Tag: vocabulary

Anki Heat Maps – Honesty Corner

When it comes to building and reviewing habits, honesty is the best policy. And there’s one Anki plug-in that has been that tough-talking, truth-speaking friend I’ve needed over the years.

Review heat map has been going for as long as I’ve been using Anki (and that’s a long time already!). I think it was a German conversation partner on iTalki who pointed me in its direction originally – it was so long ago, that that origin story is lost in the mists of time.

But because of that admirable length of service, I have years of usage data in there – and it really shines a light on my consistency (or lack thereof) in that time.

Anki Honesty

I’d not looked at mine in a while – in the desktop app they’re hiding below your decks – so it was about time to check in. And while I knew I’d been a bit on and off in 2024 (preparing for a PhD was a slight distraction!), I didn’t realise I’d been quite so neglectful.

Anki heat maps over time

Anki heat maps over time

It’s not all bad, though. There’s actually something very encouraging about this. Progress is bitty, yes; but it never stops completely. A couple of times, I’ve had over two weeks without checking in. But I’ve always got back into it (usually in a mammoth catch-up sesh, working through 200+ cards – although even those catch-ups took perhaps just 10-15 minutes each).

Taking stock like this also serves as a motivational kick – I can do better. And so it’s back in my goals list for 2025 – make Anki part of the start of your day. Getting a year completely blued out, like 2021, will be so satisfying.

Know Yourself

Heat maps can show us that sometimes, we fail to take our own advice. We fall off the wagon. It’s clear that there are times that I repeatedly let my daily tactics slide, despite my own efficiency evangelism!

That said, knowledge is power. Looking over those heat maps, I see when those times of slippage occur. Without fail, they’re always times of being over-busy, stressed out, or – conversely – times of extreme leisure (think: holidays!). More than anything, the stops and starts in my heat maps show that life sometimes gets in the way.

But you can always get it back on track.

Review Heat Map is a pretty essential addition to your Anki toolbox, to my mind. And it’s available for free from the Anki plug-ins site!

Greek text on a packet of crisps

Language Lessons from Packaging (And A Little Help from ChatGPT)

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If you love scouring the multilingual packaging of household products from discounter stores (a niche hobby, I must admit, even for us linguists), then  there’s a fun way to automate it with LLMs like ChatGPT.

Take the back of this packet of crisps. To many, a useless piece of rubbish. To me (and some of you, I hope!), a treasure of language in use.

Greek text on a packet of crisps - food and household item packaging can be a great source of language in use.

Greek text on a packet of crisps

Normally, I’d idly read through these, looking up any unfamiliar words in a dictionary. But, using an LLM app with an image facility like ChatGPT, you can automate that process. What’s more, you can request all sorts of additional info like dictionary forms, related words, and so on.

From Packaging to Vocab List

Take a snap of your packaging, and try this prompt for starters:

Create a vocabulary list from the key content words on the packaging label. For each word, list:
– its dictionary form
– a new, original sentence illustrating the word in use
– common related words

The results should be an instantly useful vocab list with added content for learning:

Vocabulary list from food packaging by ChatGPT

Vocabulary list compiled by ChatGPT from a food packaging label

I added a note-taking stage to round it off. It always helps me to write down what I’m learning, adding a kinaesthetic element to the visual (and aural, if you’ve had ChatGPT speak its notes out loud). Excuse the scrawl… (As long as your notes are readable by you, they’re just fine!)

Handwritten vocabulary notes derives from crisp packet packaging

Notes on a crisp packet…

It’s a fun workflow that really underscores the fact that there are free language lessons all around us.

Especially in the humblest, and often least glamorous, of places.

Mapping out conversational probabilities - it's much easier with flowcharts.

Vocabulary Flowcharts : Preparing for Probabilities with ChatGPT

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The challenge in preparing for a speaking task in the wild is that you’re dealing with multiple permutations. You ask your carefully prepared question, and you get any one of a number of likely responses back. That, in turn, informs your next question or reply, and another one-of-many comebacks follows.

It’s probability roulette.

What if you could map all of these conversational pathways out, though? Flowcharts have long been the logician’s tool of choice for visualising processes that involve forking choices. Combined with generative AI’s penchant for assembling real-world language, we have a recipe for much more dynamic language prep resources than a traditional vocab list.

