If you are presently learning a language, chances are that you are employing a variety of different language learning strategies to do so – such as using flashcards for vocabulary memorisation during your personal study time. 

Many educators believe that teaching a second language involves more than teaching material, effective learning requires students to also learn effective language learning strategies.

But while the overall concept of language strategies and teaching them to language students seems straightforward enough, researching language learning strategies has proved to be much less straightforward. Confounding questions include:

• How can we tell which language strategies are effective and which ones are not? 
• What is a language strategy, and what is not? For example, is attending classes a strategy?
• Could it be that some strategies are more effective for learners in specific circumstances, or at specific stages of development? 

While these may seem like basic questions, for decades researchers have struggled to find clear answers to these questions. Learners typically employ multiple strategies simultaneously – so if they show extraordinary improvement, how do we know which strategies contributed to this success and which may in fact have been hindering? Linguistic research tools typically consist of simple surveys and statistical analyses that traditionally have struggled to handle the complexity of the problem. 

Teachers and learners intuitively believe language strategies are valuable, but researchers have struggled to extract clear, actionable information about which strategies are effective for what and when and who. As a result, today most learning strategies recommended are based on anecdotal stories or a “gut feeling” by educators or students that they will be helpful. But it is certainly possible that the strategies you are employing, while they may feel productive, may simply be filling your schedule with ‘busy work’ and giving you a sense of progress without any real-world results.

A key tenant to the Grow Fast Grow Deep team is “provable effectiveness.” We aim to guide our students in the most effective and efficient learning pathway possible. To achieve this goal, we collect Big Data by tracking our students’ language strategy choices and circumstances, to plot against their Rate of language attainment (ROA). AI is being increasingly used in educational analytics, and offers the ability to handle far more complex statistical modelling than ever before. Utilizing Machine Learning algorithms we can then extract actionable advice that we can feed back to the next generation of students.

So far we have been able to offer concrete answers to issues such as optimising time management, tailoring strategy use to particular learner profiles, and which strategies are effective and when to use them. It may be early days so far, but we hope to publish the results before too long and share with others more broadly what we have learned.

Watch this space!