The MFL AI Toolkit Just Got Better: New Models for Worksheet Authoring [August 2026]

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Local AI is getting better. The past few weeks saw the release of several compact but powerful LLMs that make a great fit for foreign language content authoring (think worksheets and reading texts, with an even lower overhead!).

I’m using LM Studio to run these for content projects – you’ll find them all as easy downloads in the models tab. Make sure you have a bit of disk space and a fast connection – they range from 8 to nearly 20GB in size – then download and start prompting!

  • Qwen3.8-27B — Alibaba / Qwen
    Released 13–14 August 2026 · Apache 2.0 · ~27.8B parameters

    The freshest of the bunch, and arguably the pick of the litter for MFL content work. It’s the direct successor to the community-favourite Qwen3.6-27B, but now natively multimodal (text, images and video), with a 262K-token context window that stretches to 1M — plenty of headroom for feeding it whole set texts or past papers and asking it to generate comprehension exercises around them. Qwen also ships adjustable “reasoning effort,” handy for dialling compute up for tricky grammar explanations and down for quick vocab drills.

  • Muse Glimmer — Meta
    Released 10 August 2026 · Apache 2.0 · 30B parameters

    Meta’s return to genuinely open weights, distilled down from their closed flagship Muse Spark 1.2. It’s pitched squarely at agentic, on-device workflows — think batch-generating worksheet sets, checking your own answer keys, or wiring up a local pipeline that self-corrects its output — and runs comfortably on a single consumer GPU or a beefy Mac. Covers 100+ languages, which is more than most of us need, but never hurts!

  • Bonsai 27B — PrismML
    Released 14 July 2026 · Apache 2.0 · 27.8B parameters (1-bit / ternary)

    Now this is at the extreme end of “small”, and it’s attempting something quite novel. It’s an ultra-low-bit compression of Qwen3.6-27B — down to 3.9GB in its 1-bit form — small enough to run on a many portable devices (although I’ve not tried it on PocketPal yet), and comfortably on a laptop with room to spare. Quality takes a modest hit versus full-precision Qwen3.6-27B (PrismML’s own figures put it around 90% retention at 1-bit, better at the ~7GB ternary setting), so it’s more “worksheets on the train” than “your main authoring model,” but as a proof that 27B-class output now fits in your pocket, it’s a fun one to have installed.

A slightly older model that’s worth a mention alongside these is Qwen3.6-35B-A3B, a very efficient mixture-of-experts model that nominally has 35B parameters but only about 3B are active at any one time via a clever routing trick. It’s noticeably faster than Qwen3.8-27B for similar output quality in my own testing, and it’s been my workhorse for some time. It’s worth keeping an eye out for a future MoE version of 3.8 built the same way — that could be genuinely excellent.

Why Small Models?

Using smaller models locally addresses many of the environmental and privacy concerns around AI use. All the prompt compute happens privately on your local machine — no student data, no draft worksheets, no half-finished reading texts ever leave your laptop. And despite the tiny footprint, they’re still excellent at producing native-quality text across dozens of languages, which was frankly unthinkable on consumer hardware even a year ago.

None of these is going to replace a careful human eye on the final worksheet — but as first drafts, distractor generation, or a quick “give me five more sentences at this CEFR level,” they’re genuinely useful additions to the toolkit. Worth an afternoon of poking around, at the very least.

More Greek fun on the socials

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Formative social media – that’s the kind we like! And I keep finding accounts that make me feel slightly better for all the minutes scrolling on Instagram.

Of course the algorithm helps – like one and it’ll funnel all of them to you sooner or later. But there are some really special ones that I’d add to the first raft of them that I compiled a while ago.

First off, Nefeli Abastado and team run the brilliant gr_language. It dives deeper than most Greek accounts by adding an etymological and cultural slant – you learn about the Hellenic world woven into the words.

Next we have Artemis, a Greek teacher from Crete, who runs the excellent Greek Talk Club channel. My favourite thing about it is the focus on the colloquial; snazzy infographics are a regular feature, teaching you how Greeks really speak.

