AI Parallel Texts for Learning Two Similar Languages

I’ve seen a fair few social media posts recently about linguist Michael Petrunin’s series of Comparative Grammars for polyglots. They seem to have gone down a storm, not least because of the popularity of triangulation as a polyglot strategy.

They’re a great addition to the language learning bookshelf, since there’s still so little formal course material that uses this principle. Of course, you can triangulate by selecting course books in your base language, as many do with Assimil and other series like the Éditions Ellipse.

Parallel Texts à la LLM

But LLMs like ChatGPT, which already do a great job of the parallel text learning style, are pretty handy for creative comparative texts, too. Taking a story format, here’s a sample parallel text prompt for learners of German and Dutch. It treats each sentence as a mini lesson in highlighting differences between the languages.

I’m learning Dutch and German, two closely related languages. To help me learn them in parallel and distinguish them from each other, create a short story for me in Dutch, German and English in parallel text style. Each sentence should be given in Dutch, German and English. Purposefully use grammatical elements which highlight the differences between the languages, which a student of both does need to work hard to distinguish, in order to make the text more effective.

The language level should be lower intermediate, or B1 on the CEFR scale. Make the story engaging, with an interesting twist. Format the text so it is easy to read, grouping the story lines together with each separate sentence on a new line, and the English in italics.

You can tweak the formatting, as well as the premise – specify that the learner already speaks one of the languages more proficiently than the other, for example. You could also offer a scenario for the story to start with, so you don’t end up with “once upon a time” every run. But the result is quite a compact, step-by-step learning resource that builds on a comparative approach.

ChatGPT creating parallel texts in German and Dutch with an English translation.

ChatGPT creating parallel texts in German and Dutch with an English translation.

Variations and Limitations

I also tried prompting for explanatory notes:

Where the languages differ significantly in grammar / syntax, add an explanatory note (in English) to the sentences, giving details.

This was very hit and miss, with quite unhelpful notes in most runs. In fact, this exposes the biggest current limitation of LLMs: they’re excellent content creators, but still far off the mark in terms of logically appraising the language they create.

It is, however, pretty good at embellishing the format of its output. The following variation is especially impressive in an LLM platform that shows a preview of its code:

I’m learning Spanish and Portuguese, two closely related languages. To help me learn them in parallel and distinguish them from each other, create a short story for me in Spanish, Portuguese and English in parallel text style. Each sentence should be given in Spanish, Portuguese and English. Purposefully use grammatical elements which highlight the differences between the languages, which a student of both does need to work hard to distinguish, in order to make the text more effective.

The language level should be lower intermediate, or B1 on the CEFR scale. Make the story engaging, with an interesting twist.

The output should be an attractively formatted HTML page, using a professional layout. Format the sentences so they are easy to read, grouping the story lines together with each separate sentence on a new line, and the English in italics. Hide the English sentences first – include a “toggle translation” button for the user.

Claude by Anthropic creating an HTML-formatted parallel story in Spanish and Portuguese.

Claude by Anthropic creating an HTML-formatted parallel story in Spanish and Portuguese.

It’s another use case that highlights LLMs’ greatest strength: the creation of humanlike texts. For linguists, it matters not a jot how much (or little) deep understanding there is beneath that. With the language quality now almost indistinguishable from real people-speak, AI texts serve as brilliant ‘fake authentic’ language models.

e-Stories as parallel texts are yet another fun, useful flavour of that!

A cute robot coding at an old-fashioned computer terminal. AI code generation is great for making language games!

AI for Language Games : We’re All Developers, Now!

I’ve been developing games for language learners for over two decades now. Learning those programming skills was a labour of love, started when I was still a classroom teacher. Honing my own coding skills took years of practice. But now, thanks to ever-improving generative AI models, you can skip that step.

All it takes to create interactive language games is a good set of prompts!

Generative AI is an uncanny fit for language learners and teachers, who quickly realised how useful it could be for authentic(ish) text creation. But it doesn’t have to be static. By specifying the kind of features you want in a prompt, you can come up with great self-contained digital ‘worksheets’ with self-marking activities.

