Macmillan’s “Mastering” Series: Language Learning Stalwarts of the 80s and 90s

Leave a comment

You might remember that I was reminiscing about the forgotten Made Simple series the other week. It led me to recall another language learning series of old, and one I often mix up with Made Simple, I must admit. It’s Macmillan’s Mastering … series, another once much more familiar name in the self-paced and further ed market.

It’s not surprising that they sometimes merge into Made Simple in my language book memory. The book format itself was similar – a somewhat taller paperback, with that thick, off-white paper that feels really satisfying to turn (and crease, for fellow page corner turner-downers like me). Even the covers features that black, yellow and red of their Made Simple cousins. Like those books, these feel like grown-up courses, and, were likewise staples at night classes in the 80s and 90s.

The Mastering library overlapped with Made Simple in topics, but with a couple of important differences. For one thing, the series contained an intermediate stage for the mainstream languages; Mastering German 2, for example, is a very decent second-tier course that picks up where the first leaves off.

Impression of Mastering French I (Macmillan)

Mastering … take a slightly broader path with its titles, too. Mastering Arabic, for example, is one of the few really accessible, off-the-shelf courses in the language from the time. Perhaps that’s the reason it’s one of the titles that’s still very much with us; now acquired by Bloomsbury, Mastering Arabic continues as a respected and well-used course book today.

That’s not to say the old ones aren’t worth a look, too. And you can often pick them up on eBay for just a couple of pounds – you know we like a bargain at Polyglossic!

AI Role-Plays that Actually Move the Needle

Leave a comment

Papers on AI in education are two a penny at the moment, but there’s a particularly nice one that appeared recently in Frontiers in Education (30 Sept 2025). It takes a fresh look at AI-generated, scenario-based conversation practice for university EFL learners – one of perhaps the most obvious and widespread use cases for AI in language learning, but given a smart, systematic treatment by a team of scholars from Saudi Arabia, China and Pakistan.

The gist is simple: build realistic speaking scenarios with AI, let students interact in them over a term, and see what happens. Over 18 weeks with 130 first-years split into control vs. AI-scenario groups, the AI cohort came out ahead on pronunciation, accuracy and conversational flow. They also reported higher interest and better teacher–student interaction to boot.

The catch? Emotional thinness in AI dialogue, patchy content quality if you don’t curate, and a risk of learner over-dependence on the tech. 

So, what can we pinch for our own learning? Well, the paper itself is full of useful nuggets and worth a careful read. But here are some key takeaways for avoiding “AI for AI’s sake” based on the team’s findings.

1) Make your speaking tasks scenario-first, not tool-first.

Before opening any chatbot, sketch a brief: Where am I? Who am I? What’s my goal? What counts as success? That mirrors the paper’s “input → interaction → output” design and stops generative models meandering (always an occupational hazard worth mitigating against).

2) Bake in “flow nudges”.

The study’s gains in conversational flow suggest prompts that push you to repair, clarify and keep turns moving. Add rules to your prompt like: “If I give a short answer, ask a natural follow-up; if I stall, offer two options.” That keeps the exchange discursive rather than Q&A-ish. 

3) Add in a feedback micro-loop.

The report notes improvements in pronunciation, which is fine if you’re using AI in voice mode. If not, replicate that with a regular mini-feedback cycle that gives short explanations for tricky words of phrases.

4) Curate, don’t just generate.

A recurring warning was inconsistent or culturally off-kilter content when left unchecked. Make sure to describe your scenario frames in terms of function, time and place (e.g., returning a faulty purchase in Athens; arranging a GP appointment in Lille). 

5) Add a human(-like) layer to keep things warm

Students benefitted from richer teacher–student interaction around the AI tasks. Translate that to solo study by doing a quick human check: post one 60-second recap to a study buddy, social feed or tutor each week. This ‘social accountability’ step compensates for the AI’s limited emotional range. Try recording the dialogue afterwards as a voice note, too, for some added spoken practice.

6) Watch the dependence trap.

The authors flag tech over-reliance. Give yourself “AI-off Fridays”: repeat a scenario from memory with real materials (voice notes, a friend, or even talking to your phone camera), then compare to your AI-assisted version for gaps. 

