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Case Study: Using Learning Analytics to Improve
the Student Learning Experience
Ed Foster, Student Engagement Manager, NTU
Effectively Utilising Higher Education Data, 26th November 2015
How does NTU use data to improve the
student learning experience?
• Going to talk from the perspective of the NTU Student Dashboard
– Learning analytics resource
• Context
– Building on solid foundations
• Quality management process
• Strategy of moving towards institutional data warehouse with management reporting
• Extensive use of surveys including effective dry runs for the NSS
• Dashboard development came from 3 drivers
– What Works? Student Retention & Success
– Internal audit
– Information Systems strategy of engaging suppliers in a dialogue about
developing Learning Analytics
Learning Analytics
• Use of institutional data sets to develop an understanding about
outcomes for individual students or groups
• Potentially, learning analytics can alert staff and students to the
risks of a student dropping out early, or under-performing
• For me, analyics must be action oriented
• Learning analytics is only as useful as the action it instigates
• Other uses
– Making MOOCs more appealing
– Curriculum design
– Testing the efficacy of learning and teaching strategies/ interventions
– Fascinating insight into computing departments
What did we set out to achieve?
Goal Individual learner
• Improve
retention
Early warning alerts to tutors
Enable students to benchmark own engagement
• Improve sense of
belonging/
engagement
Notes facility to agree action plans, record
meetings
Tool for interaction between tutor & student
• Improve
attainment
Benchmark engagement & see positive
behaviours
Students can see own grades and feedback
• Data for analysis by cohort
• Improving University systems
• Character references & other potential data sharing
How does the dashboard work?
NTU
Student
Dashboard
Student biographical
info, e.g. enrolment
status
(not used for analysis)
Evidence of student
engagement
• Door swipes
(where appropriate)
• Library books
• VLE use
• Dropbox
submissions
•2015-16
• Attendance
• Electronic
resources
Staff
view
Student
view
Compares student
engagement across
the cohort & gives
rating
Can make
comments
in free text
box
Raises
alerts!!
Purchased Student Dashboard from Solutionpath.co.uk
Staff log in
Cumulative view of student engagement
Week by Week Engagement
Engagement for
past 5 days
Explanation of
engagement
ratings
Advice about
what to do to
improve
engagement
Does it work?
• Yes
• 24% of students with low average engagement progressed from the
first year to the second
• 92% of those with high average engagement
• Average engagement by far outweighs any demographic or entry
qualification disadvantage
• 42% of final year students with low average engagement achieved a
2:1 or first
• 81% of students with a high average engagement
All data from 2013-14 data set
Evidence of changes in student engagement & institutional
working practices
Dashboard Impact: Students
• 27% of students reported that they had changed their behaviour in response to the
data provided by the Dashboard
“Become more engaged
with the NOW so it shows
high engagement rating,
and so I'm higher than
the class average.”
“Attending more
lectures and seminars to
increase my performance
chart from satisfactory to
high. ”
“Accessed more material
on NOW and using library
more frequently”
“Increased my attendance
and told someone if I will be
late or not attending. Also
more use of the library.”
Also seen competition between peers & Dashboard appearing in student culture
Dashboard impact: Tutors
• Started to see changes to tutor behaviours
• In the pilot survey 80% felt that the data provided by the
Dashboard changed how they worked with students
[The Dashboard] “enabled me
to view a better profile of
the student and target
interaction accordingly”
“As I knew which students
were not engaging with their
course, I could contact them.
It was useful to have an
email prompt about what to
do and information about how
to contact the students.”
"It gives me a quick picture
of my tutorial group, which
will help support them, and
track their progress."
Yes about 1-2
times
Yes about
monthly
Yes about weekly
Yes whenever
I’ve had an alert
email
very useful 2 1 11 4
quite useful 7 26 27 8
undecided 13 11 1 4
Not very useful 7 9 2 2
Not at all useful 1 2 2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%AxisTitle
Relationship between Dashboard use and
staff perceptions of usefulness (n=140)
Survey conducted summer 2015
Where next?
Learning analytics is only as useful as the
actions it instigates
For the academic to
jump into the bath
tub, they need
time, training,
motivation, to
have easy access
to data, a room to
talk to the student
or space to email
them.
Just knowing that
they need to jump
is only the first link
in the chain
The sector already has enough data to act,
but appears not to have done so
ECU
report
from
2010 –
evidence of
attainment gap
comfortably 10 years
old – 3 complete
generations of
University students
Exploiting the data provided by learning
analytics
• We are confident that the Dashboard delivers accurate
timely data to staff and students
• We can confidently say that it changes student behaviours,
but requires much further research to understand scale and
depth of change
• We are working on the point where we have identified a
problem
– What interventions work?
– & for which students?