It’s possible to go well beyond this – into actual interactive gaming. Today’s generation of AI platforms are capable of taking your brief, then coding it up efficiently and intelligently as a working game, without any further input from you.

Now, if you can imagine it, you can make it.

Language Tetris

Let’s take a classic gaming example: a version of Tetris with a language learning twist. Blocks fall from the top of the screen, labelled with a word in either German or English. Students must manoeuvre the blocks with the arrow keys in order to land German-English equivalents together, whereupon they pop and disappear from the stack. The game speeds up as students progress; the aim is to prevent the blocks from stacking to the top for as long as possible.

It’s fun, and fantastic for improving recall with a set of vocab items.

An AI-generated interactive language learning game. Blocks fall from the top of the screen - the student must match them and avoid them piling to the top.

An AI-generated interactive language learning game. Blocks fall from the top of the screen – the student must match them and avoid them piling to the top. (Pictured is a ‘boom’ block that gives the students a lifeline!)

You can play a working version of it here, and you’ll see what I mean: it’s fun, it gets quite fast and furious, and it does a great job of drilling words. It may not look particularly pretty in its current state, but it’s completely playable; with a bit of visual sprucing, it wouldn’t look out of place on any language learning website.

It’s the kind of thing that would make a nice intermediate coding challenge for someone learning web app development. Maybe a weekend project, or something to do across a series of evenings.

But it took just a few minutes with ChatGPT.

Prompting for Language Games

Here’s the prompt I used for the initial version (and you’ll see some similarities with the interactive worksheet prompt, too):

Let’s create a language learning game in JavaScript, completely self-contained on a single HTML page. It will be like Tetris, adapted for language learning as follows:
– blocks will have either a German or an English word on them from a pot of ten vocabulary items on the topic ‘Clothing’
– blocks will descend from the top of the screen
– as they fall, students use the left, right and down arrows to manoeuvre the blocks before they land
– if a matching German block and English block touch (above, below or to the side), they go POP and disappear – and the game speeds up slightly
– ensure that ‘gravity’ is respected, so if there are blocks above one that ‘pops’, they fall into place accordingly
– the aim is to avoid the blocks stacking up to the top
– every few blocks (maybe every 5-10 at random), a ‘boom’ block falls that ‘pops’ every block it touches on landing (just to clear the space and make it a bit easier)

If you pop this into Claude Sonnet 3.5 right now – as long as you have Artifacts turned on – you should be able to play what comes up straight away. If you’re using ChatGPT or another platform, there’s an extra (easy-ish) step to do before you can play: you just need to save your code in some text editor as an HTML file.

Code output from a prompt in ChatGPT

Code output from a prompt in ChatGPT

Live Preview – Without Claude’s Artifacts

In fact, one free editor for coding – Phoenix Code – also shows you a live preview of the page working as you paste the code in, Claude Artifacts-style. If you really get into language games generation with AI, it’s well worth a download.

Using Phoenix to save and preview AI-generated language games

Using Phoenix Code to save and preview AI-generated language games

One important caveat: your game may well not be perfect on the first go. It might have a bug or two – AI might have missed the point occasionally. My initial version of Language Tetris, for example, allowed students to move the block across existing columns, unlike in the classic game.

But by prompting and re-prompting, requesting tweaks and changes as you go along, you can produce some amazing results. Change the styling, add features, include fiendish rules of play.

The sky’s the limit.

Pulling It All Together

Once you’re done with one game, it can serve as a template for others. It’s usually clear in the code where to change the vocabulary items to something else. Just change, Save As… a new filename, and build up a library of topical games.

A snippet of code produced by ChatGPT

It’s usually clear from a glance at the code where you can change the vocabulary.

In terms of styling, these games do tend to be graphically quite simple. That said, you can easily prompt for more visually appealing elements. And why not use a AI image generation tool like Bing to make some more attractive graphics to integrate into your creations?