And, thanks to a ready-made flowchart plugin for ChatGPT – courtesy of the charting folks at Whimsical.com – it’s really easy to knock one together.

Vocabulary Flowcharts in Minutes

In your ChatGPT account, you’ll need to locate the Whimsical GPT. Then, it’s just a case of detailing the conversational scenario you want to map out. Here’s an example for ‘opening a bank account in Germany’:

Create a flowchart detailing different conversational choices and paths in German for the scenario “Opening a bank account as a non-resident of Germany planning to work there for six months.” Include pathways for any problems that might occur in the process. Ensure all the text reflects formal, conversational German.

The result should be a fairly detailed ‘probability map’ of conversational turns:

A 'vocabulary flowchart' in German, created by the Whimsical.com GPT on ChatGPT.

A ‘vocabulary flowchart’ in German, created by the Whimsical.com GPT on ChatGPT.

Vocabulary flowcharts are another tool in your AI arsenal for speaking prep. Have you given them a whirl yet? Tell us about your own prep in the comments!

French Coffee Breaks

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If you know me, you’ll know that French was long my ‘also ran’ language – solid but under-used and under-practised. But that’s been changing more and more in recent years, as the language has been unexpectedly useful for a whole range of reasons. So this week, here’s a wee heads-up from me about a book I’ve been finding super useful for brushing up my French: 50 French Coffee Breaks.

I’ve been aware of the Coffee Breaks Languages brand for a while, thanks to their series of podcasts. They’re not actually a resource I’d used much in the past, as I had the impression the level was a bit basic. Wrong false impressions – I was pepped up by their Swedish ‘holiday soap opera’ lately, which was far from beginners-only, and really helped prepare for a trip to Malmö.

Anyway, roll on to now, and me, searching for something to improve my French. I’m a repeat false beginner – I did French at school, but ditched it for German and Spanish early on. Since then, though, it’s become incredibly useful (and attractive) as the language of a wonderful country that is very close to my own, and so very easy to visit! Cue lots of ‘improve my French’ blitz sessions over the years.

The cover of the book 50 French Coffee Breaks
50 French Coffee Breaks

French Coffee Breaks

For that French blitz, there are a couple of good, systematic improve-your-French books about, including the excellent Teach Yourself French Tutor, which I’ve used for grammar training. And it’s Teach Yourself that are behind the 50 Coffee Break books too, so there’s heritage and form backing the format.

The approach couldn’t be better for a busy linguist fitting in an extra maintenance language amidst everything else. The chapters offer 5, 10 and 15-minute practice sessions, across a range of useful (very travel-friendly) topics. In fact, they generally took me less time, depending on the level, but in every case they either strengthened something I’d half-forgotten, or taught me something new.

It’s definitely the kind of book you’ll want to write on and deface with a pen – anathema I know (books are my temple too!) but I made an exception with this one. There’s something very satisfying about filling it with scribble, and the pocket paperback format is perfect for it (I’d never sully my Teach Yourself Tutor books this way, mind!).

Overall, a fab purchase that has confirmed how useful the Coffee Break Languages materials are after all. I was thrilled to see that a Swedish version was released only last year too, something that had escaped my attention. Needless to say, I’ve got that one on my shelf now too…

A collage of lots of word and picture cards.

Treating Leeches – Strategies for Suspended Anki Cards

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How do you deal with leeches?

I’m not talking about traditional medicine here (not to downplay the modern application of the age-old treatment at all!). The leeches I’m more concerned with on the day-to-day are those Anki cards you forget so persistently that the app takes charge, suspending them from your deck.

It’s an apt description for an item that sucks away your time and motivation. I don’t know about you, but I also get that sinking feeling of failure when “card was a leech” pops up baldly.

Catching Leeches

First of all, fight that feeling. Leeches can creep up for a number of reasons, and your memory lapse is the least of them. Despite the cold rebuke, Anki means well. It suspends the cards to save you wasting any more time on part of your learning strategy that isn’t quite working. So, for now, let them go.

Instead, schedule a review of leeches regularly. Once a month or so seems about right if you’re a prolific language learning user – I always have a couple to deal with in that time span. In the Anki desktop app, head to Browse. Then, there are two ways to list leeches. You can simply highlight Suspended under Card State in the left-hand menu.