• NTU is leading an Erasmus+ project to investigate effective
interventions (we are recruiting)
– KU Leuven and U Leiden
• If you’re interested in finding out more, we are running a
free symposium on Thursday 10th December
– Learning Metrics, Learning Analytics at Nottingham Trent University

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ABLE - Inside Government E Foster 26th November 2015

  • 1. Case Study: Using Learning Analytics to Improve the Student Learning Experience Ed Foster, Student Engagement Manager, NTU Effectively Utilising Higher Education Data, 26th November 2015
  • 2. How does NTU use data to improve the student learning experience? • Going to talk from the perspective of the NTU Student Dashboard – Learning analytics resource • Context – Building on solid foundations • Quality management process • Strategy of moving towards institutional data warehouse with management reporting • Extensive use of surveys including effective dry runs for the NSS • Dashboard development came from 3 drivers – What Works? Student Retention & Success – Internal audit – Information Systems strategy of engaging suppliers in a dialogue about developing Learning Analytics
  • 3. Learning Analytics • Use of institutional data sets to develop an understanding about outcomes for individual students or groups • Potentially, learning analytics can alert staff and students to the risks of a student dropping out early, or under-performing • For me, analyics must be action oriented • Learning analytics is only as useful as the action it instigates • Other uses – Making MOOCs more appealing – Curriculum design – Testing the efficacy of learning and teaching strategies/ interventions – Fascinating insight into computing departments
  • 4. What did we set out to achieve? Goal Individual learner • Improve retention Early warning alerts to tutors Enable students to benchmark own engagement • Improve sense of belonging/ engagement Notes facility to agree action plans, record meetings Tool for interaction between tutor & student • Improve attainment Benchmark engagement & see positive behaviours Students can see own grades and feedback • Data for analysis by cohort • Improving University systems • Character references & other potential data sharing
  • 5. How does the dashboard work? NTU Student Dashboard Student biographical info, e.g. enrolment status (not used for analysis) Evidence of student engagement • Door swipes (where appropriate) • Library books • VLE use • Dropbox submissions •2015-16 • Attendance • Electronic resources Staff view Student view Compares student engagement across the cohort & gives rating Can make comments in free text box Raises alerts!! Purchased Student Dashboard from Solutionpath.co.uk
  • 7. Cumulative view of student engagement
  • 8. Week by Week Engagement
  • 9.
  • 10. Engagement for past 5 days Explanation of engagement ratings Advice about what to do to improve engagement
  • 11.
  • 12. Does it work? • Yes • 24% of students with low average engagement progressed from the first year to the second • 92% of those with high average engagement • Average engagement by far outweighs any demographic or entry qualification disadvantage • 42% of final year students with low average engagement achieved a 2:1 or first • 81% of students with a high average engagement All data from 2013-14 data set
  • 13. Evidence of changes in student engagement & institutional working practices
  • 14. Dashboard Impact: Students • 27% of students reported that they had changed their behaviour in response to the data provided by the Dashboard “Become more engaged with the NOW so it shows high engagement rating, and so I'm higher than the class average.” “Attending more lectures and seminars to increase my performance chart from satisfactory to high. ” “Accessed more material on NOW and using library more frequently” “Increased my attendance and told someone if I will be late or not attending. Also more use of the library.” Also seen competition between peers & Dashboard appearing in student culture
  • 15. Dashboard impact: Tutors • Started to see changes to tutor behaviours • In the pilot survey 80% felt that the data provided by the Dashboard changed how they worked with students [The Dashboard] “enabled me to view a better profile of the student and target interaction accordingly” “As I knew which students were not engaging with their course, I could contact them. It was useful to have an email prompt about what to do and information about how to contact the students.” "It gives me a quick picture of my tutorial group, which will help support them, and track their progress."
  • 16. Yes about 1-2 times Yes about monthly Yes about weekly Yes whenever I’ve had an alert email very useful 2 1 11 4 quite useful 7 26 27 8 undecided 13 11 1 4 Not very useful 7 9 2 2 Not at all useful 1 2 2 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%AxisTitle Relationship between Dashboard use and staff perceptions of usefulness (n=140) Survey conducted summer 2015
  • 18. Learning analytics is only as useful as the actions it instigates For the academic to jump into the bath tub, they need time, training, motivation, to have easy access to data, a room to talk to the student or space to email them. Just knowing that they need to jump is only the first link in the chain
  • 19. The sector already has enough data to act, but appears not to have done so ECU report from 2010 – evidence of attainment gap comfortably 10 years old – 3 complete generations of University students
  • 20. Exploiting the data provided by learning analytics • We are confident that the Dashboard delivers accurate timely data to staff and students • We can confidently say that it changes student behaviours, but requires much further research to understand scale and depth of change • We are working on the point where we have identified a problem – What interventions work? – & for which students? • NTU is leading an Erasmus+ project to investigate effective interventions (we are recruiting) – KU Leuven and U Leiden • If you’re interested in finding out more, we are running a free symposium on Thursday 10th December – Learning Metrics, Learning Analytics at Nottingham Trent University