TinCan or xAPI has been around for quite some time now. However, it has not generated the kind of buzz it was due given its ample flexibility compared to SCORM. Much of corporate learning still tends to rely on an age-old SCORM standard.
A lot of it is attributed to legacy content developed over a period of 20 years that still has value from a learning perspective, and also to the fact that most LMS providers, as well as rapid authoring tools, still support SCORM. Hence, even with the rise of xAPI, learning organizations are not in a hurry to adopt it as the philosophy is very simple – if it ain’t broke, don’t fix it. The real problem is learning formats, which still tend to be predominantly regular Web-based training, where the tracking and reporting requirement does not usually go beyond the completion status, score, and time spent which is well supported in SCORM.
However, the last few years have seen a steady rise in the demand of other engaging learning formats based on Augmented Reality/Virtual Reality (AR/VR), serious games, simulations etc. where traditional SCORM tracking will not be enough to capture the data and insights these formats can generate. Organizations are also adopting Artificial Intelligence and Machine Learning to understand learning behaviours and provide learning experiences that are tailored to specific individual needs. This again requires lot of data in the context of learning which is used by these frameworks.
Following are some examples of how xAPI can be leveraged to create smarter and innovative solutions.
‘Data is the new oil’. This applies to learning data as well. xAPI makes it possible to collect data from a wide range of (online/offline) experiences across different systems and stores them in an LRS (Learning Record Store). Following are some examples of the data that can be captured across different Learning formats using xAPI:
Making use of Data:
The LRS provides inbuilt analytics on the captured data. Besides, the data can also be exported for consumption by any third-party system. The exported dataset can then be analyzed for providing custom analytics, creating adaptive learning models, etc. E.g. Analysis of Simulation data may show that a learner may need intervention on a particular KPI/parameter. Also, behavioural data may suggest that the attention span of the learner is short and that they prefer a video format which is also a suitable learning style for the content.
Following are some the use cases of how xAPI data can be used to design innovative, engaging and effective learning experiences.
“Learning is a journey, not a destination.” The effective use of xAPI can make this journey a memorable one for the learner, making it holistic and meaningful and it also ensures a better ROI for the organization. More and more organizations are realizing this need for transformation which means the sunset of SCORM and the dawn of xAPI and newer progressive standards are closer than ever before.
– By Parthasarathi Sett, Vice President – Technology at MPS Interactive Systems