Tag: vocabulary

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.

An egg frying in a non-stick frying pan (image by freeimages.com). How do you ensure your vocabulary doesn't stick together?

Non-Stick Vocabulary : Separating Similar Words

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We’ve all been there in the early stages of language learning. Somehow, certain words just seem to blend into each other. Does X mean Y or Z? I keep saying X for Y! And why do all those little words look so similar? You want your vocabulary to stick in your mind, not the individual items to stick together. 

These recall problems are pretty normal, particularly when you throw in the social pressure of speaking with others, which can even mess with your native language. With a foreign language, the problem is compounded by differences in phonemic salience – that is., which sounds count as important markers to distinguish one word from another. Something really subtle in your native language, like the difference between a hard stop and a palatalised counterpart, can completely change a meaning. Take the pair of words adabu (good manners) and ajabu (wonder, amazement) in Swahili. When I started Swahili classes, I could not separate them in my head for the life of me. It’s likely that my brain just found it tricky to meaningfully separate the sounds represented by d and j, as /d/ often morphs into /dj/ in my native dialect (try saying induce or and you).

Other times, words might get sticky because they share similar structures that co-trigger, like rhyming sequences. That would explain why I also found it tricky to separate the word asali (honey) from the previous two. Latching onto that aXa pattern, it somehow ended up occupying a very similar memory space to adabu and ajabu. And of course, it probably didn’t help that you spell all three with just five letters! It’s the cost-economising (read: lazy) part of the brain spotting patterns and making heuristic shortcuts – even when these are very unhelpful. Tsk. (Incidentally, the brilliant Daniel Kahneman writes about dodgy heuristics in Thinking, Fast and Slow, which is well worth a read if this piques your interest!)

Revisiting Vocabulary

Interestingly, it’s an effect that isn’t confined to brand new languages. It can even happen with old languages we’re dredging up from the past, or low-level maintaining.

Hebrew is one of those for me. It’s not quite a maintenance language; in fact, I can barely even count it as a fully-fledged language of mine. I barely reached A1 in the modern, spoken language, so it doesn’t take a lot of maintaining. I keep it in that list, chiefly, for reasons of nostalgia!

Anyway, a couple of years ago, I sought to do that minimal maintenance a bit more systematically. I grabbed my copy of Routledge’s Colloquial Hebrew, trawled the first six chapters for vocabulary, and dumped it into Anki. I set my Hebrew deck to drip through a single new card a day, and just let time do the rest.

Overall, it’s been a brilliant, low-key method for solidifying all that ultra-basic stuff. But, every now and again, I do struggle to recall certain words. And surprise, surprise, it’s usually those that look a little bit similar to others. It’s adabu-ajabu all over again!

Seeing it through Anki eyes gave me a new perspective on it, though. In test mode, mix-ups are largely artefacts of the isolated vocabulary item problem. It crops up time and time again in polyglot social media circles: don’t drill words, drill structures. Disembodied parts of speech have little salience on their own. Your brain needs something to hang them onto.

Damage Limitation

Of course, when all your Anki cards are done, you’re already in a bit of a bind over this. You could go back and update all your cards to be sentences (sourcing them from a bank like Tatoeba, for example). But that’s a lot of work.

Instead, you can embed mixological words in some kind of context on the fly. When cross-contamination occurs, think of a phrase – however short – to include the word in. Use alliteration, rhyme, any trick to make it stick. Say it out loud, enjoy the sound of it, visualise it. And try to recall that same phrase whenever the troublesome word pops up again. For my Swahili pair, I came up with:

  • mji wa ajabu (a wonderful town)
  • dada mwenye adabu (a good-mannered sister)

In both cases I’ve chosen a word repeating the troublesome letter (d/j) to highlight the problem sound. I won’t say I never mix them up now – but it has certainly helped.

From my novice Hebrew, another example shows that you can sometimes even combine them together. Take tsar (tight, narrow) and tsad (side). Smoosh them up into tsad tsar (narrow side), and they might just end up sorting each other out.

