Why I'm thankful to work in L&D
Why I'm thankful to work in L&D
(And why you should be too.)
Last week, my wife and I made our annual pilgrimage to the United States for Thanksgiving.
As an outsider, I’m utterly fascinated by the traditions surrounding Thanksgiving — watching the parade, playing “football”, dousing savory foodstuffs in sugar, etc.
Before I met my wife, my experience of these traditions had come exclusively through television and cinema, through the likes of Friends and Miracle on 34th Street.
Watching these movies and TV shows, it always struck me as quaint when, in the middle of dinner, the characters would stand up and take it in turns to give thanks for something in their lives.
The earnest sincerity of this tradition feels profoundly un-British and, dare I say, even more exotic than combining marshmallows and potatoes.
In the L&D Dispatch, we often focus on the deficiencies of L&D — on the things that are broken that need to be fixed. But I want to take a different tack this week.
Perhaps I’ve spent too much time in America, or maybe the spirit of the season has finally started to melt my cold, cynical heart, but I’d like to dedicate this edition to explaining why I’m thankful for my profession — and why I couldn’t imagine doing anything else.
❤️ I get to make a difference in people’s lives
It’s easy to lose sight of this from one day to the next, but our role in L&D is fundamentally about helping people thrive at work. We may not be curing diseases, championing social causes, or rescuing people from burning buildings, but I genuinely believe there is a nobility in a profession that’s dedicated to learning.
The recent focus on business impact and ROI in L&D is generally a positive development — in many ways, it’s long overdue. But if I thought the sole purpose of my job was to move certain metrics or hit specific KPIs, I don’t think I’d keep doing it.
🎩 I get to wear many hats
In a previous newsletter, Ross G explained that the modern learning professional has many faces. One day, you’re a designer. The next day, you’re a web developer. The day after that, you’re a data scientist.
While the varied demands of this role can be stressful, they also make the job interesting. I enjoy the intellectual challenge of trying to get my head around complex topics, applying different skills to scope out problems, identify the source of these issues, and then develop solutions to address them. No two days are the same, and I’m incredibly grateful for that.
🤲 I get to be part of a community of learning nerds
When I took my first job in L&D, I was reluctant to accept it as a career path. I’d previously worked in the tech start-up space, where it felt like cool people were making cool products and trying, in their way, to change the world. In contrast, corporate L&D just seemed kind of… lame.
While I do still see strangers’ eyes glaze over whenever I describe what I do for a living, I no longer view L&D (or the people who work in it) with the same lens. Through recording the podcast and attending conferences, I’ve had the opportunity to meet interesting, likeminded people from a range of backgrounds, and become part of a vibrant community of learning nerds. If you’re reading this newsletter, you are very much a part of that community.
🙏 I get to work with an amazing team
This last one is a bit of a cheat, as it isn’t about my profession so much as it is about my team at Mind Tools. I’ve now been working at Mind Tools for over eight years and, while I love my job for its own sake, I don’t know if I would have been here this long without my team.
Getting to work with a bunch of smart, dedicated people every day is an honor and a privilege. I’m thankful for you all — even those of you who don’t bother to read the Dispatch. 😉
What are you thankful for? If you want to discuss this, or your custom learning development needs, just email custom@mindtools.com or reply to this newsletter from your inbox.
🎧 On the podcast
Instructional designer and author Julie Dirksen’s first book, Design for How People Learn, is a core text here at Mind Tools Towers. So we couldn’t wait to speak to her about her follow-up — Talk to the Elephant: Design Learning for Behavior Change.
This week on The Mind Tools L&D Podcast, Julie joins Ross and Owen to discuss what she means by the ‘rider’ and the ‘elephant’, and the many (often good) reasons that people don’t do what they are told.
Check out the episode below. 👇
You can subscribe to the podcast on iTunes, Spotify or the podcast page of our website. Want to share your thoughts? Get in touch @RossDickieMT, @RossGarnerMT or #MindToolsPodcast
📖 Deep dive
In the fifth episode of the TV sitcom Frasier, psychologist Niles Crane moans:
‘Who knows why anyone does anything?’
Frasier replies:
‘Remind me again what you do for a living?’
It’s a throwaway gag, but it speaks to a fundamental truth: Human behavior is complex, as Aim for Behaviour’s Robert Meza explains in this fantastic LinkedIn post (thanks Julie Dirksen for sharing).
In the post, Robert summarizes nine different theories for technology adoption from H. Taherdoost’s 2018 paper ‘A review of technology acceptance and adoption models and theories’.
The ‘Theory of Reasoned Action’ for example can predict human behavior through attitudes, social norms and intentions, but does not address habitual or moral factors. The ‘Technology Acceptance Model’ focuses on the perceived usefulness and ease of use of technology, but ignores factors like social influence.
The key point here, I think, is that people are complex - and often irrational. We can use theories and frameworks as lenses through which to explain their behaviour, but our interpretation will vary depending on the lens we use.
Which circles back nicely to the podcast above!
Taherdoost, H. (2018). A review of technology acceptance and adoption models and theories. Procedia manufacturing, 22, 960-967.
👹 Missing links
👀 Cambridge Dictionary names ‘Hallucinate’ Word of the Year 2023
In a year where AI has been absolutely everywhere, it’s perhaps not surprising that Cambridge Dictionary has chosen ‘hallucinate’ as their word of 2023. More interesting to me were the accompanying comments from Dr Henry Shevlin, an AI ethicist at the University of Cambridge, who suggested that the word reflects our readiness to anthropomorphize artificial intelligence, ‘implying an agent experiencing a disconnect from reality’.
🤖 What can Copilot’s earliest users teach us about generative AI at work?
Sticking to the topic of AI, a new report from Microsoft explores the impact of its ‘Copilot’ tool on productivity in the workplace. Amongst the users surveyed for the report, 70% said they were more productive thanks to Copilot, while 64% said they spent less time processing email. Perhaps most importantly, 77% of respondents who had used Copilot said they didn’t want to give it up.
⚡ Do animations improve learning?
A couple of weeks ago, I wrote about Richard Mayer’s principles of multimedia learning for our regular ‘deep dive’. One of these principles suggests that, generally speaking, static images should be favored over animated images when it comes to designing learning content. So, are there ever circumstances where animation can improve learning? This excellent blog post from Andrew Watson explores the research. (Shoutout to Mike Taylor’s Friday Finds newsletter for bringing this to our attention.)
👋 And finally…
With Thanksgiving behind us, Michael Bublé has now completely defrosted and is playing on repeat in our household. Here’s a banger to kickstart your week.
👍 Thanks!
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