The document summarizes a project to create a personalized learning portal called the Learning Commons that provides learners access to curated content from multiple providers. It tracks learners' progress on competencies using xAPI data. The project involved developing a shared data model to tag content and define competencies. This allowed the portal to surface relevant content, measure skill development, and provide insights for various stakeholders. The outcomes were intended to improve the learner experience through personalized pathways in content and help instructors and organizations make data-driven decisions.

1. Improving the Learner
Experience Through an
xAPI-Enabled Multi-Source
Content Portal
April 17, 2018 — http://goo.gl/HfuscA

2. Project Summary
Through partnerships with leading human capital
organizations, the Learning Accelerator aims to transform
K-12 education through blended learning on a national scale.
As part of their distributed adult-learning strategy, TLA has
partnered with Yet Analytics to create the Learning
Commons, an xAPI-enabled, multi-source content
exploration and experience tracking portal. As learners
utilize content through curated playlists, skill and
competency development is automatically tracked and
presented back to individual learners, cohort leaders and
content providers through xAPI data.
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3. The Problem for Learners:
Multiple Pathways to Content
What if we could make the learner
experience personalized and
data-driven at the same time?
● Figure out what they need to
learn
● Find excellent content to
learn it
● Track and reflect on
progress
● Across boundaries of
platform, location, time

4. The Problem for Content Providers & Instructional
Designers: Insight into Learner Experience
Competency
Alignment
What resources are
being used? What
content is most
valuable?
Usage
Analytics
Informal
Learning
Can we curate
resources? Can we
measure informal
learning?
How do resources
relate to each
other and build
learner skills?
What if we could make the learner
experience personalized and
data-driven at the same time?
● Find resources across
content providers
● Find resources across
competencies and
frameworks
● Lead learners through
recommended progressions
● Understand usage, value,
and engagement

5. The Problem for Content Providers
& Instructional Designers
Competency
Alignment
What resources are
being used? What
content is most
valuable?
Usage
Analytics
Informal
Learning
Can we curate
resources? Can we
measure informal
learning?
How do resources
relate to each
other and build
learner skills?
What if we could make the learner
experience personalized and
data-driven at the same time?
● Find resources across
content providers
● Find resources across
competencies and
frameworks
● Lead learners through
recommended progressions
● Understand usage, value,
and engagement
Lesson Learned:
Get your
stakeholders all
involved early!

6. The goal was to create a system
where there is interoperable
content aligned to interoperable
competencies made possible by
interoperable data.

7. Project Phases
Phase One: Data Model
● Develop a common language and data structure for competency
● Design a shared data structure to tag content across platforms and sources
Phase Two: Learner Portal
● Create a multi-source learning experience interface
● Collect and connect informal learning data as it happens

8. Phase One: Shared Data Model for Content
Task 1: Define Content
Relationships
● Identified how
resources relate to
each other
● Identified how
resources from different
content sources are
related to the learner’s
journey
Content from
these
organizations are
all on different
platforms, LMSs,
CMSs, and
websites.

9. Phase One: Shared Data Model for Competency
Task 2: Define Competencies
● Built off of the iNACOL Blended Learning Educator Competency Framework
(bit.ly/blendedcompetencies)
● Translated bigger competency standards into granular, actionable elements (things we could do,
see, measure, demonstrate with xAPI data)

10. Phase One: Shared Data Model for Competency
Task 3: Create Shared Tagging
Model
● Identified set of skill areas
(competencies) and
granular, measurable
learning tags
● Linked the content to
competencies
● All content aligned to xAPI
data model for usage
tracking and skill
development
Skills/Competencies
Learning Tags

11. Phase One: Shared Data Model for Competency
Task 3: Create Shared Tagging
Model
● Identified set of skill areas
(competencies) and
granular, measurable
learning tags
● Linked the content to
competencies
● All content aligned to xAPI
data model for usage
tracking and skill
development
Skills/Competencies
Learning Tags
Lesson Learned:
Don’t create
another
framework, make
an interoperable
system that can
grow.

12. Phase One: Shared Data Model for Competency
Skills/CompetenciesLearning Tags

13. Now fast forward 11 months while
we built out an xAPI-enabled
interface between the content, the
content providers, the
organizations, and the learners.

14. Phase Two: The Learning Commons
March 13, 2018

15. Phase Two: The Learning Commons
● Provides multiple pathways into
content for learners and improves
content searchability
● Content curation is streamlined
through playlist creation and
community validation
● Progress data from informal learning
is automatically collected and stored
in a learner’s profile
● Enables a unified learner experience

16. Unified Search Portal for Learners Content Accessibility by Search

17. Content Browse by ProviderContent Browse by Tags and Skills

18. Sharable for External ConnectionsCreation of Curated Playlists

19. Network Learning for Groups Recommendation by Relevance

20. Registration of Content to Data Model Competency Mapping by Data Model

21. Registration of Content to Data Model Competency Mapping by Data Model
Lesson Learned:
Design reference
systems and data
models with
change in mind!

22. Personalization for Learners Learner Profile with Competency

23. Personalization for Learners Learner Profile with Competency
Real-time
competency
development
measurement for
learners and
leaders, made
possible by xAPI.

24. Phase Two: Granular xAPI-Driven Insights
● Content usage patterns and
relevance of content to different
users and groups
● Specific interaction data with content
objects and media
Data views from the Yet xAPI LRS have been generalized for this presentation.

25. ● Provides multiple pathways into
content for learners and improves
content searchability
● Content curation is streamlined
through playlist creation and
community validation
● Progress data from informal learning is
automatically collected and stored in a
learner’s profile
● Enables a unified learner experience
Outcomes for Learning Commons

26. ● Provides multiple pathways into
content for learners and improves
content searchability
● Content curation is streamlined
through playlist creation and
community validation
● Progress data from informal learning is
automatically collected and stored in a
learner’s profile
● Enables a unified learner experience
Outcomes for Learning Commons
Lesson Learned:
Build-in an
adoption and
roll-out plan for
any new
initiative!

27. Rather than start with this as a data
problem, we used xAPI from the
very beginning of design to solve
our learner experience problem.

28. Project Outcomes
With more time and more data we expect:
● Content providers to be able to make decisions about content creation and
resource investment.
● Network leaders and districts to be able to make decisions about professional
development opportunities and support for teachers.
● Educators to be able to make data-driven decisions about their own learning in
ways that have positive impact for schools and students.
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29. Thank You!
See the Learning Commons for yourself! Visit https://www.learning-commons.org.
See the case study and video on the Yet Blog.
Send questions or give feedback to me at margaret@yetanalytics.com.
Learn more about our work at Yet at https://www.yetanalytics.com.
Learn more about the Learning Accelerator at https://learningaccelerator.org/.
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