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Learning Analytics and Higher Education: Ethical Perspectives Sharon Slade and Fenella Galpin
| Date post: | 25-Dec-2014 |
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Learning Analytics and Higher
Education: Ethical Perspectives
Sharon Slade and Fenella Galpin
Overview of session
Introduction (15 mins)
The student perspective (45 mins)
Stakeholder discussions - to explore ethics in relation to learning analytics, from the point of view of different stakeholders in the process (45 mins)
Plenary - issues arising from earlier discussions, possible conflicts between stakeholders (30 mins)
Towards a code of conduct (30 mins)
Wrap up - taking it forward (15 mins)
Lunch!
Our students leave information about themselves every time they interact with usWith no realization or understanding of what we do with that information
So, how do we use that data – and does it matter?
Learning analytics is the measurement, collection, analysis and reporting of data about learners to increase our understanding of them and their learning needs, and to use that understanding to influence their learning.
What do we mean by data about learners?
Background
Disability
Gender
Ethnicity
Learning behaviours
Study history
Learning style
Funding issues
Assignment/test scores
Websites visited
Hitting study milestones
Study goals
Age
Distance from campus
Working status
Family income
LanguageLog in frequency
Posting to forums - frequency
Frequency of contact with tutor
Posting to forums - content
What might we be concerned about?
Most papers have focused on privacy issues, but is there more to it than that?
Here are just some aspects that we might want to think about and explore….
Privacy
Do students appreciate that information is being
gathered about them?
Are we explicit about what we might do with that
information?
Transparency and robustness
Who can see the data collected?
Who can see/influence the models?
How reliable and robust are the models?
Power
Who gets to decide what happens next?
Who can choose which students get more support?
Do teachers, learners, and administrators have the same authority/rights to determine what support is provided?
------ less
Ownership issues
Who can mine our data for other purposes?
Can students opt out of having their information used?
… and what are the consequences of that?
How long is data kept for?
Responsibilities
Is there a shared responsibility to ensure
that information is accurate? Can students
opt to disguise themselves online?
Do we have a responsibility to ensure
equitable treatment of students based on
what we know? (or despite what we know)
Snakes and ladders
Work on a table in groups of 4 or 5
Say a quick hello to others there and share the instructions on the table
You have 30 minutes to complete as much of the game as you can
The student perspective
How does it feel to be a student?
Did you feel advantaged or disadvantaged?
Did it feel fair/unfair?
How did having a label feel?
Exploring from different perspectives…
Join in one of the groups – based on your card
colour, and discuss with other participants the
questions noted there.
You have 45 minutes to discuss and note on flip
charts your thoughts before we share as a whole
group.
Towards a code of conduct
Taking forward what has been discussed so far…. how might we start to capture what really matters?
The OU’s Data Protection Policy (health warning – summary only…)
We use personal information to: • Process applications
• Carry out research (internally or using external agency)
• Produce statistics for publication
• Provide student information to other organisations, in line with legal and government requirements
• Some information may be used by the University to identify students who require additional support or specific service. We consider disclosure of this information as explicit consent to use this information for this purpose.
• Your contact details may be passed to survey contractors… used only for survey purposes and data will then be deleted.
What are the main areas to consider?
Campbell et al1
suggest:ConsentData privacyData stewardshipInformation sharing (internal)Obligation to actDistribution of resources
TransparencyRobustness/reliabilityInvolvement of facultyAvoidance of biasSensitivity about certain profiles/types
1 Campbell, J.P., DeBlois, P.B. and Oblinger, D.B. (2007) EDUCAUSE Review, 42(4), 40–57
Interested in further discussion?
