While my bandwidth to peruse research has diminished this year (work has been busy, and I like spending time with my children) I have still encountered a fair number of compelling studies. In keeping with the tradition begun in 2023, and building on last year’s review, I am endeavoring to round up the research that has crossed my radar over the last 12 months.
This year presents a difficult juncture for research. Political aggression against academic institutions, the immigrants who power their PhD programs, and the federal contracts essential to their survival has disrupted research. Despite this, strong research continues to be published. Because research is a slow-moving endeavor, I suspect the full effects of these disruptions will manifest increasingly in future roundups; for now, the good work persists.
The research landscape of 2025 highlights a continued shift toward experience-dependent plasticity. This view treats the human mind as a dynamic ecosystem shaped by biological rhythms, cultural “software,” and technological catalysts. Learning is no longer seen as a linear accumulation of skills, but as a sophisticated orchestration of “statistical” internal models and external social and cultural and technological attunements.
Longtime readers will recognize this “ecosystem” view from my other blog on Schools as Ecosystems. It is validating to see the field increasingly adopting this ecological lens—viewing the learner not as an isolated machine, but as an organism deeply embedded in a biological and cultural context.
Our “big buckets” for this year have ended up mirroring the 2024 roundup, which means, methinks, that we have settled upon a perennial organizational structure:
The Science of Reading and Writing
Content Knowledge as an Anchor to Literacy
Studies on Language Development
Multilinguals and Multilingualism
Rhythm, Attention, and Memory
School, Social-Emotional, and Contextual Effects
The Frontier of Artificial Intelligence and Neural Modeling
Language is the everpresent medium of teaching and learning, the element that infuses every classroom interaction. Yet, how often do we explicitly plan the content, structure, and quality of this critical element?
While we meticulously map out and prepare for the activities we engage our students in, the specific linguistic structures and vocabulary we employ often remains implicit, almost accidental. This raises critical questions: which aspects of our classroom talk truly accelerate literacy – is it sheer volume, vocabulary precision, or syntactic complexity? And how can we become more deliberate and intentional architects of this vital linguistic environment for all students, including those developing multi-dialectalism and multilingualism?
My recent presentation at ResearchED in NYC ventured into this territory, examining the research on how the linguistic environment we curate can influence student literacy achievement.
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.
“Semantic gradients,” are a tool used by teachers to broaden and deepen students' understanding of related words by plotting them in relation to one another. They often begin with antonyms at each end of the continuum. Here are two basic examples:
Now imagine taking this approach and quantifying the relationships between words by adding numbers to the line graph. Now imagine adding another axis to this graph, so that words are plotted in a three dimensional space in their relationships. Then add another dimension, and another . . . heck, make it tens of thousands more dimensions, relating all the words available in your lexicon across a high dimensional space. . .
. . . and you may begin to envision one of the fundamental powers of Large Language Models (LLMs).
Paper Citation: Philip Capin, Sharon Vaughn, Joseph E. Miller, Jeremy Miciak, Anna-Mari Fall, Greg Roberts, Eunsoo Cho, Amy E. Barth, Paul K. Steinle & Jack M. Fletcher (2023) Investigating the Reading Profiles of Middle School Emergent Bilinguals with Significant Reading Comprehension Difficulties, Scientific Studies of Reading, DOI: 10.1080/10888438.2023.2254871
A few months ago, a study crossed my radar that caused me to stop, print it out, mark it up, and then begin digging into related studies, which is what I do when a study grabs my attention.
Getting into research is akin to getting into Miles Davis—if you like a given song or album, you may start checking out the other musicians he plays with, and they'll lead you into a new and ever expanding fractal universe, because Davis had a knack for collaborating with musicians who were geniuses in their own right. A few examples: John Coltrane, Tony Williams, Keith Jarrett, Herbie Hancock, John McLaughlin, Wayne Shorter, Jack DeJohnette, the list goes on and on.
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 know that the explicit teaching of unfamiliar words that students will encounter in written text is important. But what about the language that is used by teachers throughout the school day? What implicit learning opportunities are constrained or afforded through the model of the language that a teacher uses while teaching, and what are the impacts on student learning?
I'm going to try out a new type of post here, in which I'll share one interesting research item I've happened across in greater depth. In the past, I've simply tweeted them out, but then I forget about them. I'm hoping this will be a better way of retaining them in memory and deepening my understanding — and of course, sharing them with you!
Individual differences in L2 listening proficiency revisited: Roles of form, meaning, and use aspects of phonological vocabulary knowledge
Citation: Saito, K., Uchihara, T., Takizawa, K., & Suzukida, Y. (2023). Individual differences in L2 listening proficiency revisited: Roles of form, meaning, and use aspects of phonological vocabulary knowledge. Studies in Second Language Acquisition, 1-27. doi:10.1017/S027226312300044X
This paper explores how various aspects of phonological vocabulary knowledge affect second language (L2) listening proficiency. The study involved 126 Japanese learners of English.
Back in 1978, Bloom & Lahey presented a simple and useful model of language: form, meaning, and use.
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.
