This document discusses Apereo Foundation's Learning Analytics Initiative. It provides context on the use of analytics in higher education. It outlines Apereo's vision for an open learning analytics platform that would allow institutions to collect, store, analyze and act on learning data. The platform would integrate with systems like Sakai, Apereo OAE and others. It discusses current progress including an analytics processor and dashboard. It also outlines seven strategic issues and a future of moving platform elements to incubation and encouraging adoption and resource commitment. The overall goal is to facilitate collaboration and sharing of analytics among institutions.

1. Apereo Foundation | Learning Analytics
Ian Dolphin, Apereo Foundation | Ja-Sakai Conference | March 2015 | Tokyo

2. Agenda
Why open source for higher education?
What is Apereo?
Apereo Learning Analytics Initiative

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Why open source software for
higher education?

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Utility: Software that meets a need

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Utility: Software that meets a need
Innovation

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Utility
Innovation
85%
15%

7. Utility
Innovation
Photo by blprnt_van - Creative Commons Attribution License http://www.flickr.com/photos/55772089@N00 Created with Haiku Deck
Utility
Innovation
Customization

8. Utility
Innovation
Photo by blprnt_van - Creative Commons Attribution License http://www.flickr.com/photos/55772089@N00 Created with Haiku Deck
Utility
Innovation
Customization
Contribution

9. Utility
Innovation
Photo by blprnt_van - Creative Commons Attribution License http://www.flickr.com/photos/55772089@N00 Created with Haiku Deck
Utility
Innovation
Customization
Sustainability
Contribution

10. Contribution is critical
… and not just code …

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What is the
Apereo Foundation?

12. Apereo is …
• A not-for-profit registered in New Jersey
• A membership organisation
• A network of institutions & communities

13. Mission
The core mission of the Apereo
Foundation is to assist and facilitate
educational organizations which
“collaborate to foster, develop, and
sustain open technologies and
innovation to support learning, teaching,
and research."

14. Foundation Provides …
• A deliberately minimal set of services
• Manage licensing and intellectual property
• Accounting
• Events
• Programmes;
• Fellows, Teaching with Sakai Innovation Award
• Infrastructure (technical + community)
• Routes to pooled expertise and guidance

15. Subsidiarity Principle
“Apereo does not attempt to
provide what projects or
institutions can better
provide themselves”

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Communities …
• Software Communities
• Communities of Interest

17. • Karuta
• EDExchange
• CAS
• Bedework
• Open Academic Environment
• Sakai
• Student Success Plan
• uPortal
• uMobile
• Opencast
• UniTime
• Xerte
Incubating… Sponsored …
Software Communities …

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Communities of Interest
• Thematic -
• “Teaching and Learning”
• “ePortfolio”
• “Learning Analytics Initiative”
• Explore work/ideas around common theme
• One of the nurseries for our incubation process

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Incubation
• Software: from innovation to sustainability
• Structured process
• Guided by community mentors
• Results in exit by graduation … or not
… not graduating is not a failure

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Networks & Partnerships
Apereo will not realise its mission alone …
… or by simple linear growth
Regional partnerships: ESUP-Portail (Fr)
Thematic partnerships: InCommon, SoLAR

21. Apereo Foundation
Learning Analytics Initiative

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23. Context & Landscape
• Higher education: post war transformation
• Did practice keep pace with change?
• Increased student numbers + diversity
= impact on retention?
• Technology-driven“answers”
• CBT, Courseware, eLearning, LMS/VLE, MOOCs …

24. Business Analytics
Business analytics (BA) refers to the skills, technologies,
practices for continuous iterative exploration and
investigation of past business performance to gain
insight and drive business planning.[1] Business
analytics focuses on developing new insights and
understanding of business performance based on data
and statistical methods.
https://en.wikipedia.org/wiki/Business_analytics

25. Learning Analytics?
Academic Analytics Learning Analytics
A process for providing higher
education institutions with the data
necessary to support operational and
financial decision making*
The use of analytic techniques to help
target instructional, curricular, and
support resources to support the
achievement of specific learning goals*
Focused on the business of the
institution
Focused on the student and their
learning behaviors
Management/executives are the
primary audience
Learners and instructors are the primary
audience
* - Analytics in Higher Education: Establishing a Common Language

26. Adaptive Learning &
Cognitive Tutoring
Data
Visualization
Academic Early
Alert Systems
Student Advising &
Recommendations