What words do you tend to mix up in your target language? And how do you go about fixing it? Let us know in the comments!

Greek microblog content from Instagram (screenshot).

The Way of the Microblog : Kitchen Sink Inspiration and Language Learning

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It’s all about the foreign language microblog for me lately. Short, snappy snippets of target language piped directly to your social media streams: what’s not to love?

In fact, I’m practically drowning in them at the moment. That’s thanks to the notorious and mysterious algorithm (TM), of course, which is a fact of life these days; like one thing, and you get a ton more of the same thrown at you, for better or for worse.

Happily, in the case of us language learners, it’s generally for the better. Take my Instagram feed; its AI wisdom has decided to channel reams of Greek pop psych, heartwarming quotes and concise self help my way. It’s twee and a wee bit naff, granted. But every one of those posts is a 30-second language lesson.

This latest bite-sized adventure all started with a single Greek account, gnwmika.gr. It exclusively posts what you might call ‘fridge magnet’ content: folk wisdom and kitchen sink inspiration.

The great lesson imparted here, in true, lofty microblog style, is:

“Beautiful things will make you love life. Difficult ones will teach you to appreciate and respect the beautiful ones.”

I know – deep, eh.

Anyway, I hit follow and thought little else of it… Until things escalated. Next thing, I’m being shepherded to not only more of the same, but anything and everything Greek. Poetry, history, celebs, TV… the lot. It’s become a rabbit hole leading to some well obscure (but fascinating) places. And, crucially:

…my Greek is so much better for it!

Fill Your Little (Microblog) World Right Up

It all plays in marvellously to the fill your world with target language strategy. Since our worlds are ever more digital, one of the easiest ways to do that is to follow the monkeys out of accounts we find fun and engaging. Add one or two, and let the system start popping more and more into your suggested follows.

Now, the only catch is that the algorithm (TM) is smothering me in Greek. I’d love a bit of Gaelic, Icelandic, Norwegian or Polish (and the rest). So, if you’re reading this and have some good microblog recommendations to kick the cycle off again…

…please let me know!

Polish verbs of motion - my mistake-ridden brain dump!

Slavic Kryptonite: Vanquishing Verbs of Motion

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Every foreign language has its kryptonite. Sometimes it’s a common sticking point that takes most learners time to really get. Other times, it’s a personal stumbling spot for an individual learner. For me, it’s verbs of motion that are my strength sappers.

So why are they so difficult? Or, rather, why do I find them so difficult? I’m not denying the possible existence of some polyglot supermind that simply understands them at a click of the fingers (and I bow down to that mind!). But, for me, verbs of motion take time to grasp as a native speaker of a non-Slavic language. Namely, they have an extra layer of granularity compared to the comparatively simple come and go in English.

First of all, like many languages, Polish makes a distinction between going by foot and going by vehicle. Nothing strange there – for example, decidedly non-Slavic German does the same with gehen and fahren.

But in Polish (as well as many of its Slavic sibling and cousin languages – perhaps all of them, although I’m sure someone better-versed can correct me!), there is also a split between going once and going frequently or repeatedly. These can be formed from quite unsimilar roots, too; to go (on foot) in Polish is either iść or chodzić. So, we have:

  • idę do szkoły
    I go / am going to school (now)
  • chodzę do szkoły
    I go to school (regularly, as I work / study there, for example)

Brain Dump Horror

So far so good, then; just a few extra nuances and verb tables to learn. Now, I thought I had those covered, but there’s always room for revision. So, one evening this week, I decided to do a brain dump to check what I remembered. Brain dumpage, of course, is always worth doing regularly to audit your language skills. I splurged as much as I could remember onto a sheet of paper, then checked my results against a good grammar book.

It wasn’t pretty.

Polish verbs of motion - my mistake-ridden brain dump!

Polish verbs of motion – my mistake-ridden brain dump!

Present tense? No problem. Past and future? A disaster.