Finally, you might be wondering if educational games developers like me are feeling a bit… well, put out by all this. My answer is a resounding not at all! If anything, AI code generation is a brilliant proof-of-concept, prototyping tool to try out new gaming ideas before setting fingers to keyboard. It’s incredibly useful to test if something will really work before pouring hours into coding it.

And of course, you can pick up with your own skills where AI leaves off, to create something even more special with that irreplaceable human touch.

Have you been using AI as your own coding assistant? Let us know in the comments what you’ve been creating together!

A robot reading a script. The text-to-speech voices at ElevenLabs certainly sound intelligent as well as natural!

ElevenLabs Voices for Free, Custom Language-Learning Material

There’s been a lot on the grapevine of late about AI-powered leaps forward in text-to-speech voices. From providing accent models to in-depth speaking games, next-gen TTS is poised to have a huge impact on language learning.

The catch? Much of the brand new tech isn’t available to the average user-on-the-street yet.

That’s why I was thrilled to happen across TTS service ElevenLabs recently. ElevenLabs’ stunning selection of voices powers a number of eLearning and audiobook sites already, and it’s no hype to say that they sound as close to human as you can get right now.

Even better, you can sign up for a free account that gives you 10,000 characters of text-to-speech conversion each month. For $5 a month you can up that to 30,000 characters too, as well as access voice-cloning features. Just imagine the hours of fun if you want to hear ‘yourself’ speak any number of languages!

Using ElevenLabs in Your Own Learning

There’s plenty to do for free, though. For instance, if you enjoy the island technique in your learning, you can get ElevenLabs to record your passages for audio practice / rote memorising. I make this an AI double-whammy, using ChatGPT to help prepare my topical ‘islands’ before pasting them into ElevenLabs.

The ChatGPT > ElevenLabs workflow is also brilliant for dialogue modelling. On my recent Sweden trip, I knew that a big conversational contact point would be ordering at coffee shops. This is the prompt I used to get a cover-all-bases model coffee-shop convo:

Create a comprehensive model dialogue in Swedish to help me learn and practise for the situation “ordering coffee in a Malmö coffee shop”.

Try to include the language for every eventuality / question I might be asked by the coffee shop employee. Ensure that the language is colloquial and informal, and not stilted.

The output will be pasted into a text-to-speech generator, so don’t add speaker names to the dialogue lines – just a dash will suffice to indicate a change of speaker.

I then ran off the audio file with ElevenLabs, and hey presto! Custom real-world social prep. You can’t specify different voices in the same file, of course. But you could run off the MP3 twice, in different voices, then splice it up manually in an audio editor like Audacity for the full dialogue effect. Needless to say, it’s also a great way for teachers to make custom listening activities.

The ElevenLabs voices are truly impressive – it’s worth setting up a free account just to play with the options and come up with your own creative use cases. TTS is set to only get better in the coming months – we’re excited to see where it leads!

ChatGPT French travel poster

A Second Shot at Perfect Posters – ChatGPT’s Image Tweaker

The big ChatGPT news in recent weeks is about images, rather than words. The AI frontrunner has added a facility to selectively re-prompt for parts of an image, allowing us to tweak sections that don’t live up to prompt expectations.

In essence, this new facility gives us a second shot at saving otherwise perfect output from minor issues. And for language learning content, like posters and flashcards, the biggest ‘minor’ issue – the poor spellings that crop up in AI image generation – makes the difference between useful and useless material.

Rescuing ChatGPT Posters

Take this example. It’s a simple brief – a stylish, 1950s style travel poster for France. Here’s the prompt I used to generate it:

Create a vibrant, stylish 1950s style travel poster featuring Paris and the slogan “La France”.

I wanted the text “La France” at the top, but, as you can see, we’ve got a rogue M in there instead of an N.

ChatGPT generated image of a French travel poster

To target that, I tap the image in the ChatGPT app. It calls up the image in edit mode, where I can highlight the areas that need attention:

ChatGPT image editing window

Then, I press Next, and can re-prompt for that part of the image. I simply restate the slogan instructions:

The slogan should read “La France”.