27. Reporting Data
• Summarize historical data
Analyzing Trends
• Identify historical trends and correlations
Predictive Analytics
• Predict future outcomes and behaviour
Institutional Journey

28. OAAI Project - Marist College
Student Aptitude Data
(SATs, current GPA, etc.)
Student Demographic Data
(Age, gender, etc.)
Sakai Event Log Data
Sakai Gradebook Data
Predictive
Model
Scoring
Identifies
students“at
risk”to not
complete
course
SISDataLMSData
OAAI Early Alert System Overview
Intervention Deployed
“Awareness”or Online
Academic Support
Environment (OASE)
Model Developed
Using Historical Data
Step #1: Developed model
using historical data Academic Alert
Report (AAR)

29. OAAI Impact
• Statistically significant positive impact on final grades
• Across student population (including low income)
• Models proved portable - reference group of institutions
• Staff feedback -
“I became more vigilant about reaching
out to individual students”
“I received the highest volume of
unsolicited positive feedback”

30. Sharing open models and
algorithms is critical to
institutional learning

31. Strategic Vision -
Open Learning Analytics Platform
Collection
based data capture from any
potential source using
Experience API and/or IMS
Caliper/Sensor API
Storage
for all learning-related data
using Learning Record Store
(LRS) standard.
Analysis
Analytics Processor (LAP) that
can handle data mining, data
processing (ETL), predictive
model scoring and reporting.
Communication
Dashboard technology for
displaying LAP output.
Action
fed into other systems to
trigger alerts, etc.
Learning Record
Storage
Summary and Results
Communication
Analysis Results
Action
Learning
Data
Analysis
Learning
Activities
Collection

32. Strategic Vision -
Open Learning Analytics Platform
Collection
based data capture from any
potential source using
Experience API and/or IMS
Caliper/Sensor API
Storage
for all learning-related data
using Learning Record Store
(LRS) standard.
Analysis
Analytics Processor (LAP) that
can handle data mining, data
processing (ETL), predictive
model scoring and reporting.
Communication
Dashboard technology for
displaying LAP output.
Action
fed into other systems to
trigger alerts, etc.
Learning Record
Storage
Summary and Results
Communication
Analysis Results
Action
Learning
Data
Analysis
Learning
Activities
Collection
Administrative
Systems
Learning
Delivery

33. Strategic Vision -
Open Learning Analytics Platform
Collection
based data capture from any
potential source using
Experience API and/or IMS
Caliper/Sensor API
Storage
for all learning-related data
using Learning Record Store
(LRS) standard.
Analysis
Analytics Processor (LAP) that
can handle data mining, data
processing (ETL), predictive
model scoring and reporting.
Communication
Dashboard technology for
displaying LAP output.
Action
fed into other systems to
trigger alerts, etc.
Learning Record
Storage
Summary and Results
Communication
Analysis Results
Action
Learning
Data
Analysis
Learning
Activities
Collection
Administrative
Systems
Learning
Delivery
LRS
LAPDashboards etc
SSP + Systemsn

34. Current state …
• Data Collection: xAPI integrated with Sakai, Apereo OAE, Larissa,
OpenLRS. IMS Calliper exploration when mature
• Learning Record Store (LRS): Two reference implementations -
OpenLRS (Unicon, USUHS) Larissa (UvA)
• Learning Analytics Processor (LAP): Reference implementation of
API (Unicon/Marist)
• Open Dashboard: Reference implementation (Unicon/USUHS).
IMS LTI compliant - embed in many systems
• Student Success Plan: Case Management - Graduated incubation,
growing number of adoptions

35. Seven Strategic Issues
(not the only seven ….)
1. Data: from where?
SIS? LMS/VLE? Library? eResources? Others?
2. Systems open enough to extract required data?
3. Institutional governance?
4. Committed institutional leadership?
5. Application centric vs Platform approach?
6. Ethics and Privacy:
cultural and legal concerns in globalized environment

36. Willingness and ability
to share?
7

37. Futures
• Move elements of platform into incubation
• Encourage use, experimentation, adoption
• Encourage resource commitment
• Encourage regional exchanges
• Networking: JISC Analytics, SoLAR. SURF, MINES ??
• Participate

39. More information on Apereo: ian.dolphin@apereo.org
On the Analytics Initiative: A.M.Berg@uva.nl