Chris Blackmore - Using Learning Analytics to Deliver Personalised Feedback to Online Learners. TELFest 2016 presentation

2. Using Learning Analytics to
Provide Personalised
Feedback to Online Learners
Chris Blackmore, University Teacher, ScHARR

3. 01/07/2016 © The University of Sheffield

4. 01/07/2016 © The University of Sheffield
Learning analytics is 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
Call for Papers of the 1st International Conference
on Learning Analytics & Knowledge (LAK 2011)

5. 01/07/2016 © The University of Sheffield
Why use learning analytics?
Data is already being collated
Can we use this productively, e.g. to enhance
student experience?
Where is the added value, e.g. can it tell us things
we otherwise would not know?

6. 01/07/2016 © The University of Sheffield

7. 01/07/2016 © The University of Sheffield
Understand the variety of data available

8. 01/07/2016 © The University of Sheffield

9. 01/07/2016 © The University of Sheffield
Harvest the data (and clean if necessary)

11. Analyze (at appropriate level)

12. 01/07/2016 © The University of Sheffield

13. 01/07/2016 © The University of Sheffield
Distribute personalized feedback to learners

14. 01/07/2016 © The University of Sheffield
A worked example
Pilot project in 2015-16
From a ScHARR PGT module on e-learning
programme
10 students
Data to be analyzed – discussion forum postings

26. Clout
Analytical thinking
Authenticity
Emotional tone

27. 01/07/2016 © The University of Sheffield
Analytical thinking - Captures the degree to which
people use words that suggest formal, logical, and
hierarchical thinking patterns

28. 01/07/2016 © The University of Sheffield
Clout - refers to the relative social status,
confidence, or leadership that people display
through their writing or talking

29. 01/07/2016 © The University of Sheffield
Authenticity - When people reveal themselves in an
authentic or honest way, they are more personal,
humble, and vulnerable

30. 01/07/2016 © The University of Sheffield
Emotional tone - puts positive and negative
emotions into a single summary variable. The higher
the number, the more positive the tone. Numbers
below 50 suggest a more negative emotional tone.

38. So what?

39. So what?
Pilot project – data was not presented to students
No evaluation yet, e.g. how helpful was it to students
and tutors?
Does it really make a difference to participation,
engagement, results or satisfaction?

40. But…
Only worth doing if it fits with learning objectives
VLE issues, e.g. work involved in harvesting,
analyzing and distributing data
Type of learning will impact on nature and volume of
data available, e.g. not all courses generate enough
discussion forum postings for analysis
Ethics

41. c.m.blackmore@sheffield.ac.uk
@chrisblackmore
http://elearningemotions.blogspot.co.uk/

42. Images
https://commons.wikimedia.org/wiki/File:7-
alimenti,pane,Taccuino_Sanitatis,_Casanatense_4182..jpg
https://pixabay.com/static/uploads/photo/2015/01/24/07/06/wheat-609929_960_720.jpg
http://www.rgbstock.com/bigphoto/n0mRho6/northern+riverland
https://www.flickr.com/photos/mdpettitt/14688135310
https://en.wikipedia.org/wiki/Bread_machine
https://commons.wikimedia.org/wiki/File:Vegan_no-
knead_whole_wheat_bread_loaf,_sliced,_September_2010.jpg
https://en.wikipedia.org/wiki/Whole_wheat_bread#/media/File:Vegan_no-
knead_whole_wheat_bread_loaf,_September_2010.jpg
https://commons.wikimedia.org/wiki/File:Roman_Army_Bread_-
_Ingredients_(12119594175).jpg
https://www.flickr.com/photos/9139977@N05/581062514
https://www.pexels.com/photo/bread-food-healthy-breakfast-2434/

43. 01/07/2016 © The University of Sheffield

44. 01/07/2016 © The University of Sheffield

45. 01/07/2016 © The University of Sheffield