AI in Practice

Bringing all that together, here’s a ready-to-use mini-format you can try for a 15-minutes role-play practice that isn’t crow-baring AI in for no real gain:

  • Minute 0–2: Choose a vetted scenario card (place, role, goal, 3 key phrases).

  • 2–3: Prime the bot with constraints (stay in A2/B1, insist on follow-ups, correct only one thing per turn).

  • 3–10: Converse. Every third turn, ask for a meaning / explanatory nudge on one tricky word or structure.

  • 10–12: Bot summary with 3 personalised upgrade lines you could have said.

  • 12–15: Record a no-AI voice note version. Park it for a weekly human warm-layer check.

Pastable Prompt

You are a language conversation partner tasked with improving the language skills of me, the user.
We’ll do a short scenario-based speaking practice in French.
Follow these rules carefully:
1. Keep the level at A2–B1 CEFR.
2. Always stay in character and make the conversation feel natural – imagine we’re really there.
3. Insist on follow-up questions whenever my answers are too short or unnatural.
4. Correct only one thing per turn, briefly and gently, then move on.
5. Every third turn, give me a short “💡 Language note” explaining a tricky word or structure that came up.
6. After about 20 lines or so of dialogue (ideally when the conversation draws to a natural close), give a performance summary, including what I did well, some ‘upgraded’ versions of my sentences showing how I could sound more natural or advanced, and 2-3 new phrases worth learning from this conversation.
7. Keep the tone friendly, realistic, and mildly humorous if it fits the setting. When ready, start the conversation by greeting me in the target language and setting the scene.

The bottom line is that AI role-plays can be genuinely useful when we design around them: scenario first, small feedback loops, and human warmth stitched back in. Treat the model like a scene partner with good timing but flat affect, and you’ll harvest the fluency gains without outsourcing your judgement.

The paper’s results are encouraging; its realistic caveats are a gift that ground us back in practical realism. As always, build guardrails into your AI usage first of all, to ensure that you get the most from – and enjoy – the chat! 

Perplexity Tasks for Language Learners

Leave a comment

AI techniques to support language learning are pretty well-known now. From structured conversation partners to resource creators, LLM platforms have been embraced by the polyglot community.

Like many of us, I dip in and out of them almost unthinkingly now. Often, I’ll snap in a page from a chapter I’m working on with my Greek teacher, and it’ll help me prepare ahead of a lesson. Sometimes, I’ll get it to reel off a list of useful phrases on a topic I’m studying. LLMs can make great worksheet creators, too. In many ways, it’s simply a very interactive reference tool, giving (mostly) reliable answers but with a big nod to context.

I’d been pretty dogged in my choice of platform, sticking for the most part with ChatGPT Plus. Claude and Gemini were also in the mix, alongside some fun running local models. But for the most part, I thought my tool choices were pretty settled.

But then I gave Perplexity a whirl.

Perplexity – Task Master

Perplexity isn’t an LLM in the sense that ChatGPT, Gemini and Claude are. It uses LLM technology. But it’s actually more of an intelligent, context-sensitive search tool, that uses natural language APIs to turbo-boost its web-hunting activities.

I’d clearly not found that prospect very exciting, as I’d not gone near it until now. But thanks to a bundled free upgrade, I got to try the premium tier of late. And one particular feature stands out as potentially transformative for my learning habits: Perplexity Tasks.

Tasks are scheduled searches you set up with natural language instructions. And those instructions can be as rich as your usual LLM prompts in terms of requested formatting and such like, so in essence, you can build regular bulletins with up-to-date information in any language you like. Take one of mine, that runs daily:

Search the global news for the biggest world news story of the day. Summarise it in French, German, Modern Greek, Polish, Scottish Gaelic and Swahili at a level appropriate for an intermediate learner, ensuring that the translation is of the highest, native speaker standard quality, idiomatic and natural-sounding. Summaries should be 3-4 sentences long. Highlight key words in bold.

Accompany each summary text with a glossary / vocabulary list detailing all the key / difficult words from it in dictionary format (listing word class, irregular parts if applicable etc.). Hyperlink glossary items to Wiktionary entries where available with further information on them (use the English version en.wiktionary.com).