To be fair, I could have seen it coming. My poor iTalki Polish teacher has been subject to my unconfident fumblings for the right going word for some time already.

It was time to sort it out.

Verbs of Motion : A Strategy

Here’s the thing: knowing conjugations and grammatical intricacies off-by-heart are important for serious study of a language. But if your goal is to speak fluently, then simply having a few common forms confidently in memory is arguably more useful. In any case, some linguists, like Bybee, argue that this is how we build up and reference our native languages too – not as grammatical tables and rules, but as interconnected exemplars in the mental lexicon, ready-for-use, pre-conjugated models from exposure that we use for reproduction.

Of course, you could say that my Polish-learning brain was doing a bit of that already. If you look at my red-bepenned brain dump above, the past tense bits of to go I did get right were the first, second and third person masculine forms – probably frequent parts in my own conversation.

But then, what about what I do with other people? The we bits of the paradigm clearly needed some work. And then, talking about friends and family – for that, let’s add in the they parts. Gradually, a picture emerges of what I need to add to my vocab drilling. This useful list at the ready, I then add them into Anki as individual vocab items, and they’re on the conveyor belt to stronger recall. Here are a few for illustration:

  • pójdę
    I will go (on foot, once)
  • (po)jadę
    I (will) go (by transport, once)
  • szliśmy
    we went (on foot, once)
  • jechałem
    I went (by transport, once)
  • jeździłem
    I used to go, would go (by transport, multiple times)

…and so on. Fingers crossed, talking about moving and shaking will start sorting itself out soon.

Break it down, build it up

It’s a great trick, but time-old and simple: break a bigger problem down to slowly build up your competencies. You can apply it to verb patterns in many foreign languages, not just Polish, as well as any other aspect that seems too multifaceted and complicated to grasp all in one fell swoop.

The next time I do a brain dump of Polish verbs of motion, I hope I’ll get a few more right. And if I do, I expect it will have more to do with working on those key forms, rather than developing a photographic memory of entire verb tables.

A big slice of cheese. And Anki moved mine! Picture from freeimages.com

Who Moved My Cheese? Anki media folder, Mac edition

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It is actually a fair while since I last tinkered under the Anki hood. I haven’t needed to, to be honest. I’d set everything up just right for my current clutch of active and maintenance languages way back, and everything was chugging along nicely.

But polyglot dreams never sleep for long. The need for a fresh round of customising came from an exciting new side project, Croatian. Easy, I thought. I’ll rustle up some cute Croatian card layouts, complete with a cute wee flag.

The problem: everything had changed!

Frustratingly, it was no longer possible to access the media and backup folders from the app itself. There must be some rationale behind this, of course, and it’s not hard to reason why. Wrong moves when messing with app files can be dangerous for your precious vocab database.

But, for low stakes operations like simply dropping an image into the media folder, it seems reasonable to have access to it (with a helpful dose of caution!). Unfortunately, there’s a dearth of how-to out there right now. It took a bit of Googling and re-Googling to find the answer. But, finally, I sorted it.

And here’s how!

Anki media folder (Mac)

The Anki library folder now lives in the following place on a Mac:

/Users/[your_username]/Library/Application Support/Anki2/[your_anki_name]

However, the path is probably hidden to you from the Library level up. To get round that, bring up your username folder (Users/[your_username]) in Finder. Then,  hold down command (⌘), shift and the full stop (period, .) key to show hidden files and folders. You should now see a whole load of extra items, including the Library folder. Drill down from there along the above path, and you should end up in your Anki directory.

If it’s not there, then it’s also worth trying the ‘all users’ version of that path:

/Library/Application Support/Anki2/[your_anki_name]

Once you’ve located it and entered the (now) secret lair, it’s still collection.media we’re interested in as before. You can drop whatever you like in here, and refer to it in your card templates and other custom Anki items – just like in the old days!

Once you’re done, of course, you might well want to hit command (⌘), shift and the full stop again go hide all those oddly-named bits and pieces – until the next time!