Learning analytics: At the intersections between student support, privacy, agency and institutional survival

Learning analytics: At the intersections between
student support, privacy, agency and institutional
survival
Paul Prinsloo (University of South Africa, Unisa) @14prinsp
Sharon Slade (Open University, OU) @sharonslade
Imagecredit:https://www.flickr.com/photos/haydnseek/2534088367

Image credit: http://www.yourtango.com/201168184/facebook-relationship-status-
what-does-its-complicated-mean

HIGHER EDUCATION
Image credits:
Survivor image: Adapted from https://commons.wikimedia.org/wiki/File:Survivor_Bermuda_Logo.jpeg
Murky middle: https://s-media-cache-ak0.pinimg.com/736x/5c/58/07/5c58072b5f003d7a69b129cb6f8055b6.jpg
Triage: https://en.wikipedia.org/wiki/Triage
Surveillance camera: http://www.governmentnews.com.au/wp-content/uploads/2014/02/cctv_camera.jpg

HIGHER EDUCATION
• Increasing competition, changing contexts, internationalisation
• Rankings and quality regimes/criteria
• Increasing funding constraints and austerity measures
• Funding follows performance rather than preceding it – the need for
evidence
• Persisting concerns about student retention, failure and dropout
• History of well-intentioned but often bang-bang approaches to increasing
student retention and success
• The mandate and fiduciary duty of higher education
• Optimising the student experience, ensuring student success/throughput
Survivor – the Higher
Education series (new
rules, new contestants,
better than ever)

• Determine criteria/characteristics
• Calculate cost of care/intervention/return on
investment
• Implementation – educational triage
• Evaluation
Moving the murky middle/drowning the
bunnies

Engaging with (some) assumptions &
practices re the need for (more) data
• Our (mis)understanding of student
retention, success and failure
• Can we assume that knowing more, per
se, results in understanding and care; that
more data will necessarily contribute to
better teaching and learning?
• The danger of context collapse and the need to ensure context integrity
when data collected from disparate sources and for a variety of purposes
are combined
• The inherent biases, dangers and potential of algorithmic decision-
making
• The scope of students’ right to privacy

Educational triage in practice
• School league tables can lead to a
focus on key boundaries
– Evidence that the ‘murky middle’
overlooked in favour of those most
able to support achievement of
key results
• Traditional classroom-based
universities
– potential focus on ‘seen’ or
perceived need
– often driven by individual subject
tutors
• Distance learning institutions
– largely reliant on student data to
direct support
– often driven by available data and
assumed patterns

Analytics in practice at the Open University
Framework for consistent support
– Drives minimum set of proactive
interventions through curriculum focused
Student Support Teams to all students
– Additional core interventions target students
based on characteristics (potentially ‘at risk’)
and/or study behaviours
– Large number of possible proactive
interventions (e.g., missed milestones, etc)
– Prioritising interventions is complex: which
characteristics/milestones/behaviours/
modules take precedence? Who decides?
– Results in non-standard support largely not
transparent to students and driven by
available staff resource

Some considerations…
• We cannot ignore the reality of ‘Survivor: Higher Education’
• The impact of funding, resources and contexts on the ‘murky middle’
• The moral implications of our admission requirements: admission without a
reasonable chance of success? The cost of support to make ‘success’ happen?
• Educational triage’s potential to exclude students from access/support based
on criteria that disregard context, structural inequalities and inter-
generational debt
• The need for transparency re rationales for inclusion/exclusion & decisions
made
• The scope of students’ agency: can students refuse advice/support provided
they understand the consequences of their opting out?

Thank you
Prof Paul Prinsloo
Research Professor in Open Distance
Learning (ODL)
College of Economic and Management
Sciences, Office number 3-15, Club 1,
Hazelwood, P O Box 392
Unisa, 0003, Republic of South Africa
T: +27 (0) 12 433 4719 (office)
T: +27 (0) 82 3954 113 (mobile)
prinsp@unisa.ac.za
Personal blog:
http://opendistanceteachingandlearning
.wordpress.com
Twitter profile: @14prinsp
Dr Sharon Slade
Senior Lecturer
Faculty of Business and Law
The Open University, Walton Hall,
Milton Keynes, MK7 6AA, United
Kingdom
T: +44 (0) 1865 486250
sharon.slade@open.ac.uk
www.linkedin.com/profile/view?id=53
123496&trk=tab_pro
Twitter profile: @sharonslade

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(cont.)
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(cont.)
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