This is an interesting and useful guide describing in detail how to use xAPI. It thereby serves as a good way to understand xAPI as a concept. This is the second article in a series (see the first, from last March, on getting started with xAPI and Storyline). In this article she shpws "how to create custom xAPI statements for Storyline, that is how to send data from Storyline triggers to your LRS." You need to develop the xAPI triggers at specific points in your resource, and then you can track how people are using it, whether they finished, and whether they replayed it. See more on the same topic from her blog (and pulling a live stream of the data from her example). Here's a bit more from HT2 Labs.
This is basically marketing content but I'm including it today as evidence of a wider trend in learning toward workplace performance support over formal in-class training. As the headline suggests, performance support needs to be context-aware, knowing not just what the learner is doing but also what they've done (and learned) in the past. According to the site, "Today’s workers want answers fast and have little patience for training that cannot be immediately applied. Just-in-time training (JITT) is one way to meet this need by providing easy access to up-to-date microlearning content." I'd suggest that this is what people in general want, not just workers (I have certainly seen a demand for it at the executive level). Having said all that, there's still a lot of manual intervention required to make such a system work. You need to define and gathaer data on company key performance indicators (KPI). And you need to define and gather employee performance and business data.
I don't think this author is telling us anything we don't already know, but there's a nice analogy in the retelling. Basically, there are two points being made: first, our devices (collectively known as the Internet of Things (IoT)) are reporting back to advertisers and marketers through backchannels; and second, we do not own full rights to our devices, but merely license the software that is used to run them. The analogy is feudal: "In the feudal system of medieval Europe, the king owned almost everything, and everyone else’s property rights depended on their relationship with the king." There were some differences, of course, between the feudal system and today's reality. But it's an interetsing comparison.
The idea of an Open Access (OA) dashboard is to automate some processes related to accessing and distributing open scholarly materials. This article reports on the outcome of an OA dashboard feasibility study (41 page PDF). The results are not encouraging, as it suggests a business case cannot be made. "Although there is a gap in terms of analysing data on OA, open data sources are not mature enough to power a dashboard and may undermine the validity of its outputs."
IBM has unveiled "a smart search engine that uses Watson’s ability to parse natural language and make recommendations with the aim of accurately matching what teachers are really looking for." Interestingly, "Populating the search engine is a collection of more than 1,000 OERs—from sources such as Achieve, UnboundED and statewide orgs like EngageNY—hand-selected by math experts assisting the program." The product is called Teacher Advisor With Watson 1.0. 1,000 OERs isn't very many, so I'm thinking this is more of a 'stake in the ground' for IBM, marking territory it intends to begin developing.
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Copyright 2017 Stephen Downes Contact: email@example.comThis work is licensed under a Creative Commons License.