The result – a correct spelling, this time!

ChatGPT French travel poster

It can take a few goes. Dodgy spelling hasn’t been fixed; we’ve just been given a way to try again without scrapping the entire image. Certain details also won’t be retained between versions, such as the font, in this example. Others may be added, like the highly stylised merging of the L and F in the slogan (a feature, rather than a bug, I think!).

But the overall result is good enough that our lovely 1950s style poster wasn’t a total write-off.

Another case of AI being highly imperfect on its own, but a great tool when enhanced by us human users. It still won’t replace us – just yet!

Image tweaking is currently only available in the ChatGPT app (iOS / Android).

An illustration of a robot scribe writing AI prompts for ChatGPT or Gemini

Power to the Prompts : Fave Tweaks for AI Worksheets

Content creation is what AI excels at. That’s a gift to language learners and teachers, as it’s the easiest thing in the world to create a set of prompts to run off original, immersive worksheets.

AI isn’t great at everything, though, which is why our prompts need to tweak for its weaknesses – the things that are obvious gotchas to language folk, but need explaining to a general assistant like AI. Fortunately, in most cases, all you need is an extra line or two to put it right.

Here are five of my favourite prompt-enhancers for worksheets, covering everything from vocab to copyright!

Five Tweaks for Perfect Prompts

Cut Out the Cognates

Cognates are generally great for language learners. As words that are instantly recognisable, they’re extra vocab for free. But for that very reason, they’re not the ones that worksheets should be making a song and dance about. It’s not particularly useful, for example, to have “der Manager” picked out in your German glossary as a key word. Yes, I worked that one out!

Try this in your vocab list prompts, bearing in mind that not all platforms will work equally well with it (Gemini aced it – ChatGPT sometimes gets it):

Don’t list items that are obvious English loanwords or cognates with English.

Highlight the Good Stuff

You know what I mean by the good stuff – those structures and snippets of languages that are really frequent, and really reusable. I like to call them sentence frames – you can learn them, and switch in other words to add to your own linguistic repertoire.

You can ask AI to draw attention to any really pertinent ones in your target language texts:

Highlight (in bold and italics) the most pertinent key words and phrases for the topic, and provide a brief glossary of them at the end.

Make It Colloquial

Vanilla AI can sound bookish and formal. That’s no good as a model for everyday speech, so polish your prompts with a wee push to the colloquial:

Make the language colloquial and idiomatic, in the style of a native speaker.

Include an Answer Key

It might seem obvious, but if you’re making materials for self-study, then you will find an answer sheet indispensable. It’s an often overlooked finishing touch that makes a worksheet truly self-contained:

Include an answer key for all questions at the end.

Covering Your Back With Copyright

Copyright issues have been bubbling in the background for LLMs for some time now. They produce texts based on vast banks on training data, which isn’t original material, of course. But in theory, the texts that pop out of it should be completely original.

It can’t hurt to make that explicit, though. I like to add the following line to prompts, especially if I’m intending to share the material beyond personal use:

Ensure that the text is completely original and not lifted directly from any other source.

 

What are your favourite tweaks to make perfect prompts? Let us know in the comments!

An image of a robot struggling with numbreed blocks. AI has a problem with random ordering.

Totally Random! Getting Round AI Random Blindness in Worksheet Creation

If you’re already using AI for language learning content creation, you’ve probably already cried in horror at one of its biggest limitations. It’s terrible at putting items in a random order.

Random order in language learning exercises is pretty essential. For instance, a ‘missing words’ key below a gap-fill exercise should never list words in the same order as the questions they belong to.

Obvious, right? Well, to AI, it isn’t!

Just take the following prompt, which creates a mini worksheet with an introductory text and a related gap-fill exercise:

I am learning French, and you are a language teacher and content creator, highly skilled in worksheet creation.
Create a French worksheet for me on the topic “Environmentally-Friendly Travel”. The language level should be A2 on the CEFR scale, with clear language and a range of vocabulary and constructions.
The worksheet starts with a short text in the target language (around 250 words) introducing the topic.
Then, there follows a gap-fill exercise; this consists of ten sentences on the topic, related to the introductory text. A key content word is removed from each sentence for the student to fill in. For instance, ‘je —— en train’ (where ‘voyage’ is removed).
Give a list of the removed words in a random order below the exercise.

