Guest Post by Angela Grant, Pennsylvania State University
Do you remember the last time you took a language course? No matter if it was online or classroom based, immersive or translation focused, I would be willing to bet a large sum of money that your language abilities when you left that course were different from your peers. Perhaps you are like my husband, better at reading and writing than speaking your second language. Perhaps you are like me, a whiz in the classroom but a bit shy in real life. Maybe you’ve got your numbers down, but not much else. That’s the kind of variability we are dealing with.
Of course, these “individual differences” are present in every field, from mathematics and music to art and athletics (consider the difference between Simone Biles and the rest of the U.S. women’s gymnastics team, for example). But in my own field, the psychology of second language acquisition, it is a question that frequently arises: Why does learning a new language come easier to some than others?
I became interested in individual differences in second language acquisition as early as middle school, although I would never have phrased it that way back then. Rather, I wondered why I really enjoyed learning Spanish (and later, Italian), while other students struggled. This question has stuck with me, and ever since then I have been working to figure out why and how individual people learn languages differently.
Most recently, I was excited to find that Xiaoqian Chai and colleagues at McGill have been using resting-state fMRI (a technique that measures brain activity while you are awake, but not doing a task) to investigate exactly this question. Looking at students in an intensive 12-week immersion course, they found large individual differences in how much the participants improved their French skills.
As presented by Jonathan Berken at the most recent CNS conference, and published in the Journal of Neuroscience, they scanned the brains of native English speakers before they began the immersion course. These students were practicing French six hours a day, five days a week, and living in the bilingual environment of Montreal, Quebec. If you want to learn a language quickly, this is the way to do it.
Rather than relying on course grades or self-report, Chai and colleagues collected spontaneous speech data (by asking participants, to say, tell them about a day at the beach) and reading samples in both French and English before and after the course. The analysis of the resting state data revealed that differences in improvement of each behavior were related to pre-existing differences in their functional brain connectivity.
Each skill—reading and speaking, respectively—depended on different functional connections. Reading, but not speaking, was dependent on connections with the visual word form area, while speaking, but not reading, was dependent on connections with the medial inferior frontal gyrus. For both skills, however, the overall pattern was the same: Greater connectivity between relevant areas before training was associated with larger gains in language performance.
These findings beg even more questions: If connectivity predicts learning, how do we predict connectivity? What can we do, as scientists and educators, to facilitate these connections?
One way to understand this may be to dive deeper into learners’ skills in their first language—in this case, English. Although Chai and colleagues did not report individual differences in their learners’ English skills before training, I can’t help but draw a connection to the literature on “dual-language learners” in the United States. That research emphasizes that a strong first language is the key to acquiring a strong second language, especially in children. Consequently, it’s possible that some of the differences in connectivity may have been due to the participants’ pre-existing language skills: how much the participants read, or how social they were, for example.
Another critical question is: What happened after the course? Did the poorer learners show greater increases in connectivity (because they had more room to grow, so to speak) or less (because there is a more direct relationship between connectivity and performance)? While there is some research out there that may provide clues (for example, check out Stein et al., 2014), few studies have been able to track real learners over long periods of time due to the expense and high drop-out rates associated with longitudinal studies.
For example, in my own work evaluating the neural correlates of second language vocabulary processing, I followed Spanish learners over one year of instruction, and what began as a sample of 33 participants ended with only 19 (Grant, Fang & Li, 2015). Nevertheless, until we can track learners longitudinally, we will still have many questions about what makes a good second language learner. I know I certainly do, so I guess I better get back to work. The next generation of middle-schoolers are coming into a more globalized world than ever before, and they are going to need some help.
Angela Grant is a Ph.D. Candidate in Cognitive Psychology and Language Science at the Pennsylvania State University. She uses behavioral and neuroscience techniques to study language processing across multiple contexts, with a focus on second- language learning and bilingualism.
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