Mnemonics

More about language games

Posted by Shai Shapira on November 21, 2012
Posted in: Games, Languages, Mnemonics, My Games. Tagged: , , . Leave a Comment

In the previous post I said that if the Serpent Scribe of Kyoto was a success, I’ll try to continue making language-learning games. Unsurprisingly, I couldn’t help myself and didn’t wait for it to succeed. I’ve been working on some nice things that might become available soon.

I think it’s really an interesting experience with some lessons to be learned about memory and learning. I’ve tried several alphabets with the Serpent Scribe, and I think I can say that about 30 minutes with a game like this can bring me from knowing nothing in an average alphabet, to knowing it all. However, if I stop there, I’ll forget it all about an hour later. So the next challenge would be retaining the knowledge. This brings me back to what I asked a long time ago about mnemonics – if they can help us learn so much in such a short time, can we use them repeatedly and learn an entire language in a month?

It seems like the way to retain such information is to create associations – see the information in as many contexts as possible, not just in the simple flashcard or dictionary entry. One of my favourite examples is music – I’m often amused by how my vocabulary in languages I don’t know is affected by my favourite bands in the language – in German I can speak of death and blood, but I can’t ask what time it is. In Hungarian I can talk about flowers and birds, but not much else. In Portuguese about forests and hunters, in Indonesian about love and spirituality, and so on.
The Serpent Scribe starts working on it by providing challenges – chances to use the symbols learned in new contexts. But more work is needed.

This is why I think most structured language learning methods are useless on their own – I think the best way is to drown yourself in a huge array of different methods, each one bringing new associations to pick up new words from. But more importantly, I think you need to learn the language while doing something other than language learning – associations need to be between two things, so there has to be something else happening while you’re learning. It could be an especially frustrating level in a game, could be an awesome guitar chord in a song, or anything else. So my goal is to make games that are fun on their own, and as a side effect make you encounter loads of different words in the language you’re learning. We’ll see if I can make that happen.

The Memory Game

Posted by Shai Shapira on February 28, 2012
Posted in: Languages, Mnemonics, My Games. Tagged: , . Leave a Comment

As you might remember from past posts, I have some interest in memory improvement techniques. Also you might remember, I’ve been learning Chinese for the past few months[1].

One of the most important things in learning something (like memory techniques, or a language) is using it, practicing it. Getting short-term goals to achieve, instead of just sitting and studying for the very long term goal of “learning it completely”. So how can we make short term practice goals for those things?

If you know me, you’re already guessing that the answer is some sort of game. Here’s a little something I’ve been working on in the past few days:

Basically, it’s the old game known (among other names) as Concentration. Each pair of cards is a Chinese character and its definition, thus every game is a chance to practice my Chinese character vocabulary. As the board gets bigger, it starts making sense to bring in memory techniques – On a huge board, there is little chance to remember all cards intuitively, so it’s a good way of practicing that as well.

Of course, I never see a game without thinking, “how can we make this more complicated”? Here’s what I’ve been thinking:

Make a new game, that is a combination of Concentration and collectible card game. Each player builds their own deck of cards from the set of all available ones, and the game starts with each player laying their cards face down in front of them. Each player, in turn, flips two cards – could be their own or the opponent’s. So far, sounds pretty much like ordinary concentration.
The twist – whenever you flip two identical cards of your deck, you get to use those cards. Each card has a function, like in Magic: The Gathering and similar games. Basically, it’s like playing a Magic-style collectible card game, but instead of drawing your cards randomly from your deck, you get them by remembering. I think it’s a nice addition, it’s probably going in the list of “things to develop one day”. But not very soon.

[1] At least officially, in reality it’s been pretty much on hold for quite a while.

Computational Mnemonics

Posted by Shai Shapira on October 24, 2011
Posted in: Mnemonics. 1 comment

I’ve been mostly working on two things lately – finishing my next game, and learning the Chinese language. While the former might sound more computation-related, there are some interesting things to note about the latter.

The main challenge in learning Chinese is[1], of course, mastering the huge amount of characters. Having a long interest in memory improvement techniques, I decided to try using those to help. Basically, I’m using a home-made variant of the peg system, where each symbol that can appear in a chinese character gets a peg. So far it seems to be working fairly well – I’m pretty sure my vocabulary has been increasing quite rapidly since I started[2].

And this makes me wonder about the possibilities of it. How long should it take to memorize, say, 2,000 characters and their meanings? Using ordinary methods, the answer seems to be a long, long time. But if we look at it from a pure, information-theory point of view, is that justified? It took me about a week of somewhat-intensive reading to finish “Moby Dick”. How much information did I get from it, compared to the amount of information in a Chinese dictionary? And what about a 90 minute movie? Does the fact “Indiana Jones is an archaeologist who wears a hat” contain less information than “白 represents the color white”? My guess is no, and that means that watching such a movie gives me the equivalent of a huge boost to my vocabulary, but it gets spent on less useful information. If this is the case, all that remains is to find a proper translation between the information I want to get (i.e the meaning of, say, 2000 Chinese characters) and information I can easily remember. This is exactly what the peg system does, but maybe it’s not enough. Could there be a stronger system? Maybe the science fiction idea that we could “upload” a large body of information immediately to our brains is not that far from being possible – it might not take a few second like some cybernetic implant from a movie, but if we could maintain our maximum rate of information absorbing and limit it to the information we want – I’m not sure learning an entire language’s vocabulary[3] in a month is that far fetched.

As far as I know, there’s not much research into it. There are world memory competitions, but all I could find about it were repeating discussions of the same few known methods. What I haven’t seen so far, is an examination of it from a computer science perspective – which is odd, because I think it is obviously a branch of computer science – it has the same need for data structures and algorithms, the only difference is that instead of running the algorithms on electrical microchips, we run them in our brains. But the link system and the peg system are the same linked list and array[4] we know from our computers. What we need is to write algorithms that are better suited for our brain’s hardware – dealing less with performance speed, and more with reliability, as our C array isn’t likely to suddenly forget what was in cell 2, but for our brain’s array this is the main concern.

Hopefully I’ll find some interesting results.

[1] As far as I know, being still in early stages.
[2] My new favourite word: 伥 (chāng), which my dictionary defines as “Ghost of somebody devoured by a tiger who helps the tiger devour others”.
[3] Of course, there are several ways to define “learning” a vocabulary. Being fluent in a language includes a wide array of vaguely defined associations you have for each word that such learning will not get you. But a “robotic” dictionary translation available in your brain for each word is a huge step forward.
[4] Interestingly, while computers generally use arrays and linked lists as the basic, “native” data structures, and implement other data structures with them, the peg system uses a map to implement the array, implying that our basic data structures in brain algorithms are the linked list and the map.