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When it comes to foreign languages, blended learning—combining technology with human instruction—is better than computer learning or human instruction alone.
Here at Transparent Language, we design products for schools and institutions not to replace teachers, but to leverage face-to-face instruction. Supported by our own research and experience, we firmly believe in a blended learning method called declarative acceleration.
To put it simply, declarative acceleration is a way of using technology to do what technology does best, using teachers to do what teachers do best, and skillfully merging the two.
There are two big aspects of language that ultimately need to work together for successful language acquisition. We call them declarative knowledge and procedural knowledge, but we’re just talking about vocabulary and phrases on the one hand, and language skills on the other.
A crucial part of language capability is learning lots of words, phrases and various other small chunks of the language. In fact, studies have shown that, of all the factors contributing to language proficiency, vocabulary size is by far the single most significant factor, accounting for anywhere from 50% to 70% of proficiency gains depending on the language and the skill being studied. Whether you find learning words and phrases game-like and fascinating or redundant and boring, at the end of the day, you can’t do language without vocabulary.
Of course, language is much more than just vocabulary. “Fluency” is a rubbery term, but we know it when we hear it: using native-like word order, choosing the right words and level of formality, speaking at a normal, native speed—these are the necessary and beautiful skills of language.
What we all want—learners and teachers alike—is to achieve higher proficiency levels, complete with a robust vocabulary, as quickly and successfully as possible. Declarative acceleration is the best way we know to do that.
Imagine a classroom lesson about going to go to the grocery store, ordering from the deli section and chatting with the cashier at checkout. We know we want class time to be exciting, uplifting, and useful. A good teacher will set up a variety of interesting, challenging, enjoyable, pedagogically valuable tasks, peer activities, communicative activities, etc. to support this lesson.
We first ask ourselves, what declarative knowledge (words, phrases and small chunks of language) would a learner need in this situation? We then collect and strategically organize that declarative material, and deliver it to the learner using our technology.
It turns out that if you want to, for instance, memorize the table of chemical elements, a good computer program can help you do that much faster and more reliably than even the best chemistry teacher. The computer can quickly build mental associations between, for instance “H” and “hydrogen” or “W” and “tungsten” with displays, games, and learning activities of all kinds. The computer can present dozens of learning encounters per minute, watch what is done right and what is a problem and continually adjust. A teacher couldn’t easily do that as quickly, in a fast-paced, fully individualized way with even one student, never mind five or ten.
The same is true for vocabulary, words, phrases and other memorized language chunks. So we use the computer to do what the computer does best. If this type of declarative learning is available for every lesson, the learner will likely build a robust vocabulary that is two or three times larger than in a traditional course.
The teacher then has the pleasure of guiding these declaratively prepared and empowered learners through a suite of challenging and useful contextual language activities, coaching and encouraging all the while.
It turns out that not only does knowing more words and phrases at the end of a course help you communicate or understand better in the obvious way—of course it’s good to know the word “flour” if you want to ask what store sells flour—it also significantly strengthens the process of skills building. Conversations, role playing, task performance, morphology, syntax, noticing, digesting and practicing grammar, are all easier, more satisfying and more effective.
Research suggests what might be worth trying, but putting ideas into practice is how you find out what works and what doesn’t. Declarative acceleration works.
In the video below, Transparent Language CEO Michael Quinlan discusses our methodology further: