Scrolling through LinkedIn today showed an awesome article written by Jason Haag on Learning Solutions that is well worth a read and needed to be shared.
The article looks at 10 best practice methods that should be adopted when developing and sending xAPI statements and in particular, using the Context Extensions to gather richer more meaningful data.
As Learning Record Stores (LRS) become smarter in reporting, having quality data based on existing profiles will ultimately provide better learning analytics.
If you’re developing anything with xAPI, you will want to have a read of this.
There’s an old computing adage, “Garbage in, garbage out,” that you may have heard referenced before when it comes to dealing with big data sets. Well, xAPI is no different. If you dig a little deeper and investigate all that xAPI has to offer, you’ll soon realize that there’s a lot of room left to more richly enhance the quality of your learning analytics beyond what’s typically recorded by only the Actor, Verb, and Object parts of the statement. Adopting best practices can go a long way, but what are best practices and why are there only 10 of them?
Jason Haag
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