PLAY WORDS. INFINITELY.

What do we need? We need word use examples. We need them current. We need them tailored. We need them now.

‘Artificial’ once meant skilled creation. Did you know? The Ancient Greeks divided knowledge into two types: episteme (the theory, or, in today’s terms, ‘I’ll tell you why you should press that AI button in class’) and techne (the practice, or ‘fine, I’ll build the button for you’). The records don’t mention a third, in-between knowledge type, or the how-to-press-the-button-somebody-else-built variety so common today, but I digress. Art was considered techne as well, which makes sense: to create something ARTificial, you had to be a skilled and experienced master.

In the process, the art part somehow disappeared, and nowadays the word mostly means something unnatural or fake. Thanks to the mindless automation of everything under the motto ‘save time to waste it efficiently later’, the skills-and-experience part also seems to be fading. Yet with large language models generating content on the fly, I suspect artificial is about to mutate again, this time toward something instant, adaptive, and alive only in the moment. Well, life is dynamic, everything changes, and we react…eventually.

Speaking of changes, some time ago my coauthor (and great friend) and I decided to revisit our Business English/ESP coursebook series. We hadn’t touched them in a while, both busy with other projects, and wanted to dust them off to see which bits and pieces were still relevant. They felt outdated, to say the least. You know that feeling when you open your old grammar textbook: good, but gramophone-kind of good, frozen in a different time. I know many teachers share this sentiment (see Eva’s CTRL+ALT+DEL Your Old Grammar Sentences). So I thought it would be a good idea to add some current examples, to change horses for a SpaceX ship, so to speak.

Then I started thinking about dynamic changes: content that adapts to time, context, and the user, instantly. Exactly the kind of thing large language models can help deliver. And that’s how my Wordsplainer was born.

A bit of art, making word exploration visual and turning words into draggable graphs (dragging doesn’t replace pen and paper, which learners should use if they want to really remember words, but is anyway better than just reading static content). A bit of skill, showing nuances of words, not just dumbed down definitions, including forms, contexts where the words occur, combinations, synonyms, and the like. A bit of tailoring, content adjusted to proficiency level (lower-higher), register (conversational, business, or academic), and age (teens or adults, for now). Settings are adjustable anytime, so lower-level versions can be used as a scaffold.

This isn’t a dictionary, and it’s not trying to be. It’s a word playground: click a node, read examples, copy what you like, and keep exploring.

Well, I wouldn’t be me if I didn’t try to gamify the experience (there are plenty of WORD GAMES on the blog already). To make word exploration more fun and get language enthusiasts aka learners thinking strategically and in broader contexts about words (forms, collocations, synonyms, you name it), I added the Word Path Challenge, a mix of Word Ladder and the Wikipedia Game. The goal: start with one word and reach the target by clicking through nodes and text strings (yes, all strings, even examples, are clickable), with each user choosing their own unique path, linking words and word aspects that didn’t seem connected at first. Serious fun.

Welcome to my playground, where artificial adapts, and words graph.

I hope you have as much fun exploring it as I had building it.