Exposing leeches via Suspended Cards in the Anki Browse window

Exposing leeches via Suspended Cards in the Anki Browse window

Otherwise, you can use the fact that Anki tags leech cards with the text leech to draw them out. Highlight one of your decks in the left-hand menu, then in the bar at the top of the Browse panel, add the text tag:leech to narrow the results to that set.

Exposing leeches via tags in the Anki Browse window

Exposing leeches via tags in the Anki Browse window

Now out in the open, we need to think of a rehabilitation strategy for our annoyingly helpful leeches.

Treating the Cause, Not the Problem

It’s tempting to just un-suspend by removing that leech tag, and pop the card right back in the deck. But there’s a reason Anki singled it out – something wasn’t working.

Often, it’s not simply failure to remember. Many of mine aren’t words I’ve forgotten, but words I get mixed up – either with other target language words, or with the wrong English translation. For example, in Greek, I leeched out παραδέχομαι (paradéchomai – admit) with αποδέχομαι (apodéchomai – accept), due to their similarity – same root verb, different prefix.

It’s not always just soundalikes, either, but happens with concepts. Left and right are a case in point in Swahili. I know both words very well – kushoto and kulia – but I’d always say one for the other, to the point that they were marked as leeches.

I could recall them – it had just become 50/50 whether I’d say one or the other!

These cases of interference usually arises because there’s a lack of distinguishing information on the vocab card. The easiest way to fix that is to make your cards clearer and more precise. Any defining detail will do, and with language learning, context is key. Short sentences that embed the vocabulary items are perfect. To give the brain more to hang onto, you can expand them from basic X is Y types to X is Y, so/because…, and even make use of allegory and rhyme in your examples.

Taking the Swahili example, there’s a topical hook with those that adds layers of meaning: politics. There’s also a good rhyme for kulia in pia (also). So to my card, I add the sentence (and forgive the unpalatable mention of unpopular politicians here) Boris yuko kulia, na Rishi pia (Boris is on the right, and Rishi too).

And (of course) there’s a wee AI tip for that. If you struggle to fine rhymes – not unreasonable if you’re at an early stage in a language – then just ask your LLM of choice for rhyming pointers, or even entire couplets. It’s one of the things is does a pretty decent job of!

Asking AI for rhyming words in foreign languages.

Asking ChatGPT-4 for rhyming words in foreign languages.

 

 

Leeches are an initially frustrating but ultimately helping feature of the Anki lifestyle! Do you have alternative methods for bashing them? Let us know in the comments!

Does AI have a noun problem? Strategies for avoiding it.

AI Has A Noun Problem : Let’s Fix It!

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If you’re using AI for language learning content creation, you might have already spotted AI’s embarrassing secret. It has a noun problem.

Large Language Models like ChatGPT and Bard are generally great for creating systematic learning content. They’re efficient brainstormers, and can churn out lists and texts like there’s no tomorrow. One use case I’ve found particularly helpful is the creation of vocab lists – all the more so since it can spool them off in formats to suit learning tools like Anki.

But the more I’ve used it, the more it’s become apparent. AI has a blind spot that makes these straight-out-the-box vanilla lists much less useful than they could be.

A fixation with nouns.

Test it yourself; ask your platform of choice simply to generate a set of vocab items on a topic. Chances are there’ll be precious few items that aren’t nouns. And in my experience, more often than not, lists are composed entirely of noun items and nothing else.

ChatGPT-4 giving a list of French vocabulary items - all nouns.

ChatGPT-4 giving a list of French vocabulary items – all nouns.

It’s a curious bias, but I think it has something to do with how the LLM conceives key words. The term is somehow conflated with all the things to do with a topic. And nouns, we’re taught at school, are thing words.

Getting Over Your Noun Problem

Fortunately, there’s therapy for your AI to overcome its noun problem. And like most AI refining strategies, it just boils down to clearer prompting.

