Learning new information in L2 is more effortful than in L1. We found different functional connectivity networks of naturalistic learning through speech among adolescents, confirming this prevalent observation
Does learning language require effort? Does it require more effort when learning a new language later in our lives? Why?
Today, we will highlight a study that shows the additional neurological networks that adolescents activate when learning in a second language – a key insight for all educators to consider.
Language Learning: Effortless for Babies, Effortful for Adults
Babies learn language with such ease that they have already begun to recognize the unique patterns of a language–even to distinguish between the unique patterns of multiple languages–while still in the womb.
We therefore tend to assume there is something wholly innate or natural to learning language.
Yet as we’ve explored previously in a series on this blog, even learning our first languages may not be as innate or natural as it can appear. Human language reflects a unique synchrony between our biological and cultural evolution, finely attuned to the social environment in which we interact.
When I typically begin a series of blogs to conduct nerdy inquiry into an abstract topic, I don't generally know where I'm going to end up. This series on LLMs was unusual in that in our first post, I outlined pretty much the exact topics I would go on to cover.
Here's where I had spitballed we might go:
The surprisingly inseparable interconnection between form and meaning
Blundering our way to computational precision through human communication; Or, the generative tension between regularity and randomness
The human (and now, machine) capacity for learning and using language may simply be a matter of scale
Is language as separable from thought (and, for that matter, from the world) as Cormac McCarthy said?
Implicit vs. explicit learning of language and literacy
Indeed, we then went on to explore each of these areas, in that order. Cool!
In a previous series, “Innate vs. Developed,” we’ve also challenged the idea that language is entirely hardwired in our brains, highlighting the tension between our more recent linguistic innovations and our more ancient brain structures. Cormac McCarthy, the famed author of some of the most powerful literature ever written, did some fascinating pontificating on this very issue.
In this post, we’ll continue picking away at these tensions, considering implications for AI and LLMs.
“Over cultural evolution, the human species was so pressured for increased information capacity that they invented writing, a revolutionary leap forward in the development of our species that enables information capacity to be externalized, frees up internal processing and affords the development of more complex concepts. In other words, writing enabled humans to think more abstractly and logically by increasing information capacity. Today, humans have gone to even greater lengths: the Internet, computers and smartphones are testaments to the substantial pressure humans currently face — and probably faced in the past — to increase information capacity.”
According to the perspectives of the authors in the paper quoted above, the capacity to process and manage vast quantities of information is a defining characteristic of human intelligence. This ability has been extended over time through the development of tools and techniques for externalizing information, such as via language, writing, and digital technology. These advancements have, in turn, allowed for increasingly abstract and complex thought and technologies.
The paper by Jessica Cantlon & Steven Piantadosi further proposes that the power of scaling is what lies behind human intelligence, and that this power of scaling is what further lies behind the remarkable results achieved by artificial neural networks in areas such as speech recognition, LLMs, and computer vision, and that these accomplishments have not been achieved through specialized representations and domain-specific development, but rather through the use of simpler techniques combined with increased computational power and data capacity.
Regularity and irregularity. Decodable and tricky words. Learnability and surprisal. Predictability and randomness. Low entropy and high entropy.
Why do such tensions exist in human language? And in our AI tools developed to both create code and use natural language, how can the precision required for computation co-exist alongside this necessary complexity and messiness of our human language?
”. . . the fact, as suggested by these findings, that semantic properties can be extracted from the formal manipulation of pure syntactic properties – that meaning can emerge from pure form – is undoubtedly one of the most stimulating ideas of our time.”
In our last post, we began exploring what Large Language Models (LLMs) and their uncanny abilities might tell us about language itself. I posited that the power of LLMs stems from the statistical nature of language.
In a previous post, Thinking Inside and Outside of Language, we channelled Cormac McCarthy and explored the tension between language and cognition. We dug in even further and considered Plato's long ago fears of the deceptive and distancing power of written language in Speaking Ourselves into Being and Others into Silence: The Power of Language, and how bringing a critical consciousness to our use of language could temper unconscious biases and power dynamics.
