What are the downsides to an outcomes focus?
How an obsession with output can blind us to the bigger picture.
In our last newsletter, Ross G wrote about the intangible benefits of the ostensibly frivolous moments we spend together as colleagues.
This week, I want to pick up where Ross left off, and explore what intangible benefits look like in the context of learning design.
A couple of months ago, I read an article in The Atlantic titled ‘The End of Foreign-Language Education’, and I’ve been thinking about it ever since.
In the article, Louise Matsakis explores the declining popularity of foreign-language programs at schools and universities around the world. According to data from the Modern Language Association, enrollment in college-level language courses dropped 29.3% in the United States between 2009 and 2021.
As Matsakis points out, there are various factors which might be contributing to this trend, including the rise of isolationist politics and cuts to humanities funding. But one of the most likely drivers is machine learning and artificial intelligence.
When I was a language student in the mid 2000s, I would never have dreamed of using a tool like Google Translate for an assignment. The technology just wasn’t good enough, and a machine translation would have been easily caught by any of my professors.
But a lot has changed in the last twenty years.
In 2024, Google Translate still might not provide idiomatic translations 100% of the time, but it’s ‘good enough’ for most purposes.
Meanwhile, AI-powered video platforms are making it possible for anyone to synthesize multimedia in different languages, delivered in their own voice.
In the not-too-distant future, we may all be walking around with a technological ‘Babel fish’ in our ears, providing frictionless translation into any language.
From a pure outcomes perspective, these advances — and the ensuing death of the language degree — should be celebrated.
If technology will soon enable us to communicate fluently in French, Spanish, or Mandarin, then why should anyone waste their time learning a foreign language?
In my opinion, there are three key reasons:
🗼 By learning French, I was also learning English.
Whatever skill I possess in English, much of it can be attributed to studying French. Mastering a second language requires the learner to think about words and phrases at a granular level — what comes naturally to a native speaker demands real effort from a novice.
Over time, this methodical approach to constructing sentences in French changed the way I wrote and thought in English. It also taught me to see the beauty in language.
🥐 Language and culture are inextricably linked.
While technology will facilitate communication across cultural boundaries, part of me wonders if something will also be lost in machine translation.
The experience of speaking to another human being via a technological mediator is not the same as the experience of stumbling your way through a conversation in their native tongue. Machine translation can deliver technically proficient communication, but it cannot deliver cultural understanding, which is inextricably tied to language.
🤗 Language-learning promotes tolerance.
Studying French and, subsequently, living in France were formative experiences for me. Without getting too political, learning a foreign language and immersing myself in another culture have undoubtedly shaped my worldview, and my openness to different ways of thinking.
My point in sharing all of this is that, had I been tasked with defining learning or performance outcomes for my French degree, I wouldn’t have thought of any of these ‘intangible benefits’.
Of course, the purpose of L&D is not the same as the purpose of education. But it’s worth remembering that the value of the work we do as learning designers extends beyond the business metrics we’re tasked with moving.
While the outcome of your sales training might ultimately be increased sales, it also has the potential to:
🕺 Boost engagement and morale by signalling to learners that you are investing in their professional development, potentially improving retention over time;
👯 Strengthen team cohesion by bringing people together who may otherwise work remotely or have few opportunities to socialize in person;
💡 Improve organizational culture by establishing learning and continuous improvement as part of BAU.
In L&D, it’s our job to deliver on the outcomes that matter to the business. But we shouldn’t lose sight of the bigger picture.
Interested in working with the Mind Tools Custom Team? Want to share your thoughts on this week’s Dispatch? Then get in touch by emailing custom@mindtools.com or reply to this newsletter from your inbox.
🎧 On the podcast
In ‘Measure of a Man', episode nine of the second season of Star Trek: The Next Generation, the Enterprise crew debate whether their robot companion, Data, is truly alive. More interesting for us, though, is the way they interact with artificial intelligence (AI) in general. Not just for what it tells us about how AI tools might evolve, but also for how we humans work with them.
In this special episode of The Mind Tools L&D Podcast, Ross G, Claire, Nahdia and I discuss how closely the Enterprise computer reflects current tools like ChatGPT, whether we want robots to work alongside us, and whether the Turing Test still has relevance.
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
At the height of the Covid-19 pandemic, educators and policy-makers expressed concern about the impact that lockdowns and school-closures would have on educational attainment amongst young people.
So, what does the data say? Was Covid really as bad for students as many of us assumed?
As ever, the answer depends on the metrics you choose to look at.
In the video below, Dr. Jared Cooney Horvath compares two research papers examining the effects of the pandemic on student attainment — one which focused on standarized-test scores, and another which focused on grades.
While the former found that test scores dropped significantly during the pandemic, the latter showed that students’ grades actually improved through lockdown.
It’s a helpful reminder that not all metrics are created equally, and that data can easily be bent to the stories we wish to tell.
Watch the full video here. 👇
👹 Missing links
Like many people, I have an unhealthily needy relationship with my headphones. I almost never leave the house without them, terrified of the prospect of being alone with my thoughts. In this article, Ella Glover explains why she gave up her headphones for a month, and how the experience led her to see and hear beauty she would otherwise have tuned out.
🤖 Robots are suddenly getting cleverer. What’s changed?
In last week’s episode of the podcast, we all agreed that the disembodied voice of the Enterprise computer was closer to becoming a reality than Data, Starfleet’s intelligent android. While that’s undoubtedly true, major advances are quietly being made in the field of robotics, where multi-modal models are being used to help machines ‘understand’ the relationship between words and objects in physical space.
🖋️ Writer Math
I stumbled across this amusing piece by Elissa Bassist after reading Adam Grant’s Granted newsletter. It includes such relatable calculations as ‘“EOD” equals 5 p.m., 6 p.m., and 11:59 p.m., as well as 2 a.m., 8 a.m., 10 a.m., and 11 a.m. the next day.’ and ‘If you think a piece is 100 percent done, it’s actually 45 percent done. To get it to 100 percent done, you can’t.’. I feel very seen.
👋 And finally…
A reminder that language-learning can be complicated, culturally inflected, and hilarious:
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👍 Thanks!
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