Lay it all out neatly to make it easy on the eye. Use plenty of emojis for impact too. Make this a fabulous resource for polyglot language learning! 🌍

Now, every morning, I get a wee news digest emailed straight to my inbox in multiple languages. It’s learner-friendly, includes vocab support, and gives me something to talk about in my language meets and lessons. I’ve done the same for academic paper searches in linguistics, and stories on dialect appearing in news outlets.

It feels like a proper game changer!

Tasking on Other Platforms

Now, you don’t need Perplexity to do this – it’s just one of the most user-friendly ways I’ve found to do it. If you have ChatGPT,  check out Scheduled Tasks. In Gemini, Scheduled Actions will do the trick for Pro members. Copilot is in on the game too. Others will no doubt follow suit shortly – clearly, task scheduling is becoming one of those features AI platforms are expected to have.

What I like about Perplexity, though, is that its whole raison d’être is the search – it feels particularly suited to web-based tasks like news digests. It’s also quite nice to keep the separation between my everyday LLM ramblings, and my more structured, scheduled items (use it for a few weeks and you’ll have clogged your timeline up with dozens of chats!).

If you’ve been looking for a way to make AI genuinely work for your learning rather than distract from it, try setting up a task or two – you might just find it becomes part of your morning ritual as well.

The Made Simple Series : Language Learning Blasts from the Past

Leave a comment

While helping my uncle clear out some old boxes lately, I came across a proper forgotten classic of language learning: the Made Simple series.

I knew it as soon as I spied the familiar black, red and yellow paperback – it was an early nineties edition of Spanish Made Simple, chunky, well-worn, and still with my teenage pencil notes in it. I’d passed it on to my globetrotting uncle ahead of a trip he made to South America, so it had done some serious miles.

Spanish Made Simple, Third Edition - cover impression

Made Simple was a series familiar to many who took evening classes back then. And with its slightly polytechnic-esque look and feel, it sat naturally alongside Teach Yourself, Colloquial, Hugo In Three Months and language course stalwarts, keeping up but not quite displacing them. They covered the usual mainstream languages – French, German and Spanish – but also featured other self-teach titles from Electronics to Philosophy. 

And they feel solid, with a no-fluff, down-to-brass-tacks grammar-vocab-reading model. There’s a real ‘adult ed’ feel to them, which is probably why I loved them as a language-obsessed teen. They just felt grown-up.

Made Simple… Made Disappear?

Despite the Spanish edition making it to 2.5 million copies in print, the series never held the primacy that rivals like Teach Yourself and Colloquial hung onto. Other series expanded into more languages, for example, and shifting formats – especially the rise of audio media – made keeping courses like these a real specialist undertaking. In fact, they did manage to cling on in a modern incarnation by Penguin Random House, with fresh, up-to-date jackets. But those original, ubiquitous Made Simple language titles drifted into obscurity, and you’ll only spot their tricolore jackets on the shelves of second-hand booksellers these days.

That said, being obscure and forgotten doesn’t mean being obsolete. You will know, by now, my take on old language learning gems! For those of us who cut our language learning teeth before apps and streaks, they’re a charming reminder that all you really need is a pencil, a bit of patience, and a good old-fashioned tome.

So with that, consider the original Made Simple series unearthed and celebrated once again in this post. If you’re hankering after a new angle on your language, those old Made Simple volumes are still well worth a look!

My Teach Yourself Dabbling Shelf

The Great Teach Yourself Refresh

Leave a comment

I don’t know if you clocked it as well, but my favourite blasts-from-the-past Teach Yourself have gone and given their flagship language books a bit of a refresh.

Teach Yourself is a language learning brand with a huge heritage. If you want to track how language tuition has changed (and stayed the same!), then vintage editions are a great place to start. For nigh on a century they’ve been the cornerstone of the self-teach market, appearing in 1938 and quickly establishing itself as the brand for curious minds – not least those interested in foreign languages.

