From Ellen Meiselman, University of Michigan

I work for the Learning Management team for University of Michigan Health System. We run a learning management system for all faculty and staff at UMHS. We also develop and create much of the online learning that is used in the LMS, and provide education and support for embedded educators throughout the health system.

There are many things we wish we could do that cannot be done with the LMS technology we have now. Among them:

In addition, the SCORM 1.2 standard that we use for most of our trackable online learning has a variety of technical limitations which is what originally led me to participate in the early discussions of what SCORM 2.0 should look like.

Examples of the requirements typical of what I asked for in those SCORM 2.0 workshops and interviews include:

Now that we have been working with the xAPI standard for a while, there are some areas I would particularly like to discuss with the people involved in Medbiquitous:

Agent Profile Standards

Besides the Statement API, there are APIs for the Activity Profile and Agent Profile.
We can now access any part of a user or team profile from a learning activity, using a standard! For example, we could access roles or attributes that would useful for delivering role-specific pieces in a larger training module, like "is a Clinician", "works in a Patient Care Area", "performs Central Line Insertion procedures", "works in an operating room", etc. This can be done to some degree within an LMS, but not on a granular intra-activity level. It is usually difficult to add new vocabularies and taxonomies, and there is certainly no standard. Each learning object would have to be customized individually to access that data from an LMS and use it within the learning object.

Besides roles, we could locate competencies in the Agent Profile. These values could be static information, or dynamic links to competencies and performance criteria maintained by other applications.

All of these Agent Profile properties take the form of key value pairs, and you can have as many as you like. This means the learning activity can be adaptive, based on aggregated data from numerous disparate sources and modalities. Although many of these properties will need to be ad hoc, I think at least some of these profile facets should be standards,  so that applications can all access the same data the same way.  

Extensions

The Result object contains space for extensions. I think there is plenty of room for discussion here about what would constitute useful extensions for medical education and training, including HPML - Human Performance Markup Language - a way to encode performance data into xAPI statements, interoperably, so performance can be tracked somewhat uniformly across modalities.

http://www.adlnet.gov/tla/experience-api/adopters/xapi-and-simulation-interoperable-performance-tracking-to-support-tailored-learning/