Roula’s feed also aims to colour in the Greek history and culture behind the vocabulary. Recommended for any Greek learners who asks not just what, but: why?

Nostos Hub is a super follow too. It features a little more grammar than some of the others, with great, clear explanations of tricky words and phrases in the language. There’s still a healthy nod to Greek heritage throughout, though!

For sure there are more golden Greek feeds to find – let me know your own favourites in the comments!

Thanks, Glasgow 2026

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What a week and a half it’s been at the Glasgow 2026 Commonwealth Games!

As you’ll know, I’ve been an enthusiastic convert to – and massive advocate for – volunteering since Birmingham 2022. It’s such a fantastic way to give a little back and gain a real sense of community in return. And for language geeks, international events like the Commonwealth Games bring that wonderful world of diversity right to the doorstep.

It’s wise to expect the unexpected at these things, of course. I thought I might get the chance to say karibuni (welcome) in Swahili, or chat a little in French with francophone athletes in Glasgow.

But in fact, it was my tiny bit of Welsh that got an outing in and around the venues. Team Wales had a ton of supporters cheering the competitors on, so croeso! (welcome), diolch yn fawr (thanks a lot) and un… dau… tri… (one… two… three… – for taking group pics, of course) came in surprisingly handy! And isn’t it the best feeling when you say a few words and see those smiles of surprise in return? It makes all that dabbling worthwhile, even if you’ve learnt only a handful of words.

Gwen, the Welsh Dragon—possibly my favourite Games pin of all!

The other big language surprise came from among my fellow volunteers. Of all things, one of them spoke Norwegian fluently – cue a fun wee conversation on shift. And then there was the fab bus convo with two delegates who spotted me doing Duolingo: we ended up comparing notes on the languages we were learning.

That’s what happens when lots of lovely people come together for the big, lovely shindig that is volunteering. Like-minded souls, you might call us. Although everyone here has been equally lovely and also wonderfully different.

Glasgow 2026 has been an absolute ball. It’s made me want to keep spreading the word: if you get the chance, give event volunteering a go. It’ll open up your world!

Beyond the Novelty: The Sustained Impact of Song-Based Instruction in Language Learning

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Music in the language learning classroom is not a new concept, and there’s lots of anecdotal evidence for its positive effects. But  it’s also not the easiest thing to test empirically, as you can imagine. You might see a spike in interest briefly in class, but it’s harder to show concrete academic growth over time with something so subjective.

However, a robust quasi-experimental study published in Brain and Behavior provides a more rigorous look at the data. The researchers investigated both the immediate and sustained effects of song-based lessons, offering practical insights into how multimodal approaches function over time.

The Methodology

The researchers conducted an eleven-week study involving 200 elementary-level EFL learners. To ensure internal validity, intact classes were assigned to either a control or an experimental group:

  • The control group received traditional instruction aligned with their standard curriculum (I know, what a shame for them!)
  • The experimental group covered the exact same instructional objectives and content, but their lessons were integrated with age-appropriate English songs.

Data were collected at three distinct time points: a pretest, an immediate post-test, and a four-week follow-up assessment.

The Findings

The inclusion of the delayed follow-up measurement is where this study proves its worth, moving the conversation beyond short-term performance gains. The results demonstrated that the experimental group significantly outperformed the control group across three interconnected constructs:

  • Academic Development: Learners receiving song-based instruction showed enduring improvements in their core language skills, including vocabulary growth, comprehension, and linguistic accuracy. Crucially, these academic gains were largely maintained at the follow-up stage.
  • Cognitive Engagement: Rather than simply entertaining the students, the musical input facilitated sustained attention, mental effort, and active participation. This aligns with multimodal learning theory, which posits that integrating verbal and auditory channels can enhance attentional focus and memory formation.
  • Motivation for Learning: Grounded in Self-Determination Theory, the findings indicate that song-based activities effectively supported learners’ psychological needs for autonomy, competence, and relatedness. This resulted in higher intrinsic and extrinsic motivation, an effect that also remained stable at the four-week follow-up.

