Learning Analytics bij de Rijksuniversiteit Groningen

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Dinsdag 8 november Sessieronde 3 Titel: Learning Analytics bij de Rijksuniversiteit Groningen Spreker(s): Hans Beldhuis (Rijksuniversiteit Groningen) Zaal: Penn II

Education

1|08-11-2016
1|
centrum voor
informatie technologie
ews
08-11-2016
Active Learning at UG
SURF Onderwijsdagen

3|08-11-2016
Educational vision UG
› 2010-2015 Key elements:
 inspire each other (academic knowledge)
 get best out of each other (ambitions)
 collaborate and contribute (academic community)
› Successful pilots with educational concepts:
 research-driven education
 communities of learners
 international classroom
 e-learning
› Results:
 improved student success (more students more ECTS more
diplomas less time)
 increased student satisfaction
 100% compliant to "prestatieafspraken"
 top 100 University
http://www.rug.nl/about-us/who-are-we/strategic-plan/strategic-goals/education

4|08-11-2016
2016-2020
› Innovative education to educate innovators
› Key elements:
 Active Learning
 Inclusion
› Meaning for students:
 Every student prepared for every class
 Students become involved, committed and
responsible for their own learners path
 University cares

7|08-11-2016
Early Warning Signals
+ signals
+ interventions
Early Warning Signals
1. Academic preparation
• prior education, student characteristics
2. Student performance
• student workload, attempts, grading
3. Student effort
• activity in learning environment

8|08-11-2016
Project
› The gem cannot be polished without friction,
nor man perfected without trials (ZWGG)
› Challenges & Goals to be addressed
› Who are the Stakeholders
› What data are you providing them with
› Stakeholder Actions – what do you expect
them to do with the data
› Unexpected Challenges
› Where next for the University of Groningen –
other uses of the data?

9|08-11-2016
Enable to become active
› stakeholders (3 out of 7)
 student: find out about performance and
behaviour compared with peers
 instructor: real-time insights into online
behaviour
 study advisor: identify at-risk students
earlier
› infrastructure (data warehouse)
 BB Learn + SIS
 Blackboard Analytics for Learn (A4L)

10|08-11-2016
› A Packaged Analytics Application
Transformation
Layer
Best Practices
Defined Metrics
Business Rules
Derived
Information
Data
Warehouse
OLAP
Star Schema
Pre-Built
Reports &
Dashboards
Pre-Built Data
Integration
Bb
Learn
Other
ERP
Blackboard Approach A4L

11|08-11-2016
Calculus
› freshmen (Math, Physics, Astronomy)
› ± 300 students (differ in GPA, prior education)
› block of 10 weeks
› start entrée test
› invisible students
› pass rate final test max. 75%

18|08-11-2016
Calculus als studieadviseur

21|08-11-2016
Preliminary results
› students
 support A4L (96%)
 become active in course
 some become alert on correct study choice
› instructor
 earlier & correct detection invisible students
 effective remedial teaching
 maybe better grade distribution
› study advisor
 earlier contact
 study advice (effective studying)

22|08-11-2016
Next semester
› strenghten
 educational innovation (course re-design)
 actions by 3 stakeholders
› datawarehouse and privacy
 increase data quality (ZWGG)
 perform Privacy Impact Assessment (PIA)
 draft a Code of Practice
› reports and dash boards
 analyze historical data
 customization

23|08-11-2016centrum voor
informatie technologie
ews
Hans Beldhuis, PhD
h.j.a.beldhuis@rug.nl

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