Provision of personalized feedback at scale using learning analytics
Using Learning Analytics to Deliver Online Feedback
Transcript of Using Learning Analytics to Deliver Online Feedback
Using Learning Analytics to Provide Personalised Feedback to Online Learners
Chris Blackmore, University Teacher, ScHARR
01/07/2016 © The University of Sheffield
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)
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?
01/07/2016 © The University of Sheffield
01/07/2016 © The University of Sheffield
Understand the variety of data available
01/07/2016 © The University of Sheffield
01/07/2016 © The University of Sheffield
Harvest the data (and clean if necessary)
Analyze (at appropriate level)
01/07/2016 © The University of Sheffield
01/07/2016 © The University of Sheffield
Distribute personalized feedback to learners
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
CloutAnalytical thinking
Authenticity
Emotional tone
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
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
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
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.
So what?
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?
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
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01/07/2016 © The University of Sheffield
01/07/2016 © The University of Sheffield
01/07/2016 © The University of Sheffield