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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 us
With 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? Disability
                                                Learning style
      Background              Family income
            Funding       Learning              Posting to forums -
Gender      issues                              frequency
                          behaviours
 Assignment/test                                 Distance from
 scores                  Posting to forums -
                         content                 campus
         Study goals                                 Language
Age                      Log in frequency
        Working status                         Websites visited
Hitting study            Ethnicity
milestones                              Frequency of contact
                Study history           with tutor
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 less
                                  ------
support?

Do teachers, learners, and administrators have
the same authority/rights to determine what
support is provided?
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 al suggest:      1




    Consent                                  Transparency
    Data privacy                             Robustness/reliability
    Data stewardship                         Involvement of faculty
    Information sharing                      Avoidance of bias
    (internal)                               Sensitivity about certain
    Obligation to act                        profiles/types
    Distribution of resources

1
    Campbell, J.P., DeBlois, P.B. and Oblinger, D.B. (2007) EDUCAUSE Review, 42(4), 40–57
Interested in further discussion?

 sharon.slade@open.ac.uk
 fenella.galpin@open.ac.uk


 lak12-ethics@googlegroups.com

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ethical issues in learning analytics

  • 1. Learning Analytics and Higher Education: Ethical Perspectives Sharon Slade and Fenella Galpin
  • 2. 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!
  • 3. Our students leave information about themselves every time they interact with us With no realization or understanding of what we do with that information So, how do we use that data – and does it matter?
  • 4. 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.
  • 5. What do we mean by data about learners? Disability Learning style Background Family income Funding Learning Posting to forums - Gender issues frequency behaviours Assignment/test Distance from scores Posting to forums - content campus Study goals Language Age Log in frequency Working status Websites visited Hitting study Ethnicity milestones Frequency of contact Study history with tutor
  • 6. 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….
  • 7. Privacy Do students appreciate that information is being gathered about them? Are we explicit about what we might do with that information?
  • 8. Transparency and robustness Who can see the data collected? Who can see/influence the models? How reliable and robust are the models?
  • 9. Power Who gets to decide what happens next? Who can choose which students get more less ------ support? Do teachers, learners, and administrators have the same authority/rights to determine what support is provided?
  • 10. 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?
  • 11. 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)
  • 12. 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
  • 13. 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?
  • 14. 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.
  • 15. Towards a code of conduct Taking forward what has been discussed so far…. how might we start to capture what really matters?
  • 16. 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.
  • 17. What are the main areas to consider? Campbell et al suggest: 1 Consent Transparency Data privacy Robustness/reliability Data stewardship Involvement of faculty Information sharing Avoidance of bias (internal) Sensitivity about certain Obligation to act profiles/types Distribution of resources 1 Campbell, J.P., DeBlois, P.B. and Oblinger, D.B. (2007) EDUCAUSE Review, 42(4), 40–57
  • 18. Interested in further discussion? sharon.slade@open.ac.uk fenella.galpin@open.ac.uk lak12-ethics@googlegroups.com