The output is very hit and miss – and much more miss! Perhaps 90% of the time, ChatGPT lists the answer key in the order of the questions. Either that, or it will produce feeble jumbling attempts, like reversing just the first two items on the list.

AI’s Random Issue

One prompt-tweaking tip you can try in these cases is SHOUTING. Writing this instruction in caps can sometimes increase the bullseyes. Put them IN RANDOM ORDER, darn it! It doesn’t help much here, though. It just doesn’t seem worth relying on Large Language Models like ChatGPT to produce random results.

The reason has something to do with the fundamental way these platforms function. They’re probability machines, guessing what word should come next based on calculations of how likely word X, Y or Z will be next. Their whole rationale is not to be random; you might even call then anti-random machines.

No wonder they’re rubbish at it!

A Road Less Random

So how can we get round this in a reliable way that works every time?

The simplest fix, I’ve found, is to find another, non-random way to list things differently from the question order. And the easiest way to do that is to simply list things alphabetically:

I am learning French, and you are a language teacher and content creator, highly skilled in worksheet creation.
Create a French worksheet for me on the topic “Environmentally-Friendly Travel”. The language level should be A2 on the CEFR scale, with clear language and a range of vocabulary and constructions.
The worksheet starts with a short text in the target language (around 250 words) introducing the topic.
Then, there follows a gap-fill exercise; this consists of ten sentences on the topic, related to the introductory text. A key content word is removed from each sentence for the student to fill in. For instance, ‘je —— en train’ (where ‘voyage’ is removed).
Give a list of the removed words in alphabetical order below the exercise.

The likelihood of this order being the same as the questions is minimal. Hilariously, AI still manages to mess this order up at times, adding the odd one or two out-of-place at the end of the list, as if it forgot what it was doing, realised, and quickly bunged them back in. But the technique works just fine for avoiding the order giving the answers away.

A simple fix that basically ditches randomness completely, yes. But sometimes, the simplest fixes are the best!

Random blindness is a good reminder that AI isn’t a magical fix-all for language learning content creation. But, with an awareness of its limitations, we can still achieve some great results with workarounds.

Parallel text style learning, like Assimil courses, can be a great way to improve your fluency.

DIY Assimil : Parallel Text Learning with ChatGPT

Assimil language learning books are hugely popular in our polyglot community. And for good reason – many of us learn really effectively with its parallel text method.

They’re especially userful when the base language is another of our stronger languages, adding an element of triangulation. I learned a heap of Greek vocabulary from the French edition Le Grec sans Peine, at the same time as strengthening my (ever slightly wobbly) French.

Now, Assimil is already available in a great range of language pairs. But it’s not always a perfect fit. For example, some editions are more up-to-date than others. More off-the-beaten-track languages still aren’t available. And at times, you can’t find the right base language – no use learning Breton through French, if you don’t have any French.

Enter ChatGPT (or your alternative LLM of choiceBing also does a great job of these!).

DIY Assimil Prompting

Copy and paste this into your AI chat, changing the language (top), translation language (middle) and topic (bottom) to suit.

You are an expert creator of language learning resources. I want to create some text-based learning units for beginner Malay learners (level A0/A1 on the CEFR scale). The units follow the parallel text approach of the well-known Assimil language learning books.

Each unit has a text in the target language (about 250 words) on a specific vocabulary topic. It should be narrative, talking about how the topic relates to an everyday person. It should be divided into logical paragraphs. After each paragraph, there is an English translation of that paragraph in italics.

The text should be written in very clear, simple language. The language must read like a native speaker wrote it, and be error-free and natural-sounding. Source the info for the text from target language resources online, making it as up-to-date and authentic as possible. It should be completely original and not copied or lifted from any other source directly.