Practical Implications

The data present a clear, solutions-oriented takeaway for curriculum design. Song-based instruction functions as a highly effective pedagogical catalyst: it enhances motivation, which in turn increases cognitive engagement, ultimately driving sustained academic development. Perhaps it’s something many of us knew – instinctively!

And perhaps it’s a call to bring music more into the centre stage, rather than in a minor support role. Music can be relegated to the role of a peripheral, affective ‘ice-breaker’ in language learning. But when implemented systematically, emotionally engaging, multimodal input can produce long-term, solid language gains.

Happy Commonwealth Games 2026 – Enjoy The Languages, Glasgow!

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A busy one this week, as many of us in Scotland (and beyond) are preparing for the Commonwealth Games in Glasgow, either as volunteers or visitors. The 2026 edition of the games will be filling the city with sporting joy from 23rd July to 2nd August.

And there’s a language connection there, of course – I couldn’t hide my enthusiasm at that very fact when it was Birmingham’s turn to host the Games in 2022. A huge number of languages are spoken across the Commonwealth, with some countries hanging on to a staggering level of linguistic diversity. Nearly a thousand languages are spoken in Papua New Guinea. Nigeria has over 500. India with over 400, Australia breaking 200, and Cameroon at nearly 300 round off the medal table.

Some of those, of course, will be represented by athletes and spectators coming to Glasgow. It’s a lovely thought to think that the event might bring Arrernte, Hiri Motu or Fulfulde to the streets of the city.

As for me, I’m looking forward to a couple especially. There’s Greek, obviously, thanks to Cyprus. We should hear a fair bit of Swahili about, with visitors from Kenya, Rwanda, Tanzania and Uganda. And francophone countries are in the mix too, with Canada, Cameroon, Mauritius, Vanuatu, and of course, Rwanda again. I’m a little giddy at the thought of hearing Maltese, too – not one I’ve ever tried to learn, but I’ve had a vintage copy of Teach Yourself Maltese on my shelf for years that wants to persuade me otherwise!

And as well as all the Scots, of course, there’s a wee treat for Gaelic speakers and learners – BBC Alba are covering the games in the language.

If you’re in Glasgow, have fun listening out for those languages. And wherever you’re following the fun, have a wonderful Commonwealth Games 2026. Find out more at the official site!

Open Textbook : University-Grade Language Resources for Free

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You know I like a language freebie. And this week, I found out about a brilliant free resource from colleagues involved in the project. It’s called the Open Textbook Library, and it offers a practical, structured approach to sourcing course materials without the hefty price tag.

What Are Open Textbooks?

Open textbooks are complete, peer-reviewed academic books published under open licences. This means they are free to read, download, and adapt for your own teaching and learning. While the initiative initially aimed to address the high costs of higher education textbooks, it has grown into a comprehensive academic repository. The library also now features a dedicated UK & Ireland Collection, curated by university librarians.

The Language Learning Angle

For language learners, the library offers a solid, structured alternative to expensive commercial courses, with the reassurance that they’ve been put together by subject experts. The Languages section contains university-level course books for a variety of languages, ranging from French and Italian to Arabic and Chinese.

Many of these texts are designed around modern pedagogical frameworks and mirror the courses you’d actually follow if you enrolled at the university publishing them. To give a couple of concrete examples, you can find the highly thorough Spunti series for Italian (such as Spunti: Italiano Elementare 1), alongside structured introductory materials like the Linam German courses (including German 101). Texts frequently include multimedia links too, so you have listening covered with many of them.

Beyond Languages

Of course, we’re all about languages at Polyglossic. But the Open Textbook catalogue spans a huge range of academic disciplines. If your interests overlap with the social sciences, historical linguistics, or computer science, you will find rigorously reviewed texts available in those areas as well.

How to Access the Library

Accessing the materials is straightforward. You can browse by subject on the Open Textbook Library website and download the texts directly.

They are typically provided as PDF or EPUB files. This digital format is particularly useful if you prefer to keep your physical footprint small and travel light, allowing you to load an entire syllabus onto a single device. There are no subscriptions or ongoing fees to manage – just practical, open access to structured learning.

Finally, if you’re a course author yourself, maybe you’d consider contributing to Open Textbook too. It’s a wonderful initiative to democratise learning – and who doesn’t want to give a little back?

Snarky Marketing vs. Real Data: Duolingo Really Works!

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It’s become almost trendy to knock Duolingo in the last couple of years. In fact, positioning a new language learning product as the “anti-Duolingo” has become a fairly standard marketing tactic.

And while there are always reasons to debate a language learning method – no one approach is perfect in every way for every person – it’s good to know the difference between a social media pile-on and legitimate criticism.

A new paper has provided some more objective balance on that.

Published in Language Learning & Technology, a study by Smith, Jiang, and Peters (2024) took a rigorous look at how effective the app actually is for independent learners. Instead of just relying on anecdotal feelings, they measured outcomes across a comprehensive range of linguistic abilities. We’re talking both receptive skills (reading and listening) and productive skills (writing and speaking), alongside vocabulary, grammar, and pronunciation.

They tracked 48 independent learners tackling the Spanish course over a three-month period. The findings? After putting in an average of about 27 hours of study, participants showed significant improvement across all ability measures. A small sample, for sure, but 27 hours is remarkably low for meaningful gains – less than 15 minutes a day. For an app coming under flak for meaningless gamification, that is an excellent piece of defence.

When gamification earns its keep

Working in educational software development myself, I know how tricky it is to balance engaging user interfaces with genuine pedagogical value. It’s one thing to build a platform that people want to log into every day, but it’s another entirely to prove that it’s actually teaching them something substantive. This paper validates that the gamified approach, when engaged with consistently, really does translate into measurable linguistic gains. The researchers specifically noted that session completion, accuracy rate, and an overall positive user experience were directly linked to this observed growth.

This challenges one of the most common criticisms you hear: that apps like this only teach you how to pass their specific tests, or only build passive recognition. The fact that productive abilities like speaking and writing improved significantly is a huge win, as these are notoriously difficult to scaffold outside of a classroom or immersion environment.

Of course, this isn’t to say any app is a magic bullet. Twenty-seven hours of app time won’t instantly make you fluent enough to debate current affairs over a coffee. I’m a Duolingo user, and get frustration and satisfaction from it in, sometimes, equal amounts. It never hurts to spread your screen time over other language learning apps, either.

But as a tool for building a solid foundation and keeping learners consistently engaged with the target language, this fresh evidence is robust. It turns out that beneath the relentless notifications and leaderboard leagues, there is a some sound pedagogy at work.

The next time a social media ad pops up claiming they’ve “fixed everything the green owl gets wrong”, it might be worth taking it with a pinch of salt. Any tool that gets people to consistently show up, put the hours in, and tangibly improve is something worth celebrating!

The Perfection Trap: Why ‘Sounding Native’ Isn’t the Ultimate Accent Goal

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A paper appeared this month in Language Teaching that reminds us all – in the classroom and learning at home – that accent isn’t everything.

Is English pronunciation teaching in China ready for the Intelligibility Principle? (Xue & Wu, 2026) looks specifically at English language teaching in China, and the pressure that aspirations of nativeness can put on students. For a polyglot community focused on becoming the languages we learn, this seems very familiar. The pursuit of a flawless, native-like accent can often feel like the ultimate prize – anything less is an imperfect near miss. Whether you are tackling the phonology of German, Spanish, or diving into a new challenge like Bulgarian, it is easy to obsess over perfectly mirroring native audio.

However, the authors gently remind us that this pursuit can be entirely unnecessary.

Historically, language instruction has been dominated by this Nativeness Principle, which dictates that learners should attempt to sound as close to native speakers as possible. It’s a hangover from a quite Victorian perfectionism in learning – learn by rote, never forget.  Yet, absolute native-speaker norms are an unrealistic objective for many learners – especially older ones (as much as it stings to hear that pushing 50!).

Instead, a more practical framework is the Intelligibility Principle, which argues that the primary pedagogical goal should simply be mutual understanding.

