Archives for July 2023

Ok, so the title’s a bit over the top, but…I think there’s something here. Everyone is now talking about how AI can take over a bunch of ID roles. Frankly, I agree (and have said so). In thinking about it (on a walk, as usual ;), I realized there’s a reframing, and I think it’s important. Despite being a tad flip, I do think emotion is the new ID.

So, there are things AI can’t do. It doesn’t really understand, basically. It can look at relationships and infer structure from good content! (That is, if there’s bad content, the inferences are also bad). We still need oversight, basically. So, one role will be to check AI output for accuracy. However, that’s something that largely comes from domain expertise. We’ve always needed subject matter experts to review output.

When I say AI doesn’t really understand, I mean more, however. It’s syntactically manipulating to generate semantics, but semantics is still largely cognitive. Yet as humans, we’re affective (personality) and conative (motivation) as well. In short, we’re emotional (not purely rational). Context matters. Meaning matters! We need to address these elements in our learning experiences.

Thus, I posit that it takes humans to write the introduction to learning experiences, to set the ‘hook‘. Similarly, it takes humans to make practice activities (aka assessment) that have an engaging context, appropriate challenge, and naturally embed the task. Essentially, making the practice meaningful. That’s something we, uniquely, can do.

When I wrote my book Make It Meaningful, I was explicitly addressing the fact that much of ID addresses the learning science alone (if even doing that). It was designed as a complement to my learning science book, to provide a complete LXD picture. What I didn’t expect was the advent of the LLM AIs. Yet, serendipitously (it seems to me, with the usual caveat ;), the latest book addresses the most important part of learning that AI can’t do now or  in the foreseeable future.

Look, I strongly believe that we don’t pay enough attention to engagement, and yet we can. (Note: I do not mean the trivial engagement approaches: tarted-up content presentation like ‘click to see more’, fancy production values, etc.) I run workshops online and face-to-face on this because it’s my passionate and informed belief, not because it’s going to make me rich (it won’t). It just so happens that with this advent, I think it’s even more true that emotion is the new ID. Fortunately, I think we do know how to do it. I think it gives us a role going forward; a way to answer the question: but what about AI? We just have to be prepared to respond. Are you?

I’ve previously complained about the RFPs that orgs send out. And, having just reviewed one, I have to say that I stopped short. There’s more that a company should do if they want to get a good proposal. It has to do with the actual requirements for learning, not for the proposal. There’s always that stuff (what sections, what deadlines, etc). However, too often what’s given doesn’t give enough to actually propose a solution. I want orgs to give us the right info! What do I mean?

The proposal had the sections that were to be covered. With an objective for each. Which were ‘provide information’ and then a listing of content! Sure, we could say we’ll do a knowledge dump, but you and I both know that won’t lead to any meaningful change. We could do our own inferences, and of course we did. But why?

Why aren’t we getting:

• performance objectives
• misconceptions/ways they go wrong
• models
• stories & examples
• etc?

These are the things that we need to scope a solution: to think of a pedagogical approach, to actually make something that works! It’s much easier to choose a pedagogical approach when you know what people have to do as an outcome. It affects scope, media, and more as well. All things that organizations want in responses, but they don’t give you enough to do with it. They list content, and time (!).

Sure, we’ll ask these questions through the mechanisms they provide, and it shows we know what we’re talking about. It’s not clear they do, however! It’ll help us lift our game as an industry, collectively, if orgs start to give us the right info to make good proposals. Until then, we’ll see orgs request and vendors respond with info dump courses. And we’ll continue to bore our learners and waste everyone’s time and money. Sigh.

Last week, I gave a webinar with the CEO of Upside Learning on microlearning. In the commentary, one of the attendees pointed to the research of Pooja Agarwal. Turns out she’s worked with Roediger (one of the authors of Make It Stick, a book on my list). In a paper I found there, I found justification there for an approach I’ve advocated. My point is that we should make meaningful practice. Which is something I think we don’t focus enough on, so let me elaborate.