Here are some tips to ensure more parts-of-speech variety in your AI language learning content:

  1. Explicit Instruction: When requesting vocabulary lists, spell out what you want. Specify a mix of word types – nouns, verbs, adjectives, adverbs, etc. to nudge the AI towards a more balanced selection. When it doesn’t comply, just tell it so! More verbs, please is good start.
  2. Increase the Word Count: Simply widening the net can work, if you’re willing to manually tweak the list afterwards. Increase you vocab lists to 20 or 30 items, and the chances of the odd verb or adjective appearing are greater.
  3. Contextual Requests: Instead of asking for lists, ask the AI to provide sentences or paragraphs where different parts of speech are used in context. This not only gives you a broader range of word types, but also shows them in action.
  4. Ask for Sentence Frames: Instead of single items, ask for sentence frames (or templates) that you can swap words in an out of. For instance, request a model sentence with a missing verb, along with 10 verbs that could fill that spot. “I ____ bread” might be a simple one for the topic food.
  5. Challenge the AI: Regularly challenge the AI with tasks that require a more nuanced understanding of language – like creating stories, dialogues, or descriptive paragraphs. This can push its boundaries and improve its output.

Example Prompts

Bearing those tips in mind, try these prompts for size. They should produce a much less noun-heavy set of vocab for your learning pleasure:

Create a vocabulary list of 20 French words on the topic “Food and Drink”. Make sure to include a good spread of nouns, verbs, adjectives and adverbs. For each one, illustrate the word in use with a useful sentence of about level A2 on the CEFR scale.
Give me a set of 5 French ‘sentence frames’ for learning and practising vocabulary on the topic “Summer Holidays”. Each frame should have a missing gap, along with five examples of French words that could fit in it.
Write me a short French text of around level A2 on the CEFR scale on the topic “Finding a Job in Paris”. Then, list the main content words from the text in a glossary below in table format.

Have you produced some useful lists with this technique? Let us know in the comments!

A deck of neon flashcards. Anki cards might not be quite as fancy!

From ChatGPT to Anki : Instant Potted Vocab Decks!

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With cutting edge AI galvanising the language learning world, traditional tools like Anki – which would have been considered the leading edge not that long ago – seem well in the shade. But it’s not a question of either-or. Traditional and new tech can work in happy symbiosis to support language learning.

Preparing for a recent high-stakes language mission (OK, island-hopping hol!) to Greece, I wanted to turboboost my Greek vocab. Anki was my tool of choice, of course, but one question remained: where to source new flashcard decks? Large Language Models like ChatGPT and Bing were easy choices for generating topical vocab lists, but how much copy-pasting would that involve? I wasn’t keen on spending hours formatting cards manually.

Thankfully, ChatGPT Plus’ Advanced Data Analysis mode can provide a bridge between old and new. Forget that slightly intimidating title – the main boon is simply that this mode can output a text file. And, given the right format, Anki can take such a text file as an import source. With a bit of prompting prowess, we can automate the whole process – from topic to cards, in one fell swoop. Before long, I had a fresh daily drip-drip of new words and phrases, a real shot in the arm for my Greek pre-trip.

Here’s how to task ChatGPT with the whole job of Anki deck creation. If you don’t have the Plus version, no problem – scroll down for a modified version that works with completely free plans and services!

Automatic Anki Decks – Plus Style

First of all, start a new chat in ChatGPT, and make sure Advanced Data Analysis is selected in the drop-down menu under ChatGPT-4.

Selecting Advanced Data Analysis mode in ChatGPT-4.

Selecting Advanced Data Analysis mode in ChatGPT-4.

Now, we’re ready for our prompt. Like our AI speaking prep worksheets, the beauty of this is just how specific you can make your flashcards. The topic can be as broad or narrow as you like. Here’s a sample prompt to create a French deck on the talking point ‘social issues’:

Hello! I’m learning French, and I’d like you to create an Anki flashcard deck to help me. To import a deck, Anki requires a CSV file format with just a “Front”, “Back” and “Tags” field corresponding to the English. the target language phrase and the part of speech. There is no need for header fields, so the first line should represent the first vocabulary item.
Can you create such an Anki-ready list of 50 flashcard items on the topic “Social Issues” for me, then save it for me as a .txt file I can import into the app?
– Provide a good mixture of essential and useful nouns, verbs, adjectives, and useful phrases / sentence frames (ie., so it’s not just a list of nouns!).
– Provide each term in its dictionary form if appropriate, indicating gender, plural and essential or irregular parts briefly as per convention where applicable.
– Ensure that all terms relate to the contemporary culture of the target language country as much as possible.
– Please draw on resources in the original target language when researching which words will be most useful, cross-referencing with all available data and checking constantly to make sure that the target language for the flashcards is accurate and colloquial, never bookish or unnatural.