Does This Matter for the Polyglot Community?

Absolutely. The pressure to achieve a flawless accent can actively hinder our progress. An overemphasis on native-speaker models can add to language anxiety and can decrease a learner’s willingness to communicate. Not surprisingly, many of us have an aversion to feeling a fool – it’s great to push back against that as a language learner, but it’s not always easy.

The reassuring truth is that speech can carry a heavy foreign accent and still remain highly intelligible to listeners, and therefore functional. A lot has been made of Zelenskyy’s excellent communicative skills despite a strong accent, for example. Furthermore, because English and many other languages act as global lingua francas, learners frequently communicate with other non-native speakers. Therefore, a native accent is neither necessary nor particularly beneficial for mutual understanding.

The goal isn’t to erase our linguistic identity, but to ensure our message is clearly received.

Practical Steps: What Should Independent Learners Focus On?

The paper is quite rich on practical suggestions in this regard. When you are building your corpus of vocabulary or grinding through daily flashcards, it helps to know exactly which phonetic features actually impact comprehension. Instead of trying to master every subtle nuance, prioritise the elements that carry the highest functional load:

  • Vowel accuracy: Both the length (quantity) of a vowel and the quality of the vowel play significant roles in whether a word is understood.
  • Consonant clarity: Avoiding the simplification of diphthongs and preventing the conflation of voiced and voiceless plosives are critical steps for maintaining clarity.
  • The bigger picture: Suprasegmental features, which include stress, rhythm, and intonation, have a remarkably strong influence on how a listener perceives an individual’s oral proficiency.

Tools and Tactics for the Daily Grind

As independent learners and language hobbyists, we have to direct our own study routines. Here is how we can implement an intelligibility-first approach:

  • Embrace accommodation strategies: In real-world conversations, mutual understanding is often achieved through spontaneous adjustments like simplification and paraphrasing.
  • Leverage technology: Computer-assisted pronunciation training and artificial intelligence-powered tools offer instant, data-driven feedback and personalised suggestions for self-monitoring.
  • Recognise algorithmic bias: If you are using—or even developing—language learning apps, it is important to remember that commercial automatic speech recognition systems frequently exhibit bias, showing significantly higher error rates for non-native accents.

Ultimately, dropping the demand for native-like perfection takes a massive weight off the language learner’s shoulders. By focusing on practical intelligibility, clear suprasegmentals, and flexible communication strategies, we can speak our target languages with far more confidence and far less anxiety.

Have you evolved from learner perfectionism to more intelligibility-based goals yourself? Was it hard to let go, or did you feel a sense of relief at letting go? Let us know in the comments!

One Bag to Rule Them All : A Week in Milan with Barely Anything

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I’ve been doing a bit of one bag travel this week. I spent six days in lovely, sunny Milan for a conference. And I challenged myself to take as little as I possibly could.

What does one bag travel have to do with language learning and linguistics, you might ask? Well, at its heart it shares the same ‘open world’ philosophy that prompts many of us to go the way of the words. To those who wonder what’s out there, and want to head out and experience it for themselves, the thought of chucking a few essentials in a bag and jetting off is irresistible.

It’s always fascinated me. In fact, one of my earliest blog projects was a Geocities (remember that?) self-host called One Bag Traveller. Goodness knows what happened to that. But it doesn’t matter – social media has since filled the void, and there are some very cosy corners for fellow one-baggers to gather and optimise together.

r/onebag is the place to start. One of my favourite trends here is “contents of my bag” pics – users lay out their packing and invite optimisation feedback and tweak suggestions. If you like what you see there, then check out r/zerobags too, which is “boss level” light travel. Can’t say I’m quite there yet, but I still learn plenty of “get by with less” tips from it!

What’s in my one bag?

So what did I take in my Milan conference bag? Well, as any one bag veteran knows, it starts with the bag itself. For this trip I was trying out a new one, one of those increasingly ubiquitous “cabin max” types that are perfectly sized for under-the-seat stowing, even with the most draconian airlines. This was probably bigger than I needed, to be fair, but it was light, and there was room for the inevitable conference goodies.