So, I argue that even for rote knowledge, you should retrieve in context and apply it. That is, I believe strongly in how Van Merriënboer talks about the knowledge you need and the complex problems you apply it to. That is, the knowledge underpins the ability to determine an appropriate approach and execute.  However, checking to see whether you have the knowledge can be either typical knowledge test or retrieval in some meaningful way. I think the former is boring, but it did seem to align with what learning science would imply.

Fortunately, in that paper (PDF), however, she tested and found that while lower level testing lead to better lower-level recall, it didn’t impact higher-level problem-solving.  Even a combination of low- and high-level questions wasn’t noticeably better than just higher-level question practice. So, if you want the higher-level skills, you practice them and that’s what’s necessary. Such questions require you to know the lower-level material, but don’t seem to need fact-checks.

Which, for experience design, is great news. My book on engagement suggested more meaningful practice. (It’s really on learning experience design, as it’s a complement to my learning science book. The final chapter talks about a design process for integrating learning science with engagement. ) What I proposed was to make practice meaningful by  retrieving information in the context of applying it. This is the case whether it’s mini-scenarios, branching scenarios, or full games.

FYI, if you’re seeking a face-to-face workshop talking about engagement, I’ll point you to my upcoming one at DevLearn in Las Vegas on October 24. The focus is on elegantly integrating engagement, including how to make meaningful practice, It received top ratings across the board when I ran it last year, so I am confident it’s worth it. I’m running a related workshop online right now, but at times most appropriate for the Asia-Pacific region, but if you’re interested, you might check it out.

The Internet Time Alliance Memorial Award, in memory of Jay Cross, is presented to a workplace learning professional who has contributed in positive ways to the field of Informal Learning and is reflective of Jay‘s lifetime of work.

Recipients champion workplace and social learning practices inside their organization and/or on the wider stage. They share their work in public and often challenge conventional wisdom. The Award is given to professionals who continuously welcome challenges at the cutting edge of their expertise and are convincing and effective advocates of a humanistic approach to workplace learning and performance.

We announce the award on 5 July, Jay‘s birthday.

Following his death in November 2015, the partners of the Internet Time Alliance — Jane Hart, Charles Jennings, Clark Quinn, and Harold Jarche — resolved to continue Jay‘s work. Jay Cross was a deep thinker and a man of many talents, never resting on his past accomplishments, and this award is one way to keep pushing our professional fields and industries to find new and better ways to learn and work.

We introduce the winner of the 2023 ITA Jay Cross Memorial Award: Keeley Sorokti, (on the recommendation of a previous winner, 2018’s Mark Britz).

Keeley Sorokti’s career as a knowledge management professional has been marked by her expertise in guiding organizations and teams through transformative journeys in designing and sustaining social learning, online community, and knowledge-sharing practices. Her impact can be seen in her work with multiple technology, non-profit, and higher education organizations, where she has improved knowledge creation and sharing, cross-boundary connections, collaboration, and learning experiences. Currently serving as the Director of Knowledge and Collaboration at Sift, a Digital Trust & Safety late-stage technology startup, Keeley’s role involves co-designing solutions that place people at the center, fostering an open learning, knowledge sharing and collaboration culture across the organization.

In addition to her role at Sift, Keeley Sorokti’s influence extends beyond her workplace. She actively shares her expertise and insights. As an instructor, she co-teaches the Creating and Sharing Knowledge class in the Master of Science in Learning and Organizational Change (MSLOC) program at Northwestern University. She co-founded the Chicago Online Community Professionals peer-to-peer community of practice and coworking group where KM, L&D, online community, and digital workplace professionals from around the world support each other as they work to transform the way we work, learn, and share knowledge in our organizations.

Keeley has shown a commitment to advancing the field of workplace learning and her passion for working out loud and making work visible exemplifies her humanistic approach to learning and performance.

Browse Keeley’s articles and presentations: tinyurl.com/keeley-sorokti