Limitations (For Now)

One limitation with the Advanced Data Analysis mode is that it can’t run concurrently with ChatGPT’s now restored web-connected mode, or Browse with Bing. All that means is that it will be relying on its banks of training data for the vocab collation, rather than the web. But in most cases, it shouldn’t make too much difference given the vastness of that data (although it will notify you apologetically about it – see below). We’re waiting for the day – hopefully soon – that OpenAI allows users to run several premium features together.

ChatGPT Plus whirring away creating an Anki deck.

ChatGPT Plus whirring away at an Anki deck. Quirky repartee not as standard, but provided by special request thanks to custom instructions! I like my AI cheeky.

Into Anki We Go

One you have your ChatGPT-infused vocab file ready, you can import it straight into Anki. In the Anki desktop app, head to File > Import, and select the file you saved. The import settings window will pop up, including, crucially, which field matches to which column of your data under Field Mapping. The app guesses correctly for the most part, but occasionally you may need to specify that the third column (part of speech) maps to the tags field.

Importing CSV data into Anki decks.

Importing CSV data into Anki decks.

And that’s it. You should get a brief report of the number of items added, and they’re ready to play with straight away. Instant, fresh vocab decks in seconds!

No ChatGPT Plus? No problem!

Now, the above is all very well if you have ChatGPT Plus. Many platforms lack the file output side of things. But you can still get them do the heavy work of vocab-hunting and file-formatting; all you need to do is the final copy-paste-save.

Here’s how to alter the prompt for plain old vanilla ChatGPT and Bing, coaxing it to provide Anki-ready output. I’ve also made the format a little clearer, which might help if you’re using slightly older models like ChatGPT-3.5.

Hello! I’m learning French, and I’d like you to create an Anki flashcard deck to help me. To import a deck, Anki requires a CSV file format with just a “Front”, “Back” and “Tags” field corresponding to the English. the target language phrase and the part of speech.
Can you create such an Anki-ready list of 25 flashcard items on the topic “Driving a Car” for me? Output the CSV data as formatted as code so I can easily copy-paste into a text file for Anki.
– Don’t include header fields in the CSV – the first line of your output should be the first vocabulary item (ie., car,la voiture,noun).
– Provide a good mixture of essential and useful nouns, verbs, adjectives, and useful phrases / sentence frames (ie., so it’s not just a list of nouns!).
– Provide each term in its dictionary form if appropriate, indicating gender, plural and essential or irregular parts briefly as per convention where applicable.
– Ensure that all terms relate to the contemporary culture of the target language country as much as possible.
– Please draw on resources in the original target language when researching which words will be most useful, cross-referencing with all available data and checking constantly to make sure that the target language for the flashcards is accurate and colloquial, never bookish or unnatural.

Your platform should spool out some easily copiable code. Simply paste this into a text file, save, and import into Anki.

Even using 3.5, I got some great results featuring practical, useful vocabulary sets.

Creating Anki decks with the free ChatGPT3.5 model.

Creating Anki decks with the free ChatGPT3.5 model.

Experiment, Experiment, Experiment!

As with all AI prompts, it’s worth experimenting with everything to tweak, improve and get the absolute best out of it. The number of cards, the mix of words and phrases, the source of the material – make it your own. When you have it just right, you can create cards for your own, or your students’ learning, in seconds.

Oh, and don’t forget to save your perfect prompts somewhere you can copy-paste them from later, too!

If you’re keen for more artificial intelligence tips to boost your learning, please check out my book AI for Language Learners. It’s packed with practical examples to fuel your linguistic adventures!

A screenshot of Lingvist in use, demonstrating its lovely, clean interface.

I Befriended a Lingvist (and It Was About Time) [Review]

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I gave Lingvist a whirl this week, a sentence-based language learning app from Estonia that had mysteriously passed way under my radar until now. The verdict: Lingvist, I’m glad I finally found you!