After the text, there is a glossary list of the key topic words from the text, sorted alphabetically and grouped by parts of speech (nouns, verbs, adjectives, adverbs etc.).

Are you ready to create some content? The first topic is: Mobile Technology

This prompt creates a prose-based parallel text unit. However, if you prefer dialogue-style texts, simply change the second paragraph of the prompt:

Each unit has a humorous dialogue in the target language (about 20 lines) on a specific vocabulary topic. The dialogue should relate the topic to everyday speakers through colloquial, idiomatic language.

The prompt works a treat in both ChatGPT Plus (paid) and Microsoft Bing (free). I also got very useable results in the free version of ChatGPT and Claude 2. It works so well as the focus is purely on what LLMs do best: spooling off creative text.

How Do I Use Them?

So, with your shiny, new Assimil-style units spooled off, what do you do with them?

Personally, I like to copy and paste the output into the notes app on my phone. That way, they make nice potted units to browse through when I have some spare moments on the bus or train. They’re equally handy copy-pasted into PDF documents that you can annotate on your phone or tablet.

Parallel text for Malay language learning created by AI

Parallel text in Malay and English created by AI

In terms of real-world use, the self-contained, chatty texts typically created make perfect material for the islands approach to improving spoken fluency. Create some units in topics that are likely to come up in conversation. Then, spend some time memorising the phrases by heart. You’ll be able to draw on them whenever you need in real-life conversation.

Enjoy prompts like these? Check out my book AI for Language Learners, which lists even more fun ways to get results without paying hefty course book price tags!

ChatGPT releases custom GPT models

ChatGPT, Your Way : Custom GPTs In The Wild!

This week saw one of the biggest recent developments in consumer AI. ChatGPT released GPTs – customisable AI bots – into the wild for Plus members, and the community has gone wild.

In a nutshell, GPTs are AI bots with custom behaviour that you define. And you define that behaviour using natural language, just like how you talk to regular ChatGPT.

Crucially, GPTs are shareable. So you can come up with a killer app idea, set it up in seconds, then share your creation with the world. Already, linguists and language lovers are sharing their creations on the socials.

ChatGPT for Worksheet Creation

Obviously, I couldn’t wait to get playing when the GPT creation tool went live this week. I’ve long been a cheerleader for topic-based units for independent study, especially when preparing for spoken lessons. So the first thing I coded up was a foreign language worksheet creator!

It’s the kind of thing I’ve been writing and sharing prompts about for a while, now. The big game-changer, of course, is that now, all that functionality is packaged up into a single, one-click module. Open it, tell it your language, topic and level, and watch it go. This will produce a range of resources and activities for independent learning, including a vocabulary list, reading comprehensions, and cloze quizzes.

Genuinely useful for self-study!

Foreign Language Worksheet Creator GPT in ChatGPT

Foreign Language Worksheet Creator GPT in ChatGPT

It’s already been a learning experience, for all of us tinkerers. For one thing, I found out not to overload it by trying to do too much at once, or turning on all its capabilities (browsing, code interpretation and image creation). I ended up with a uselessly slow initial version that I can no longer even reopen to edit.

Ah well – these things make us!

Old English Monkeys

When you do get a working version, however, you can boggle at the versatility of it. That’s thanks to the billions of training points backing up the platform. I asked it to create an Old English worksheet on the topic “Monkeys”, in the style of a Modern Languages worksheet, as a cheeky wee test. Admittedly, ChatGPT did say that it would be a challenging task. After all, just how many Old English documents do researchers train their LLMs on? But the results were really not bad at all…

An Old English worksheet in ChatGPT

An Old English worksheet in ChatGPT

 

I expect many of us are playing these games, pushing the new tech to see how far it can go. At the very least, we can all revisit those isolated prompt ideas we’ve been collecting over the past months, and turn them into shareable GPTs – for work and for fun.

Have you had chance to play yet? Share your proud creations with us in the comments!

A digital brain, complete with memory - ChatGPT take note!

Your ChatGPT Teacher – With Persistent Memory!

