There is a new emerging standard for eLearning – the Tin Can API.
Tin Can API was originally intended to become the next version of SCORM, the old-standby communication standard used by learning management systems (LMS) since the dawn of digital time. (Or at least since 2001, which is close enough.) SCORM is used to include eLearning modules into an LMS. Almost all current learning management systems support SCORM, and use it to pass quiz scores and similar data from learning modules to the LMS itself, where they form part of the learners training record.
For the past decade and a half this equation: SCORM + LMS = eLearning has served both academic and corporate training organizations very well. Vendors got to sell LMSs and SCORM learning modules, trainers got to collect somewhat-useful metrics, and everything more or less worked together most of the time.
It was a simpler time, back then. A number of factors have changed that are driving the demand for a newer, more flexible approach to eLearning:
- Lean Learning Techniques – Modern learning concepts, from the flipped classroom to competency-based learning, badging and MOOCs, have opened up a range of new possibilities for eLearning. The expectation that learning happens on a single system delivering a pre-defined set of learning modules no longer fits reality very well.
- RESTful APIs – The web is changing, and data portability is a very large part of this change. Modern content management systems and web applications are designed to make data easily transferrable between systems. Data is no longer bound to a single system, and easy portability is expected.
- Mobile Learners – Learners and trainees move rapidly between jobs, roles, devices and institutions. learning often starts in one place on one device, and finishes in another. If it finishes at all, since lifelong learning and the use of web-based performance support for just-in-time learning is now the norm.
- Big Data – Real-time data collection and analysis drives corporate and organizational insights, and the demand for this kind of depth of data applies at least as much to learning as is does to other aspects of the organization.
The Tin Can API overcomes the limitations of the older SCORM standard to net these new demands. it easily includes data from multiple systems, uses a modern API techniques for communications, is highly flexible and mobile friendly. It also allows for a much richer view of the learner’s experience than was available in the past.
A good example of the strengths of Tin Can API is in on-boarding new staff. One of the most common training processes in the corporate world, new employee orientation is typically driven by a mix of compliance-driven learning, such as WHMIS and key corporate policies, and soft-skills learning aimed at easing the transition of new staff onto the team. This is not particularly suited to a conventional LMS with the typical mix of videos, interactive exercises, and references to outside documents. When the eLearning points the trainee to an outside resource, for example, how do you truly confirm that the resources has been read and understood?
This is where the versatile Tin Can API comes in to its own: Unlike SCORM, Tin Can is not bound to a specific Learning Management System. Any system or device can generate Tin Can statements, which are then received by a Learning Record Store, where they become part of the data stream and are correlated with the person, learning activity, and object the user interacted with.
In our on-boarding example, in addition to tracking activity in the LMS and its learning modules, the users exploration of the corporate policies on the company website, viewing of videos social media channels, physical location data showing that they have toured the facility, self-directed research on the web, and interaction with mobile apps can all be included in a single detailed picture of their learning activity.
Tin Can API enables flexible multi-channel learning, and is is readily available today for use in your new, more experiential, eLearning and mLearning projects.