It’s a bit of a match made in Heaven, to be honest, given my love of mass sentence techniques. This app uses in-context, useful sentences to illustrate all of its vocabulary items, drawing on a massive library of items for each language. The sheer size of its libraries should keep even the most avid learners busy for a while, and it’s available in an impressive number of languages:, including Estonian (as you’d expect!), Japanese, Korean, Norwegian, Polish and Swedish, as well as the other ‘biggies’.

It boasts a very smart, clean app design, using an eminently readable font (always an easy thing to overlook in a language app). It has a sensible, just-forgiving-enough approach to mistakes, particularly with accents. And – most impressively – it has the most user-friendly automatic voice input mode I’ve come across in such an app. Even more impressively, it allows Japanese input in all three writing systems.

A screenshot of Lingvist in use, demonstrating its lovely, clean interface.

In use, the app has an excellent approach to exposition and testing. Items, new and old, appear as gap-fill challenges as you perform sentence repetitions. That makes for an engaging routine, even when words you already know pop up – it’s not just learning, it’s practice. As such, it’s the perfect tool if you already know some of the language, but want to start filling in the gaps.

Not a Newbie? Not a Problem!

Talking of non-beginners, Lingvist also features a great placement test mode. For a start, it’s not overlong. Isn’t it always a bit soul-sapping when a new app makes you churn through a 10-minute test off the bat? Lingvist’s snappy check pretty accurately chooses a spot to skip you to very quickly.

To check it out, I performed the test in my strongest foreign language, German. It airlifted me about 85% of the way to the end of its mammoth list. And, proving there’s always something more to learn, the sentences were actually complex and interesting enough to challenge me. That bodes well for forging ahead it with it in my more nascent languages – you can reach a very decent level of language with it.

It tracks that gap-filling with what seems like a quite sophisticated spaced repetition algorithm. Despite that sophisticiation, you have at-a-glance access to all of those stats in a clear, unjargonised format, which  makes the spaced rep process understandable even if you’re new to it. Again, no wonder I love it, given my constant proselytising of the spaced repetition original, Anki.

Generous Trial Period

The best things, of course, are usually worth paying for. And true enough, Lingvist is a premium app, although its pricing is very competitive compared to the likes of Babbel and others, at just over £5 a month on an annual plan. But what’s striking about Lingvist is how generous the team have been with the free trial (at least on iOS). You get a whopping 14 days to try the software out. That’s significantly more than the usual seven days with most – if you’re lucky enough to get a trial at all.

I’m just puzzled over why it took the algorithms so long to push Lingvist in my path, especially since the App Store says it’s been around since 2016. I hope it’s not been such a hidden, under-the-radar app for others, as it really deserves to be up there amongst the best.

If it’s your first time hearing about it too, check it out!

An excerpt from the AQA GCSE Spanish spec.

GCSE Specs : Free Language Learning Roadmaps

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If you’re a book fiend and love cheap resources, you’ll share my excitement for bargainous budget language guides for students taking school exams like GCSE French, German and Spanish. But you’ll be even more excited to learn that there’s a way to get this thematic, graded content for free.

Enter the humble exam specification document. All exam boards, like AQA and Edexcel in the UK, publish specifications for the qualifications they award. These PDF documents list all of the material students are expected to know in order to possess that competence, and serve as a checklist for teachers preparing students for exams. For foreign languages, that includes core vocabulary and structures, as well as cultural background information. Core vocab is frequently in glossary format, making it the stuff of dreams for systematic learners.

GCSE Goldmines

So where to find these little treasure troves of free learning? The first thing is to identify national exam boards that offer foreign language qualifications. I chose the GCSE as it’s the gold standard first stage school leaver certificate in England and Wales; change this as appropriate for whatever local qualification you are more familiar with. Google which boards run those qualifications, then mine their sites for subject pages, where you should find spec docs as downloadable PDFs. Check out AQA Spanish and Edexcel German for great examples.

GCSE French specification page from Pearson EdExcel

GCSE French spec page from Pearson Edexcel

When you drill down into these documents, you’ll find super-handy lists of topic-related words. But you can also find some really handy crib lists that aren’t simply lists of nouns under topic headings. What I find particularly useful are the round-ups of important function words, which you don’t often see in one place in a course book. Looking for a quick cheat sheet for connectives and sentence-builders in your target language? Bingo!

An excerpt from the AQA GCSE French spec.

An excerpt from the AQA GCSE French spec.

