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Experience API (xAPI): Potential for Open Educational Resources – Part 1

This is the first one of a series of posts from an article written for Commonwealth of Learning / Commonwealth Educational Media Centre for Asia, the sub-topics are listed as here. It’s authored by Jessie Chuang (Classroom Aid), edited by Henry Chen (Classroom Aid) and reviewed by Jason Haag (ADL) and Dr. Ramesh Sharma. The targeted audience of this introductory writing is for policy makers, decision makers of learning/training programs, non-technical readers/educators. The article is openly-licensed with CC-BY-SA, if you’d like a copy in PDF file format, please email: contactus[at] .

  • Introduction of Experience API (xAPI)
  • Assessment for Learning
  • Distributed Nature of OER
  • Open Learning Analytics
  • Linked Data for Open and Distance Learning
  • The Importance and Potential of xAPI for OER
  • Case Studies of xAPI
  • Concluding Remarks
  • References

Introduction of Experience API

In the past, Sharable Content Object Reference Model (SCORM) had been the most successful learning standard in recording learning activities within web-based training systems, but it was created prior to widespread use of other types of delivery platforms and learning environments such as mobile devices, intelligent tutors, virtual worlds, games, wearables, and social networking tools. For example, mobile learning is now a ubiquitous educational technology; it can accommodate both formal and informal learning, in collaborative or individual learning modes. These capabilities can augment the performance of today’s learners, but the process cannot be tracked by SCORM. It is restricted to tracking specific course-oriented things such as lesson pages viewed, test scores, and module completions; the content must be managed through a Learning Management System (LMS).

“SCORM is a collection and harmonization of specifications and standards that defines the interrelationship of content objects, data models and protocols such that objects are sharable across systems that conform to the same model. This specification promotes reusability and interoperability of learning content across Learning Management Systems (LMSs).”  — from

SCORM is concerned with making contents portable between SCORM-compliant systems, but xAPI leaves any content residing anywhere it is and keeping any format it has, just records the experiences in a standard structure and language.}

Outside of LMS environments, Innovative and diversified technologies are increasingly available for teaching and learning. Although this phenomenon creates richness, diversity, and creativity in learning experiences, it also results in a serious problem — data silos. Digital learning generates data streams, and data is valuable for evidence-based learning design. But now they are locked in different tools, like thousands of puzzle pieces that can’t be put together. There is a need for “the next generation of SCORM.”

Advanced Distributed Learning (ADL) is a Research & Development (R&D) initiative of Department of Defense(DoD) that began as a joint project of the US DoD and the Department of Labor (with industry participation). You may know ADL as the organization that brought us the SCORM standard. Around 2010, ADL recognized a need to define an updated standard that could overcome many of SCORM’s inherent limitations. The paradigm shifts in training and learning led to the birth of Experience API (xAPI), which allows us to pull data together from multiple tools, devices, applications, and systems, and will ultimately provide a more personalized learning experience.

XAPI works on the following premises:

  • People learn from interactions with other people, contents, and tools. These actions can happen anywhere.
  • When an activity needs to be recorded, the application sends secure statements in the form of <Actor><Verb><Object> (Fig.1) , and additional details with <Result>, in <Context>, at <Timestamp>, with <Attachment>, to a Learning Record Store (LRS).
  • LRSs record all of the statements made. An LRSs can share these statements with other LRSs, and can exist on its own, inside an LMS or inside a machine.
 Minimum components of an xAPI statement

Fig.1 Minimum components of an xAPI statement

XAPI was initially based on the Activity Streams specification, which emerged from social networking and is used by sites such as Facebook, Twitter, and Google Plus. But more defined constructs were added for the storing and transferring records of learning experiences. Activity Streams are already widely used in games and social platforms for tracking group/guild activities and for real time data gathering and analysis. An Activity Stream can be thought of as a triple. A triple is similar with an expression in the form of subject-predicate-object used in the Resource Description Framework (RDF) World Wide Web Consortium (W3C) specifications. RDF makes up the basic components of the Semantic Web, and is called a graph data model. The expression relates data together and the resulting relationships can be used to infer information through semantic analysis. A primary example of semantic analysis is how Google knows so much about us and the types of content we are seeking. This is significant for Learning Analytics. To be accurate, xAPI is not a graph database model, it is more of key-value store, but it can become the glue that bridges graph models with various types of NoSQL data. We’ll talk more about this later.

Other significant meanings xAPI brings to us are:

  • Granularized records and contextual information from widely-diversified environments, not just learning events, can be captured.
  • Data storage and retrieval are independent of the applications that generated them. 3rd party reporting and analytics tools can integrate and re-use data from different LRSs.
  • Human interactions in group learning, peer learning, social learning, and instructor-led learning can be recorded and interpreted.
  • Like Activity Streams, the vocabularies are extensible and community-driven so the possibilities of learning design and tracking are limitless.
  • This JSON (JavaScript Object Notation) – based standard language can work with different programming languages, and it is bandwidth-non-intensive and suitable for Internet of Things (IoT) applications.
  • The focus of the learning standards has transferred from contents to experiences — interactions between learners and contents, activities, objects, and other roles.

The xAPI forms a building block for ADL’s eventual goal: to create a “Personal Assistant for Learning” (PAL) that can understand learner needs and provide personalized learning content at the right time. xAPI — learning experience tracking — is in fact the first cornerstone of the Training and Learning Architecture (TLA) that encompasses a set of standardized Web service specifications and Open Source Software (OSS) designed to create a rich environment for connected training and learning. Like SCORM, the TLA is not a system itself, rather enables systems or applications to be built for learning. The TLA capability supports ADL’s Next Generation Learning Environment research and development strategy and is laying the foundation for PAL (TLA, 2012).

(continue to read: Experience API (xAPI): Potential for Open Educational Resources – Part 2)

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Categorised in: Experience API Powered Learning, Open Educational Resources

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