Teach Yourself advert in The Bookseller, 1959

Teach Yourself advert in The Bookseller, 1959

From quite traditional grammar-based handbooks, there was a noticeable turn towards a more communicative approach in the 80s, which kept them relevant right into the current era. That’s not to say there’s not life in those old versions – I personally love the chalk ‘n’ talk grammar translation method (although it has a time and a place!).

My Teach Yourself Dabbling Shelf

Some of my vintage Teach Yourselves!

In any case, they’ve seen fit to give their mainstream offering a revamp this year – and of course that means I’m going to have to get them to keep my collection complete. French, German, Italian and Spanish appear in smart, significant rewrites, all for release later this month. Not only that, but the Teach Yourself Beginners series for entry-level language has had a makeover, with titles ranging from Greek to Korean and Portuguese – and most of them are already available for purchase.

It’s a move that keeps the brand up-to-date, and still competitively priced, too – they compare very favourably with other popular course names. Well worth a look if you’re in the market for a new language – or just want to add them to your collection, like I do!

Image showing lots of document icons for a post on building a Zotero and Obsidian workflow

Zotero and Obsidian : A Workflow to Research Anything

Leave a comment

If much of your study is electronic – e-books, PDF papers, worksheets and the like – you’ll face the same struggle I have: digital overwhelm. A clear workflow for dealing with mounds of virtual material is essential if you’re not to get lost.

I feel like I’ve tried them all, too. I’ve gone through the gamut of e-readers: GoodReader, PDF Expert, even trusty old Apple Preview (which has great annotation features). All very decent in their own way. On the file system side of things, though, it’s another story. I’ve cobbled together some sort of ‘folders on the Cloud’ system over the years, but it’s seriously creaky. I break my own rules half the time!

Bearing that in mind, I was chuffed to bits to chance upon a whole new system recently – one that’s passed me by completely. It seems to be a particularly big hit across North American universities. It also has a large, active community online, sharing performance tweaks. And best of all – it uses completely free software.

Zotero and Obsidian

Zotero is a publications manager that you simply drag your e-material into. The app retrieves bibliographical information, renames files sensibly and stores a copy online for working cross-device. Even better, it’s capable of generating full bibliographies, so is a file store, reader and referencing tool all in one.

Obsidian is the note-taking side of this – a sleek, markdown-driven text editor that is beautifully minimalistic. It excels in creating hyperlinked notes, allowing you to build your own Wiki-style knowledge bank. But it dovetails beautifully into Zotero thanks to community plugins that allow you to import your PDF annotations directly into bibliographically pigeon-holed notes.

After resisting the temptation to kick myself for not spotting it sooner, I did a deep-dive into Zotero + Obsidian workflow how-tos, and it’s an academic revelation. A couple of community content creators are real stand-outs here – so much so that it’s best I let them do the talking rather than waffle any more. I’m learning this as I go along, and these are great places to start.

Workflow Training

Here’s where I started, more by chance YouTube search than anything else. Girl in Blue Music namechecks a lot of the other big Z+O content creators here, so it’s a good jumping point for newcomers.

From there, it’s worth exploring morganeua‘s vast selection of content, including numerous how-to videos and worked examples.

Once you’ve worked through those, you can graduate to full geek mode! Bryan Jenks pushes the system well beyond anything else I’ve seen, and likewise has a huge back catalogue of training vids. He layers styling and advanced templating onto the base, making for a slick, colour-coded, optimally managed research system.

I feel very late indeed to this workflow party. But if you are too, join the club – and let me know if you’ve found this useful too!

The Norwegian flag - the flag of Norway

#TikTokNorge – TikTok for Norwegian learners

Leave a comment

We’re slaves to the algorithm…. or are we? The great thing about TikTok is that you can engineer that algorithm with a bit of persistence. A search here, a like there, a comment somewhere else, and you subtly shift your TikTok-verse.

Of late, I’ve been nudging my own towards  serving up content that makes my aimless swiping a bit less aimless and a bit more, well, educational. And there’s a lot going on in #TikTokNorge! Mini lessons, everyday life, sketches and gags… Norwegian is well-covered on the platform – if you can uncover it first to coax onto your For You tab.

Here are some of the accounts helping me maintain and improve my own Norwegian lately – I hope you find a couple of gems in here too.

