The machine will argue they can use learning analytics to provide timely and effective interventions to students improving their chances of achieving better qualifications. Machines don’t forget or get sick; learning analytics is more accurate and not prejudiced; evidence for automated interventions. The human will argue although machines can make predictions they will never be 100% accurate; only a person can factor personal circumstances; automated interventions could be demotivating; automated interventions are not ethical.

1. Humans vs Machines: Learning analytics interventions
should always be mediated by a human being
For machines: Richard Palmer,Tribal
For humans: Sheila MacNeill, Glasgow Caledonian University

2. > >Slide
Debate
We believe that
>Learning analytics interventions should always be mediated
by a human being
Disclaimer:The opinions expressed by the presenters are not the view of their organisation
15/03/2017 Humans vs Machines2

3. > >Slide
The machine
The machine will argue they can use learning analytics to provide timely and effective
interventions to students improving their chances of achieving better qualifications.
Machines don’t forget or get sick; learning analytics is more accurate and not prejudiced;
evidence for automated interventions
Richard Palmer
15/03/2017 Humans vs Machines3

4. > >Slide
Learning analytics interventions should always
be mediated by a human being
>What does an intervention look like?
>Why automate?
>The problems with people
>Is intervention too hard for machines?
15/03/2017 Humans vs Machines4

5. > >Slide
What does an intervention look like?
>Does not have to be traditional meeting/conversation
>Based on data about what interventions work in similar situations
>Email, SMS or other electronic communication methods
>Suggest areas of focus or additional resources
15/03/2017 Humans vs Machines5

6. > >Slide
Why automate?
> Delivering lectures, seminars and tutorials
> Developing and implementing new methods of
teaching to reflect changes in research
> Designing, preparing and developing
teaching materials
> Assessing students' coursework
> Setting and marking examinations
> Supporting students through a pastoral or
advisory role
> Undertaking personal research projects and actively
contributing to the institution's research profile
> Writing up research and preparing it for publication
> Supervising students' research activities
Time and resources
> Completing continuous professional development
(CPD) and participating in staff training activities
> Carrying out administrative tasks related to the
department, such as student admissions, induction
programmes and involvement in committees
and boards
> Managing and supervising staff - at a senior level this
may include the role of head of department
> Representing the institution at professional
conferences and seminars, and contributing to
these as necessary
> Establishing collaborative links outside the university
with industrial, commercial and public organisations
15/03/2017 Humans vs Machines6

7. > >Slide
Why automate?
>Leaning Analytics knows when high risk times occur
>Can monitor the behavior of students in real time
>Can offer advice and guidance at the time when it is most needed
Timeliness
15/03/2017 Humans vs Machines7

8. > >Slide
The problems with people
>People get stressed or busy
>People get ill or other jobs
>People have bias, both conscious and unconscious
15/03/2017 Humans vs Machines8

9. > >Slide
Bias
Who believes that they have no bias between black people
and white people?
15/03/2017 Humans vs Machines9

10. > >Slide
Bias
Who believes that they have no bias between thin people
and fat people?
15/03/2017 Humans vs Machines10

11. > >Slide
Bias
15/03/2017 Humans vs Machines11

12. > >Slide
Is intervention too hard for machines?
>Pharmacist
>Driver
>Poker champion
>Comet lander
>Cancer diagnosis
15/03/2017 Humans vs Machines12

13. > >Slide
Is intervention too hard for machines?
>Pharmacist -> University California, San Francisco
>Driver -> Google self driving cards
>Poker champion -> Libratus
>Comet lander -> Rosetta and Philae
>Cancer diagnosis -> IBMWatson
>Judging personality -> O.C.E.A.N analysis
15/03/2017 Humans vs Machines13

14. > >Slide
jisc.ac.uk
Except where otherwise noted, this work
is licensed under CC-BY-NC-ND
> >
Richard Palmer
richard.palmer@tribalgroup.com
Learning analytics interventions
should always be mediated by a
human being
15/03/2017 Humans vs Machines14Slide

15. > >Slide
The Human
The human will argue although machines can make predictions they will
never be 100% accurate; only a person can factor personal circumstances;
automated interventions could be demotivating; automated interventions
are not ethical.
Sheila MacNeill
15/03/2017 Humans vs Machines15

16. > >Slide
It is the supreme art of the
teacher to awaken joy in creative
expression and knowledge
Albert Einstein
15/03/2017 Humans vs Machines16

17. > >Slide
Every student can learn,
just not on the same day
or in the same way
George Evans
15/03/2017 Humans vs Machines17

18. > >Slide 15/03/2017 Humans vs Machines18

19. > >Slide
Questions
15/03/2017 Humans vs Machines19

20. > >Slide
The vote
We believe that
>Learning analytics interventions should always be mediated
by a human being
For (the humans) or
Against (i.e. machines are better)
15/03/2017 Humans vs Machines20

21. > >Slide
Paul Bailey
Senior Co-design manager
Paul.bailey@jisc.ac.uk
15/03/2017 Humans vs Machines21 > >Slide