Summary of work undertaken at Manchester Metropolitan University to enhance the student experience, beginning with a rewrite of the first year undergraduate curriculum and including the delivery of personalised systems that wrap institutional resources around the learner
Ecological Succession. ( ECOSYSTEM, B. Pharmacy, 1st Year, Sem-II, Environmen...
LRT Talks 20140610 EFYE2014 Nottingham
1. Enhancing the First Year Student
Experience at MMU:
Clearing a path & interpreting digital footprints
Professor Mark Stubbs
Head of Learning & Research Technologies
http://twitter.com/thestubbs
http://slideshare.net/markstubbs
Nottingham | Jun 2014
#EFYE2014
2. Context | An interesting place to work!
• Large, popular, multi-campus university
– 36,000+ students | 1,000+ courses | consolidating from 7 sites
• Pursuing an ambitious transformation initiative
– New Buildings, New Curriculum, New Admin Processes & Systems,
New Learning & Mobile Tech, New Quality Processes…
3. Context | Strategic improvement imperative
Student Retention
Success &
Satisfaction
Student Intake
(Aspirations, Attitude
& Abilities)
Learning, Teaching, Assessment
& Personal Development
Processes, Facilities
& Resources
Reputation
Marketing &
Recruitment
Processes
All Year Numbers
Resource allocation
League table rankingsA
A Recruit to target
B
B Improve satisfaction, retention & success
C
C Inform decision-makers
4. CSI | Student Experience
Careful diagnosis of (diverse) learning experiences
• Recurrent messages
– NSS analysis: course organisation determines Q22
– Mobile surveys: deadlines, timetables… (m-admin)
– Focus groups: consistent, easy to find info
• Great (and not-so great) expectations
– “engaging, well-organised courses”
– “inspirational tutors who know me”
6. Coordinating our response
B
Improve satisfaction, retention & success
Great
Online Experience
(Seamless, personalised)
Great
Learning Spaces
Great
Teaching
Simplify
Unwieldy
Curriculum
£350M
7. • A coordinated strike for step-change improvement
EQAL
New Curriculum
• designing new units, …
New Admin Systems & Processes
• personal timetabling, …
New Virtual Learning Environment
• Moodle & myMMU web/mobile, Talis Aspire…
New QA & QE Processes
• facilitating curriculum transformation
In the current climate
Diminishing unit of resource
Everything depends on everything else
We are large and risk averse
12. 1
Wrapping the institution around the learner
Student ID
Timetable
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Sync to
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device
14. Wrapping the institution around the learner
Student ID (+ Unit code)
Deadlines / extensions /
feedback return dates / provisional marks
Personalised submission sheet
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15. Wrapping the institution around the learner
Unit code
Resource list
Relevant resource
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16. Wrapping the institution around the learner
Unit code
Past exam papers
Past exam paper
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20. … we can now begin to
interpret some digital
footprints
21. Using the data
2. Identify
relevant data
sources
3.Summarise
individual
data sources
4 Join on
common
identifiers
5 Prep the
data for
analysis
6.Analyse &
visualise
1.Appreciate
the issue
Refining
understanding of a
problem space
22. Understanding student satisfaction
2. Identify
relevant data
sources
3.Summarise
individual
data sources
4 Join on
common
identifiers
5 Prep the
data for
analysis
6.Analyse &
visualise
1.Appreciate
the issue
Refining
understanding of
student satisfaction
Student
demographics
Entry profiles
Internal survey
responses
Join on
student ID
Random
Forests
analysis
Satisfaction
predictors
↗ Confidence
↘ Organisation
→Teaching
Sum entry
points &
qual type
Handle missing
values, collapse
categories…
23. Understanding student success
2. Identify
relevant data
sources
3.Summarise
individual
data sources
4 Join on
common
identifiers
5 Prep the
data for
analysis
6.Analyse &
visualise
1.Appreciate
the issue
Refining
understanding of
student continuation
HESA PI
League Tables
Join on
UK PRN
Random
Forests
Regression
Tree
Predictors
YNG NSSEC4-7
Entry Tariff
NSS
Add
UKPRN
Handle missing
values, collapse
categories…
25. Limitations
1. Confirmation bias
2. Meaningful comparison
3. Quantitative V Qualitative
4. Data quality
5. Correlation ≠ causation
Reality of our current data
warehouse build: careful
thought about error handling +
painstaking checking of joins!
26. Continuous monitoring & improvement
MDL SRS TT
Data Warehouse Analysis
Cubes
Undergraduate Dental TechnologyNetwork (11209A)
Overview Students Success Satisfaction Engagement Standards Applications Employment
Head count [now] of [all]studentsfor [all modes][all enrolments]
Enrolled
268 (95%)
Withdrawn
0 (0%)
Suspended
0 (0%)
Repeat w/o attend
14 (5%)
#STUDENTS TOTAL L3 L4 L5 YO L6 L7
Undergraduate Dental Technology
Network (11029A)
268 83 73 67 45
- BSc(Hons)Dental Technology (6266) 184 73 67 44
+ BSc(Hons) Dental Technology (6266_1F) 73 73
+ BSc(Hons) Dental Technology (6266_2F) 67 67
+ BSc(Hons) Dental Technology (6266_3F) 44 44
+ BSc(Hons)Dental Technology (6267) 1 1
+ FDSc Dental Technology (621C) 62 62
+ FDSc Dental Technology (6264) 21 21
How has my studentcohort changed?
Higher than
faculty average
Lower than
last year
5%-5%
5%
-5%
PLP
Parents in HE
Mature
Live at home
Higher than
last year
Lower than
faculty average
Live at home 12%
PLP 4%
Mature 6%
Disability 3%
BME 8%
Male 42%
International 4%
In response to this information,I intend [to highlightthe followinggood practice]
Previously,the Programme Leader committed to…
On 21/03/13 Done?
On 22/02/13 raisewith the Dean targets for the part-time courses Complete
CMI: Undergraduate Dental TechnologyNetwork(11209A)
Overview Students Success Satisfaction Engagement Standards Applications Employme
Satisfaction [onall ISS] of [all]studentsfor [all modes][all enrolments]
Course Satisfaction
0% 100%50%25% 75%
69%
#Enrolled
Response
Explanation
Feedback
Advice
Organisation
Resources
Confidence
Overall
Undergraduate Dental Technology Network (11029A) 268 30% 100% 93% 93% 87% 96% 95% 100%
- BSc(Hons)Dental Technology (6266) 184 30% 100% 93% 93% 87% 96% 95% 100%
- 6266_1F 73 27% 100% 95% 95% 95% 95% 100% 100%
- 6266_2F 67 31% 100% 100% 95% 81% 100% 95% 100%
- 6266_3F 44 32% 100% 79% 86% 86% 93% 86% 100%
60.0%
65.0%
70.0%
75.0%
80.0%
85.0%
90.0%
95.0%
100.0%
2011
2012
2013
2011
2012
2013
2011
2012
2013
2011
2012
2013
2011
2012
2013
2011
2012
2013
2011
2012
2013
EXPLANATION
FEEDBACK
ADVICE
ORGANISATION
RESOURCES
CONFIDENCE
OVERALL
C
27. Change management lessons
1. Understand important dynamics
2. Be clear what needs to be done
3. Set high-level goals
4. Understand where change is required
5. Be bold and plan holistically
6. Ensure you’ve got the right team to drive
7. Make ‘big asks’ as small as possible
8. Make it stick with reinforcing change
http://tinyurl.com/jiscmmusrcCurriculum Design
Assessment & Feedback http://tinyurl.com/jiscmmutraffic