I spent a little time this morning looking into a language learning app I hadn’t heard of before. It’s called Learning with Texts, and it lets you import texts and learn additional vocabulary terms from the the article or excerpt.
Overall, I love the theory behind the application. It lets you learn words through experiencing them, giving you definitions only as you need them. However, there are some issues I have with it, which I’ll note as I describe the app.
First, you need to find the application. The first information I got from it directed me to the link for downloading and installing the application. Great, right? Well, yes, but only if you intend to install it on a server. This download, from SourceForge, I discovered fairly quickly, requires quite a bit of work. Now, I don’t necessarily mind getting a little technical, but this really is a barrier for most users.
Luckily, I also discovered that Benny from Fluent in 3 Months has hosted this application and made it available through his blog. You can use it at fi3m.com/lwt for free, but you need to sign up for an account. Problem solved!
Once logged in, the application presents you with a menu. I found that the interface was really not all that intuitive, nor is it particularly exciting. I’m a fan of simple layouts, but this seems more a case where a plan for simplicity wasn’t fully developed, resulting in an appearance of clutter.
To get started, you need to go to My Languages and enter your settings. While advanced settings are immediately available (which I feel may unnecessarily intimidate many users, but is nice if you want to specify your own dictionary), you really only need to use the Language Setup Wizard to set your native language (L1) and learning language (L2), then save. You’re ready to get started.
Once that is done, you can go back to the menu and click My Texts. From here you can copy in any text in any of your chosen languages. I chose this short article, from a Hungarian news site, about a 4-car collision.
You can now open this text in the application’s text window. From here you can click on a word to see a list of definitions pulled from the dictionary that the Language Setup Wizard assigned to the language.
Here is where I found other issues. Hungarian is a language that is very suffix- and, to a lesser extent, prefix-heavy. The dictionary used by default has no reference for these words, or, it seems, for many adjectives formed by adding -i. It also doesn’t include conjugations. This may be the fault of the dictionary used, but honestly that’s probably pretty normal for any dictionary. I found that I very frequently had to use the “GTL” button (again, not particularly intuitive) in the middle of the right side of the panel to access Google Translate. Additionally, multi-word phrases require you to select all of the words in order to find the definition, and if you don’t know you’re looking at a definable phrase you won’t know that you need to do this. It may help to put the whole article through Google Translate at some point to find this, but I may be out of luck for this particular text – Google Translate (or almost any translator I’ve seen, for that matter) doesn’t have an easy time with Hungarian.
Once you determine the definition of the word, however you do so, you can add it as the definition referenced by the text and save that reference. Fortunately, definitions that you manually add are stored, so you can build your own working dictionary eventually.
As you check each word, you can mark them as one you know well or rank them according to how comfortable you are with them. Personally, I prefer an application that sets these rankings for the user based on the number of times it has been defined correctly, but this application relies more on self-reporting, and I’m not sure that it really could be automated more. Eventually, you will get through the article and end up with a screen that is color-coded according to how well you know the word. Words you know well are green, and shades from yellow to red indicate words you are still learning. Blue means that you have not yet evaluated that word.
This color code system reminds you that this is a word you have seen before and to reevaluate how well you feel you know it. As you enter a new text, words that you have already seen are highlighted in the same way as you indicated before, so your attention is drawn to words you need to look a little harder at. It also, and this is the fun part for me, tests you later.
The day after uploading your text, a test is available for the terms in the article. It will present you with sentences from the text with a highlighted word, and you have to answer whether you know it or not.
Your answers change the initial ranking of the word and, I assume, how often it shows up in tests. The word will be added back into tests if you encounter it in another text and don’t recognize it. This is a little closer to automation and accountability, but it still does rely heavily on user self-reporting to determine the rate of learning.
Overall, I do like this app, and here is why:
- It’s not the most intuitive interface ever, but the learning curve isn’t bad at all.
- While it does require a larger initial time investment to get many words in your database, eventually that part will be over.
- Self-reporting isn’t a huge problem for most people who would use it, as you are motivated to learn and have no one to be accountable to but yourself; I just wouldn’t recommend its use with children unless you can directly supervise.
- The concept of seeing the words in context means learning grammar and usage, not just memorizing vocabulary.
- The option to upload an audio file with the text helps increase listening comprehension in the language.
However, I’m not yet sure if it will become one of my favorites. I feel like the time investment at the beginning is a bit of a barrier. I’m going to push through, though, and see where I get.