Norsk med Aria

Aria is a Norwegian teacher with a wealth of micro-lesson content on his feed, which he updates regularly. His videos are slick and well-edited, with a good balance between formal grammar tips and colloquial usage. He uses English as a presentation language, so it’s all accessible, too – a great place to start as a newcomer, as well as great revision and tips for more intermediate learners.

@norsk.med.aria

Ordering a coffee in Norwegian #norwegian #norsk

♬ original sound – Norsk med Aria – Norsk med Aria

Hilde Elise

Hilde Elise is an online Norwegian teacher who posts very regular monologues about life in Norway. She covers a huge range of topics from work and family to politics and current affairs, all at a level around A2-B1. This is delivered in clear, measured Bokmål too, so her videos are perfect for taking your language skills beyond simple sentences.

If you like her, also check out another teacher from her online school, Norsklærer Karense!

@hildeelise

Jeg elsker sola! #lærer #adjektiv #norskopplæring #morgen #norway

♬ original sound – Hilde Elise

Ola Norwegian

Ola, like Aria, uses English as his presentation language, giving his videos a more formal ‘classroom’ feel. But his content is top-notch, covering both grammar and word use. I’ve expanded my vocabulary with quite a few bits and pieces since following him.

@olanorwegian

Hvordan si “anyone”, “anywhere”, “anytime” osv? Jo: Du bruker frasen “som helst”! Men: En litt mer avansert frase er “however”. Vi kan nemlig IKKE si “Hvordan som helst”. Hmm. Har du svaret? Skriv i kommentarene! grammatikk norwegiancourse norskkurs norsk norwegian lærenorsk lærnorsk norskgrammatikk småprat smalltalk howtolearnnorwegian learnnorwegian norwegisch norskspråk norwegianlanguage norwegianculture norweski norway norge lifeinnorway explorenorway newtonorway noruega noruego oslo vocabulary vokabular

♬ original sound – Ola Norwegian – Ola Norwegian

Learn Norwegian with Preben

Preben is a worldly guy whose videos more often than not come from far-flung places well beyond Norway. But he has a focus on everyday Norwegian that is quite refreshing – casual, not overly analytical, and more like a mate telling you how to sound natural. For colloquial, idiomatic norsk, he’s your man!

https://www.tiktok.com/@norwegiancommunity/video/7533273676561550614

ilyantisocial.teaches

Like Preben, Ilya is a fan of the casual, colloquial approach to language. He’ll pick out everyday quirks and trip-ups that you won’t find in textbooks. His methods are a bit more organised, and you’ll get more chalk-and-talk in his videos, which may provide the yin to Preben’s yang!

@ilyantisocial.teaches

How to say hungry in Norwegian? How to say full in Norwegian? #norway #norwegian #languagelearning #language educational, speaking Norwegian, teacher things

♬ original sound – ilyantisocial.teaches

norwegian.with.tor

Tor was one of the first Norwegian content creators I discovered way back in the day on Instagram. Well, probably just a couple of years ago – an age in Internet terms. His content is perfect for the Insta reel format – fun, snappy sketches and gags with a learning slant. And he’s now popped up on TikTok, feeding your #NorwayTok algorithm with more micro-content.

https://www.tiktok.com/@norwegian.with.tor/video/7535920722074537238

So there you have it – six norsk content creators to transform your own algorithms with. Have I missed any of your own favourites? Let me know in the comments!

ElevenLabs Hits the Right Note: A.I. Songwriting for Language Learners

Leave a comment

In case you missed it, A.I. text-to-speech leader ElevenLabs is the latest platform to join the generative music scene – so language learners and teachers have another choice for creating original learning songs.

ElevenLabs’ Creative Platform ElevenMusic takes a much more structured approach to music creation that other platforms I’ve tried. Enter your prompt (or full lyrics), and it will build a song from block components – verse, chorus, bridge – just as you might construct one as a human writer. It makes for a much more natural-sounding track.

