytics Research. (2013). About Retrieved January 30, 2013, from http://www.solaresearch.org/mission/about/