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Spotlight on...
I study language learning as a process of statistical learning over the language input. I look at this using artificial language learning experiments and computational modelling.
“Online research will make well-powered studies with large sample sizes the rule, rather than the exception.”
If you ever studied a foreign language, you will have been taught that languages have rules, or, probabilistic tendencies, as I prefer to think about it. For example, in my native language, Serbo-Croatian, nouns that end in –a tend to be of feminine gender, and most nouns for fruit are feminine. In my research, I am interested in whether learners are sensitive to these probabilistic patterns in sound and meaning in the language they are learning, and whether the ability to pick up on these patterns helps learners generalize. For example, if someone showed me a fruit I’ve never seen before, would I, as a native speaker of Serbo-Croatian, expect to hear an a‑ending noun as the name for this fruit?
To answer these kinds of questions, together with Dr Liz Wonnacott and Dr Michael Ramscar, I designed a series of online studies in Gorilla, where I taught participants artificial languages. In these languages, novel, alien-like objects were described using nonsense words and particles (for example: “foob ma” or “jeed pe”). I was interested in whether participants could pick up on the fact that “aliens” which occurred with the same particle tended to share certain visual and/or auditory features, designed to mimic the regularities in meaning and sound which we find in natural language. I tested this by showing participants a new “alien” which had these critical features, and observing which particle participants grouped this novel item with.
Across three experiments, I was able to identify several factors that affect what and how participants learn: the order in which participants are shown the pictures of aliens and the corresponding nouns, the number of “aliens” seen during training, and whether training is timed or self-paced.
A poster presented at Architectures and Mechanisms for Language Processing (AMLaP) in Berlin, Germany with more detail of this study can be found here.
Apart from their theoretical relevance, these findings could have important implications for second language teaching in schools.
My PhD would be a living nightmare without version control.
“Since online data collection is far less time-consuming than traditional lab-based testing, it liberates researchers to devote more time to reading and writing better papers.”
Online research will make well-powered studies with large sample sizes the rule, rather than the exception in psychology. There are huge practical implications, too – with data collection being much less time consuming compared to traditional lab-based experiments, researchers will be able to devote more time to reading and writing better papers. Also, participants are a lot more willing to volunteer their time if they can do it from the comfort of their homes. It’s a win-win all the way!
Apart from the advantages I listed previously, in my work, it is very important to control for participants’ first language (as this could affect how they learn the artificial language), so I only study native monolingual speakers of English, and they are fairly difficult to find in London, which can cause delays in data collection. Online research makes it easier to reach large numbers of native speakers of English.
Zoltan Dienes’ Understanding Psychology as a Science is a fantastic introduction to the scientific method for psychologists. I only wish I’d read it as an undergraduate.
I spend my free time reading fiction, playing squash (poorly), and discovering new places to eat in London (which, on a PhD studentship, can be a real challenge!).
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