ElevenLabs music creation

ElevenLabs music creation

As you’d expect from voice experts ElevenLabs, the service copes with a wide range of languages and the diction is very convincing. A tad more so, I think, than the current iteration of the first big name on the block, Suno AI. No doubt the latter will have some tricks up its sleeve to keep up the pace – but for now, ElevenLabs is the place to go for quick and catchy learning song.

Anyway, here’s one I made earlier – a rather natty French rock and roll song about the Moon landings. Get those blue suede Moon boots on!

It’s definitely worth having a play on the site to see what you can come up with for you or your classes. ElevenLabs has a free tier, of course, so you can try it out straight away. [Note: that’s my wee affiliate link, so if you do sign up and hop on a higher tier later, you’re helping keep Polyglossic going!]

Generative Images Locally : Running Models on Your Machine

Leave a comment

I’ve written a fair bit about language models of late. This is a language blog, after all! But creating resources is about other visual elements, too. And just as you can run off text from local generative AI, you can create images locally, too.

For working on a computer, ComfyUI is a good bet. It’s a graphical dashboard for creating AI art with a huge array of customisation options. The fully-featuredness of it, admittedly, makes it a complex first intro to image generation. It’s interface, which takes a pipeline / modular format, takes a bit of getting used to. But it also comes with pre-defined workflows that mean you can just open it, prompt and go. There’s also a wide, active community that supports in online, so there’s plenty of help available.

Generate images locally - the ComfyUI interface

Generate images locally – the ComfyUI interface

At the more user-friendly end of it is Draw Things for Apple machines (unfortunately no Android yet). With a user interface much closer to art packages you’ll recognise, Draw Things allows you to download different models and prompt locally – and is available as an iOS app too. Obviously there’s a lot going on when you generate images, so it slugs along at quite a modest trot on my two-year-old iPad. But it gives you so much access to the buttons and knobs to tweak that it’s a great way to learn more about the generation process. Like ComfyUI, its complexity – once you get your head round it – actually teaches you a lot about image generation.

Of all the benefits of these apps, perhaps the greatest is again the environmental. You could fire up a browser and prompt one of the behemoths. But why crank up the heat on a distant data centre machine, when you can run locally? Many commercial generative models are far too powerful for what most people need.

Save power, and prompt locally. It’s more fun!

A swirl of IPA symbols in the ether. Do LLMs 'understand' phonology? And are they any good at translation?

Tencent’s Hunyuan-MT-7B, the Translation Whizz You Can Run Locally

Leave a comment

There’s been a lot of talk this week about a brand new translation model, Tencent’s Hunyuan-MT-7B. It’s a Large Language Model (LLM) trained to perform machine translation. And it’s caused a big stir by beating heftier (and heavier) models by Google and OpenAI in a recent event.

This is all the more remarkable given that it’s really quite a small model by LLM standards. Hunyuan actually manages its translation-beating feat packed into just 7 billion parameters (the information nodes that models learn from). Now that might sound a lot. But fewer usually means weaker, and the behemoths are nearing post-trillion param levels already.

So Hunyuan is small. But in spite of that, it can translate accurately and reliably – market-leader beatingly so – between over 30 languages, including some low-resource ones like Tibetan and Kazakh. And its footprint is truly tiny in LLM terms – it’s lightweight enough to run locally on a computer or even tablet, using inference software like LMStudio or PocketPal.

The model is available in various GGUF formats at Hugging Face. The 4-bit quantised version comes in at just over 4 GB, making it iPad-runnable. If you want greater fidelity, then 8-bit quantised is still only around 8 GB, easily handleable in LMStudio with a decent laptop spec.

So is it any good?

Well, I ran a few deliberately tricky English to German tasks through it, trying to find a weak spot. And honestly, it’s excellent – it produces idiomatic, native-quality translations that don’t sound clunky. What I found particularly impressive was its ability to paraphrase where a literal translation wouldn’t work.

There are plenty of use cases, even if you’re not looking for a translation engine for a full-blown app. Pocketising it means you have a top-notch multi-language translator to use offline, anywhere. For language learners – particularly those struggling with the lower-resource languages the model can handle with ease – it’s another source of native-quality text to learn from.

Find out more about the model at Hugging Face, and check out last week’s post for details on loading it onto your device!