In there, I had:

  • iPad + Apple Pencil (had a laptop-less week, which helped)
  • Charger, cable, adapter
  • Passport

 

  • 2 smart shirts
  • Smart(ish) shorts
  • 2 white cotton tees
  • 1 merino tee
  • 3 x socks and undies

 

  • Tote bag (easier than using big bag for daily to-and-fro)
  • Toiletries
  • Travel laundry detergent

That last bit is the clincher. I did a couple of small laundry washes during the week, making the most of the few clothes I’d taken. I got three wears out of one shirt (and I promise, it was fresh as a daisy every time!). Soak, pummel, rinse, ring, dry. In a warm place like an Italian hotel room, items were ready to wear again in a matter of hours. Choosing quick-dry garments is a good tried-and-tested tip, too (Uniqlo’s AIRism range is great).

What also helps is planning what you wear there – cargo chinos have pockets you can pop extra items into, for example. A good light shacket can help, too.

One bag, lots of freedom

Taking less on the road gives you such a sense of freedom and even resilience – your bag is so light that you can cope with any bump in the road without a dead weight bogging you down. It really is liberating. I’ll continue the tweaking and geeking – and who knows, I might even give zero bagging a shot one day!

Are you a fellow one bag traveller? What’s your number one tip for lightening the load? Or, if you’re sceptical, what’s holding you back from leaving the suitcase at home? Let us know in the comments!

Ethical AI : Give Your Local Models a Window on the World

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AI has become one of the most divisive and controversial emerging tech developments of our age. And not without reason – its impacts on the environment and on society are hotly debated and still not completely understood.

It’s one of the reasons that ethical AI is such a promising field right now. Using free tools on any medium-specced machine, you can beef up your workflows without burdening data centres in exchange for your privacy.

Perhaps you too are already using local LLMs as a more environmentally responsible content aid. They’re a great choice for assisting in activity creation in “mainstream” languages; the latest small models can comfortably match the output of the online beasts like Claude and ChatGPT.

But you may have already run up against the “black box” limitation. Out of the box, locally run LLMs have only their own resources, and no connection to the outside world for retrieving up-to-date info or fact-checking.

Tooling AI

There is a solution – and if you’re running models in LM Studio, it’s pretty easy to implement. A number of tools, or plug-ins, are available to extend the capabilities of your models. They range from simple everyday functions like a current date check, to internet searching and even file system access. When browsing models in LM Studio, tags indicate which are ready for tool use – which, in practice, is nearly all recent releases.

One word of caution – it’s important to take some care in selecting and installing tools. Community users are generally the tool developers, rather than the LLM providers. As such, you should always do due diligence and check sources before installing them. Building these assumptions into practice has been a baptism of fire for users at the bleeding edge of AI – you may well have come across recent stories about insecurities in certain third-party tools for the ‘agentic’ system, OpenClaw.

That said, LM Studio hosts a library of third-party tools on its website that should have passed community checks. These include a Wikipedia search, which instantly gives your queries a fact-checking foundation (allowing for the occasional Wikipedia factual error or two!). If that’s not enough, then there’s that full web search tool too. To use this, you need to set up a search provider – the free and ethical SearXNG is recommended, and it’s worth the fiddling around to set it up. (Again, exercise plenty of care when allowing your local models to consume external data.)

And back to that prosaic old date check – it’s actually more useful than you might at first think. As LLMs are trained on static text data, they have a memory cut-off. There’s generally an ‘awareness’ of this (insofar as we can call it that). Try, for instance, asking a local model what was in the news yesterday. It might well respond by stating its knowledge cut-off date (if it doesn’t make something up). Install a date checker and you add a corrective to this behaviour. That web search is much more effective if a model ‘knows’ when now is.

New tools are being developed all the time, bringing local model use even closer in line with online AI portals. For many, that’s a big step closer to becoming a viable, ethical replacement for them. Explore, experiment and share – I’d love to know what other tools you’ve found useful in the comments!