If you find any of that interesting, I recommend reading this short interview, How to Quiet Your Mind Chatter in Nautilus Magazine with Ethan Kross, an experimental psychologist and neuroscientist at the University of Michigan.
Two relevant quotes:
“What we’ve learned is that language provides us with a tool for coaching ourselves through our problems like we were talking to another person. It involves using your name and other non-first person pronouns, like “you” or “he” or “she.” That’s distanced self-talk.”
“The message behind mindfulness is sometimes taken too far in the sense of 'you should always be in the moment.' The human mind didn’t evolve to always be in the moment, and we can derive enormous benefit from traveling in time, thinking about the past and future.”
This has been a great year for education research. I thought it could be fun to review some of what has come across my own limited radar over the course of 2023.
The method I used to create this wrap-up was to go back through my Twitter timeline starting in January, and pull all research related tweets into a doc. I then began sorting those by theme and ended up with several high-level buckets, with further sub-themes within and across those buckets. Note that I didn’t also go through my Mastodon nor Bluesky feeds, as this was time-consuming enough!
The rough big ticket research items I ended up with were:
Multilinguals and multilingualism
Reading
Morphology
The influence of physical or cultural environment
The content of teaching and learning
The precedence of academic skills over soft skills
We have spent some time picking away at the tension between the generalizations and assumptions made around whether reading and writing development is natural or unnatural.
We continue this exploration, except now we dig into an even more fundamental aspect of human development: language. Language development is a seemingly magical evolutionary development that humans have uniquely adapted—or for which language is uniquely adapted for—to the surviving and thriving of our species.
Are we born with innate capacities for language baked into our brains—a 'universal grammar'? Or do we develop and hone these capacities—albeit, rapidly—through exposure and use? Is it both? If so, how much is innate, and how much is developed? And in what way do these continued advancements of language and literacy across the generations enable our cognitive, cultural, and technological achievements? And in what way might they at the same time magnify the biases and base motivations of those most able to leverage power to manipulate others? In other words, how much does language and literacy bring us into a more generative engagement with ourselves and our world, and how much does it create a distance that may lead to destruction?
Talking is just recording what you're thinking. It's not the thing itself. When I'm talking to you some separate part of my mind is composing what I'm about to say. But it's not yet in the form of words. So what is it in the form of? There's certainly no sense of some homunculus whispering to us the words we're about to say. Aside from raising the spectre of an infinite regress—as in who is whispering to the whisperer—it raises the question of a language of thought. Part of the general puzzle of how we get from the mind to the world. A hundred billion synaptic events clicking away in the dark like blind ladies at their knitting.
–Stella Maris by Cormac McCarthy
OK, so let’s take some stock of where we’ve been thus far in our explorations of the development of language and literacy.
We’ve spent some time poking at the notion of whether learning to read is unnatural or not, and landed on the conviction that terming it unnatural–though useful as a rhetorical device–may be less precise than recognizing that learning to read and write is more formal, abstract, and distal from the immediate context of human interaction – and thus requires more effort, instruction, and practice to master.
We then turned to the development of language and discovered that even here–despite the ubiquity and swiftness with which native languages develop anew in every child across our species–language may not be as innate and inborn as it may appear.
Both language and literacy have bestowed humanity with sacred powers for the transmission and accumulation of cultural knowledge that seems to–as of yet–have no ceiling beyond that of our own destruction. Whether this is natural or innate or not may be beside the point. What does seem to be clear is that we have something inherited within us that is unfurled and reified by the networks that are riven across our brains through storytelling, interactive dialogue, and shared book reading that connects spoken to written language, and further strengthened with the hardwon fluency we manage to achieve on our own across modalities, texts, and languages.
When I typically begin a series of blogs to conduct nerdy inquiry into an abstract topic, I don't generally know where I'm going to end up. This series on LLMs was unusual in that in 
In 
This has been a great year for education research. I thought it could be fun to review some of what has come across my own limited radar over the course of 2023.