Once you have that precious vocab, you can tackle it with your tool of choice. I like to load mine into Anki, or – increasingly, of late – paste it into AI to play some word games with.

Roadmaps – to Plenty of Places!

Obviously, there is some limitation in terms of languages, with an obvious bias for mainstream school languages like French, German and Spanish. You simply don’t find many schools that are teaching Croatian, Swahili or Uzbek. But between AQA and Edexcel, I also counted Chinese, Ancient Greek, Modern Greek, Hebrew, Italian, Japanese, Panjabi, Polish and Russian, so the choice is more impressive than you might fear.

Certainly, these spec docs are no comprehensive textbooks. For vocabulary, they can be a one-stop shop. But for grammar, you’re more likely to get a summary of features students should know, such as essential irregular verbs, or key tenses listed by name, but not fleshed out. That said, there is still huge value in that; see it as a kind of manifesto for what you, yourself, should be focusing on in the early stages of language learning. In this way, GCSE specs can supplement other learning materials as a kind of roadmap.

The Exam Spec Yardstick

As well as providing handy ‘how to’ guides for languages, there’s another benefit. It’s actually quite helpful to gauge your own competence against a national qualification. It gives you the confidence that you are performing in that language at a particular level. Many specs include links to wider levelling tools like CEFR (the A1-C2 scale) too, which is practically the currency of the polyglot community.

But specs can also provide the encouragement you need to seek accreditation yourself. If you have the knowledge and skills for GCSE French under your belt, why not sit GCSE French? There are plenty of further ed organisations that offer language GCSEs for adult learners – check your local colleges and universities to see what’s available.

It’s out there, waiting for you – a bunch of comprehensive, expertly curated resources to download for free. What gems have you found amongst the specs? Let us know in the comments!

Up the etymology garden path with ChatGPT

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This week’s story starts with an instinct. I’ve been learning Swedish, which, as a Norwegian speaker, has advantages and disadvantages. One downside is the need to fight the assumption that the vocabulary of each matches up exactly with an identical etymology, when this is so often patently untrue.

In fact, Norwegian and Swedish have walked separate paths long enough for all sorts of things to happen to their individual vocabularies. For instance, take trist and ledsen, both meaning sad in Norwegian and Swedish respectively. Adding ledsen to my list of Swedish differences (I’m using my Swedish Anki deck just for the differing words), I started wondering about the etymology of both. Norwegian trist, clearly, I thought, is a French borrowing, probably via Danish. On the other hand, ledsen looks like it was inherited from the North Germanic parent language.

ChatGPT Etymology

Since I’m exploring the use of AI for language learning both personally and professionally at the moment, it seemed like a good test case for a chat. I went straight in with it: is the Norwegian word trist a borrowing from French?

But shockingly, ChatGPT was resolute in its rejection of that hypothesis. The AI assistant insisted that it’s from a Nordic root þrjóstr, the same that gives us þrjóstur (stubborn) in Modern Icelandic, with the variant þristr which seems to have evolved into Modern Norwegian trist.

Now, the thing with ChatGPT is that it can be so convincing. That’s entirely thanks to the very adept use of natural language in a conversational format. The bot simply speaks with an authoritative voice like it knows what it’s talking about.

So it must be true, right?

Manual Etymology

At this point, it all felt a bit off. I just had to do some manual digging to check. In Bokmål cases like these, my first port of call is the Norsk Akademi Ordbok. If there is an authority on Norwegian words, there’s little that comes close.

So I key in trist, and – lo and behold – it is a French borrowing.

The entry for 'trist' in the Norwegian Academy's Dictionary, showing its etymology.

The entry for ‘trist’ in the Norwegian Academy’s Dictionary, showing its etymology.

There’s no mention of Danish, just the French and the Latin that comes from. I suspect, with a bit of digging, it might turn out to have been borrowed into Danish first, but NAOB is definitive. Not a hint of Norse etymology.

Now there’s a chance ChatGPT knows something that NAOB doesn’t, although I doubt it. More likely, it’s just the innate talent the emergent AI has for winging it, and making best guesses. That’s what makes it so powerful, but, like human guesses, it’s also what makes it fallible just now. It’s a timely reminder to double-check AI-generated facts for the time being.

And maybe, to just trust your own instinct.