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v7.2 - moving along, a point increase at a time

Multilitteratus Incognitus

Pondering what to learn next 🤔

Siri, Alexa, Cortana...OK google - show me something to learn!




Alright, so here it is, week 6 of NRC01PL. Even though I am technically in the same week as everyone I guess I am still marching to the beat of my own drummer.  I wanted to join the live session on Tuesday, but other things intervened.  Oh well.

The topic of this week is the personal learning assistant.  Hence my little callout to the four major virtual assistants (Siri for Apple, Alexa for Amazon, Cortana for Windows, and Google...for Google). I actually did try asking Cortana to "show me something to learn" but  I guess the bing search engine didn't know what the heck to do with my query. Google wasn't that much help either.  We haven't reached the point yet where they know enough about me in order to recommend something.  It's a little odd given how much data google probably "knows" about me.

So, what is a Personal Learning Assistant (not to be confused with Personal Assistant for Learning)?  According to Stephen the PLA is a platform that  (1) provides a convenient interface for the user to perform the task (of learning), (2) the platform treats each user interaction as a training example (think amazon recommendation engine); and (3) it learns general regularities from this training data (think google knowing where my home and work are based on how much time I spend at locations, and during what times).

Another thing that Stephen mentioned was something called Business Oriented Personal Learning Agents (reminds me a lot of my HR and KM days). Some components of this are (1) human learning profiles across demographics (meaningful demographic, not the silly stuff that we fill out), (2) integration of operations and training databases; (3) unbiased evaluation of performance (I assume this is by your manager); (4) development of enterprise learning profiles and patterns of learning and action; (5) making training available in multiple modalities (and multiples providers and sources).

This seems like something that is quite interesting from a work perspective.  The one concern I have about this is data lock-in.  In days past people used to stay with one company for a big part of their career.  Learner data-lock-in would not be such a big issue if you're someone like me (at the same institution for close to 20 years now), however if you're like some of my classmates, you've worked for at least 3 different companies in the last 10 years.  Having an internal gauge of how employees are doing, what they need to learn, and how effective that learning is great. It helps corporate instructional designers and talent developers do their jobs more effectively.  However, I do think that this data does also be long to the learner, as it forms part of their lifelong learning record.  If they leave that company, and if the data is proprietary (or under some sort of NDA) then that, to me, is a bit like a brainwipe (at least a partial one) for the learner's record. If there is a need to keep some information compartmentalized due to NDAs and a company's competitive advantage, then I'd like to see an appropriately scrubbed and generalized learning record exported concurrently to the learner's preferred performance and assistance platform.

Finally, when we're thinking about the personal learning assistant, I am reminded a lot of the Knowledge Navigator (see video at the bottom).  While this was meant to be a concept for PDAs, I think we're still seeing a lot of this vision coming to fruition today with our connected devices.  I think the PLA also falls into this category.  The problem, as I brought up in my previous blog post, is that we have a lot of data about us out there, but they are inaccessible to a central platform of device that crunches all of that into something that is useful for the learner.



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