Last week, I met with a potential new client to discuss the work we do on the Mind Tools Custom team, and how we could help them develop leadership capability in their organization.
The prospect was interested in exploring alternatives to their existing self-directed offering, which had failed to generate the engagement they’d hoped for.
When I asked them what was behind the lack of engagement, their sense was that colleagues simply didn’t have time for learning. It wasn’t that the content they had was bad — people were just too busy for it.
Mind Tools’ own research suggests that this is a widespread concern for learners. In our 2022 ‘Learner Intelligence Report’, 62% of employees reported a lack of time as the most significant barrier to learning at work.
Against this backdrop, it’s perhaps unsurprising that the client’s existing solution hadn’t gained traction.
In an environment where people feel increasingly time-poor, merely creating opportunities for learning won’t get the job done. If we want people to take up these opportunities, we need to provide guidance and structure. We also need to work with managers to ensure that time is set aside for professional development.
On the other hand, I think the ‘I don’t have time to learn’ argument is based on two fundamental misperceptions.
🎓 1. ‘Learning only happens in the classroom.’
When people claim that a lack of time is the biggest barrier to learning, what they mean is that it’s the biggest barrier to formal learning. And, as we know, most workplace learning doesn’t happen in the classroom, but on the job.
🕰️ 2. ‘People will willingly engage in self-directed learning if given the time to do so.’
Secondly, I don’t really buy the notion that if people just had more time at work, they’d actively choose to spend their free hours completing e-learning modules or attending workshops. Instead, they’d probably spend it catching up on all the ‘important but not urgent’ tasks that are easily neglected day to day. Or, perhaps more realistically, they’d spend it doom-scrolling on social media.
None of this is to say that formal learning isn’t important, or that organizations don’t need to worry about giving employees the time and space to learn.
But when learners say they don’t have time for learning, they might actually be saying ‘This doesn’t help me tackle my immediate challenges’.
Compared to changing the number of hours in the day, that’s an easier problem for L&D to solve.
Want to share your thoughts on this week’s Dispatch? Interested in working with our Custom team? Then get in touch by emailing custom@mindtools.com or reply to this newsletter from your inbox.
🎧 On the podcast
If you work in learning and development, you probably get some direction from your senior leadership team about what to focus on and how much to spend. But, once you get into the details, you have lots of room to play. In a sense, to act as an R&D department!
In last week’s episode of The Mind Tools L&D Podcast, Marc Steven Ramos joined us to discuss:
the strengths and weaknesses of different genAI tools;
whether tools like ChatGPT are living up to the hype;
how L&D can start experimenting, and why it’s the ideal team to do so!
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 their latest report, AI in L&D: Intention and Reality, Donald Taylor and Eglė Vinauskaitė explore how artificial intelligence is actually being used in L&D, nearly two years on from the initial launch of ChatGPT.
And what they found is that, with some notable exceptions, the majority of L&D teams continue to see the primary benefit of AI as the ability to create content, typically with a focus on speed over quality.
While it might be tempting to view content-creation as the first step along a path to AI maturity, Taylor and Vinauskaitė argue this is misguided:
‘AI, […] is not a single technology but an umbrella term for a range of technologies, each with very different routes to successful adoption. Success in climbing one mountain of adoption (e.g., creating content) will be of little use in climbing the next (e.g., inferring skills).’
Taylor, D & Vinauskaitė, E. 2024. ‘AI in L&D: Intention and Reality’.
👹 Missing links
In the wake of Redbox DVD’s bankruptcy, the code that runs the company’s rental machines has been dumped online. This has led some tinkerers to adopt the now defunct kiosks and reverse-engineer their operating system to figure out how it works. Naturally, one of the first things someone decided to do was find a way to install the video game Doom.
Last week, Anthropic announced Claude 3.5 Sonnet, the latest version of the company’s large language model. What makes this announcement noteworthy is a new feature called ‘computer use’, which allows developers to act as agents, completing simple computer-based tasks in the same way as a human would. While Anthropic describes the feature as ‘experimental - at times cumbersome and error-prone’, this release marks the moment generative AI broke out of the chat interface.
📚 Diary of an Author: 7-12 October 2024
I recently discovered Daniel Piper’s excellent Diary of an Author newsletter, and it has brought some much-needed levity to a Substack feed that is otherwise filled with content on L&D, AI, and U.S. politics. Describing himself as a ‘Serious Literary Author’, this edition sees Piper fretting over a typo in one of his emails. Then fretting over a typo in the follow-up message he sent to correct his mistake...
👋 And finally…
I’m pretty sure this is exactly how my wife sees me.
👍 Thanks!
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