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xAPI Profiles

2020 was all About xAPI Profiles (for us)

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Photo by Lisa Fotios on Pexels.com

A few days ago, Megan and I passed a milestone, with now seven years of MakingBetter. 2020 was all about xAPI Profiles (for us). It’s hard for me to grok how much we got done in 2020 considering the trash fire of a year it was.

Like many of you, Megan and I had to seriously change how we’ve managed our work/life balance, household, workflow(s). In this post, I’ll highlight what we shipped last year through MakingBetter.

The ADL xAPI Profile Server

In 2018, Megan and I drafted requirements for an xAPI Profile Server. Two years later, in 2020, MakingBetter built it with ADL.

We teamed with our besties at Veracity, keeping a learning standards team-up between Jono Poltrack and myself that spans almost two decades now, and keeping the running t-shirt jokes going between Megan and Tom Creighton. I digress.

To summarize, the ADL xAPI Profile Server is a revolutionary approach to governing data for xAPI-supporting applications. It’s an authoring tool for xAPI Profiles. It’s an RDF server, so it is processing all the semantic connections on the back-end; generating JSON-LD concepts while you author. It enables authoring tools, independent development environments to be dynamic and driven from the same authoritative document. Updating an xAPI Profile hosted on a server will make changes available to anything subscribing to that profile. Imagine managing taxonomies and ontologies for learning data that don’t necessarily require re-authoring.

Megan provided the vision and technical requirements that drove this effort, and led the technical development. Crystal Kubitzky did cracking (been watching a lot of Great British Bake-off) UX research and design, making full use of the USDS design system. Eva Rendle took on the unenviable task of managing the herculean effort to design, develop and deliver this product in 13 months’ time.

As a result, it represents that best of what can happen when everyone on a project is oriented to the same goal. Collective focus, talent and hope drove this project in 2020. The love our team put in that effort shines through when you use it.

It launches in Q2 2021. Watch me introduce and demo some of the features of the ADL xAPI Profile Server here.

xAPI Profile Authoring

MakingBetter worked with Veracity to produce a significant xAPI Profile. For the long-game on xAPI, we produced a profile with ADL to support the prototype development of the Total Learning Architecture (TLA). The profile expresses the TLA’s Master Object Model (MOM). In the coming weeks, expect posts to surface lessons learned about profile authoring and thoughts around enterprise learning analytics strategy inferred by this work.

For now, if you’re interested in reading more on the MOM and the TLA, read here.

More?

In the next post where I’ll get into what all I’m doing, with all the different hats I get to wear. After, with that bit of needed meta established, I can get into blogging about the really real nitty gritty of working with xAPI.

Dimensions in Learning Analytics

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Dimensions, in learning analytics, are the ways we describe the (theoretical) space in which we’ll analyze… learning. I think of a given xAPI Profile as the technical instructions I want tools, systems and services to calibrate on for the way I need to make sense of the data. Yesterday, I shared a demo given of the forthcoming ADL xAPI Profile Server. Today, I step back to share a mental picture of how learning analytics can be framed.

In 2019, I collaborated with Judy Katz on some ideas for visualizing learning analytics strategy for the xAPI Camp @ Learning Solutions 2019. Judy and I each had our takes at the time on how we might frame the “space,” but with almost two years to reflect and multiple opportunities to put those ideas into practice, it’s abundantly clear how we each labeled the dimensions was less important than how we organized and measured similarly.

Dimensions

A simple way to think about learning analytics is that when we want to analyze learning, we look for information about:

simple model of learning analytics dimensions: Learner by learning activity by learning experience
A rather simple model of the dimensions of learning analytics.
  • The Learner,
  • The Learning Activity, and
  • The Learning Experience

… and all of these analyzed over Time as a constant means of comparison.

Dimensions tend to stay affixed, once set. The trajectories along which we measure things likely will remain the same. Much investment of time and human capital is built on this framing, so before anyone codes anything, this model should be treated as something that can be revised, even tossed out, in favor of something better. The investment of time and effort in planning is minimal, no matter how long the process takes, compared to the costs of implementing the wrong learning analytics strategy.

Metrics

Along each of these dimensions, I’d identify metrics. Metrics help to understand the dimension of learning I’m analyzing. For example, I might break a Learner dimension down into the type of Learner, or user, anticipated by the learning experience. If I’m developing a learning solution for practicing nurses, the “Learner” likely includes the “nurse” but may also include other roles, like a Nurse Preceptor or a Nurse Educator. A dimension like “Learner” should account for every type of participant.

Tomorrow, I’ll start diving into the ways I might break down those metrics more thoughtfully, related to the Learning Activity vs. the Learning Experience.

xAPI-Camp-Learning-Solutions-2019-Learning-Analytics-StrategyDownload

Level Up Learning Data with xAPI in 2021

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You’re likely going to be reading up seriously on how to work with learning data sometime in 2021. This will be true regardless of whether you work in online K-12, Higher Education or professional training — anywhere in the world. If you will “own” xAPI know-how on your team (or maybe for the whole organization), I want to help you.

Megan and I have certainly been in your shoes.

So, I made a resolution for 2021 – I’m going to try and blog daily again like I did maybe 15 years ago about Flash For eLearning. It’s time for us all to level our data game up.

First, let’s start with this webinar (above), where I recently demonstrated a new tool coming in Q2 from ADL, the xAPI Profile Server we produced for ADL with our friends from Veracity. In the video, I explain what this is, what problems it’s going to help with and how you’ll likely put it to work. Spoiler: it’s a tool to help you author and serve xAPI Profiles, doing a lot of the heavy lifting of complex rules thingies for you.

Next, I’ll blog about how to frame a problem space to apply learning analytics with dimensions.