The interactivity of AI models like ChatGPT and Bing make them the perfect medium for exchange-based language learning. But for one thing: their lack of persistent memory.

The standard setup, to now, has been for a ‘black box’ style conversation on AI platforms. You initiate a session with your instructions, you chat, and it’s over. You can revisit the conversation in your history, but as far as AI is concerned, it’s lost in the mists of time.

It’s something that throws a mini spanner in the works of using AI for language (or any kind of) learning. Teaching and learning are cumulative; human teachers keep records of what their students have studied, and build on previous progress.

DIY ChatGPT Memory

There seems to be little movement in the direction of AI with memory amongst the big platforms, although OpenAI’s recent announcement of memory storage for developer use might lead to third-party applications that ‘remember’. But in the meantime, users within the AI community, ever adept at finding workarounds and pushing the tech, have begun formulating their interim alternatives.

One clever way around it I recently spotted takes advantage of two elements of ChatGPT Plus: custom instructions and file upload/analysis. In a nutshell, an external text file serves as ChatGPT’s ‘memory’, storing summarised past conversations between student and AI teacher. We let ChatGPT know in the custom instructions that we’ll be uploading a history of our previous conversations at the beginning of a learning session. We also specify that it analyse this file in order to pick up where we left off. At the end of each session, we prompt it to add a round-up of the present conversation to that summary, and give the file back to us for safekeeping.

Custom Instructions

Here’s how I’ve worked the persistent memory trick into my own custom instructions:

If I upload a file ‘memory.txt’, this will be a summary of our previous conversations with you as my language teacher; you will use this to pick up where we left off and continue teaching me. When prompted by me at the end of our session, update the file with a summary of the present conversation and provide me with a link to download it for safekeeping. This summary should include a condensed glossary of any foreign language terms we’ve covered.

Wording it as such makes memory mode optional; ‘teacher remembering’ only kicks in if you upload memory.txt. This way, you can otherwise continue using regular, non-teach ChatGPT without any fuss.

The only thing that remains is to create a blank text file called memory.txt to start it all off. Remember to start a new chat before giving it a whirl too, so your new custom instructions take. As you use the technique in your everyday learning chats, you’ll see memory.txt blossom with summary detail. As an offline record of your learning, it even becomes a useful resource in its own right apart from ChatGPT.

Just make sure you keep it safe – that’s your teacher’s brain you have right there!

A page of conversation summaries - my ChatGPT 'memory' file in action.

My ChatGPT ‘memory’ file in action.

Let us know your experiences if you give this technique a go! And if you’re stuck for lesson ideas, why not check out my book, AI for Language Learners?

AI for Language Learners by Rich West-Soley; ChatGPT, Bing and more for your languages study

AI for Language Learners – Book Now Available!

It was a labour of love that happily took up most of my summer, and it’s finally out! I’m very chuffed to announce that my book AI for Language Learners is available on all Amazon stores.

 

The book is the product of months of tweaking, prodding and experimenting with emerging AI chat platforms. If you’re a Polyglossic regular, you’ll have seen some of those nascent techniques appear on the blog as I’ve developed and used them in my own learning. The blog has been a bedding ground for those first book ideas, and I’m thankful to everyone who has followed along with my own AI journey.

What we’ve come to call AI are, strictly speaking, actually large language models (LLMs). These LLMs arise from billions of words of training material – truly staggering amounts of data. The resulting super-text machines are perfect matches for subjects that benefit from a creative flair with words, and as language learners, wordplay is our currency. The book contains over 50 rich prompts for getting the absolute most out of AI’s impressive capacity for it.

The process has been huge fun. Of course, that’s thanks largely to the often unintentional humour our non-sentient friends ChatGPT, Bing and others. I try to get this across in the book, which has its fair share of lighthearted moments.

I hope you have as many smiles trying the recipes out as I did putting them together!

AI for Language Learners is available on Amazon Kindle (UK £2.99, US $2.99) or in paperback (UK £7.99, US $7.99). Even better: if you’re a Kindle Unlimited member, you can download and read it as part of your subscription.