Connecting cognitive biases and typological universals in syntax

Languages can be very different from each other. For example, just focussing on the order of words, languages like English put adjectives before nouns ('red house') while languages like Thai put them afterwards ('house red'). Similarly, languages like Vietnamese put Numerals before nouns ('three houses'), while others, like the Kitharaka (spoken in Kenya), put numerals after ('houses three'). If word ordering was simply due to happenstance, we would expect to see all different orders appearing in equal proportion across languages, but we don't find that. In fact, some orders are very common, some are very rare, and some don't seem to appear at all. For example, many languages are ordered like English ('three red houses'), and many are also ordered like Thai, which is exactly the reverse ('houses red three'). But the Kitharaka order ('houses three red') is much rarer, and its mirror image ('red three houses') never seems to occur. Why is this?

One of the major controversies in the language sciences is whether we need to appeal to the basic set-up of the human mind to explain the ways languages can vary, or whether these properties are instead a result of cultural differences in communication and social interaction. A great deal of recent work coming from the perspective of psychology assumes the latter: that the properties of language can be boiled down to communication, interaction and the vagaries of history, while most work in linguistics assumes the former: there must be biases in the human mind that allow us to learn languages of particular types more easily than others. This project seeks to resolve that issue.

In order to do this, we test how well people learn languages of various types, to see whether their behaviour follows the general tendencies we see across real languages. Importantly, we use artificially constructed languages, rather than natural languages, in order to make sure that they only differ in the crucial respects. For example, we present English speakers with artificial languages that use word orders from Thai and Kitharaka. If Thai orders are more common across languages than Kitharaka ones because the former are easier to learn, then we should see this reflected in the behaviour of learners in our experiments. We can also see whether such patterns are always harder to learn, or if speaking a language which uses them-like Kitharaka-makes them easier to pick up in a new language. To do this, our experiments compare English, Thai, Vietnamese and Kitharaka speakers. If our learners all show the same kinds of patterns in how they learn our artificial languages that we find across real languages, that will suggest that the way languages vary is not random, nor is it entirely a product of historical facts. Rather it would suggest that there are universal cognitive biases at play.

We plan to look at not just the basic question of what orders appear, but also two other well-known cases where languages don't seem to vary randomly. The first relates to how words like adjectives and numbers are placed relative to the nouns they modify: most languages place them both before or after (like English and Thai), rather than putting them on opposite sides (e.g., 'two houses red', like Vietnamese). We will test whether this type of pattern is always easier to learn in a new language. Second, we will look at whether people prefer to learn languages with suffixes (e.g., 'cat-s') rather than prefixes (e.g., 'un-happy'). Both types are present in English, but most languages have (more) suffixes. Our project we will shed light on whether there are universal cognitive biases in language learning, if such biases are at play for the particular phenomena we look at, and how people's native languages affect these biases.

This project investigates how cognitive biases shape language learning, and thus ultimately the distribution of linguistic patterns across the languages of the world. The approach we use is distinctly interdisciplinary: we target hypotheses put forward by linguistics using methods developed by psychologists and psycholinguistics in order to answer questions that have broad implications for the cognitive science of language. Beyond its relevance to this academic community, the project speaks to questions that are of interest to the general public. For example, what are the deep common features of human psychology that shape the unique trait of language that we share? How do these features interact with our experience, culture, and history to produce the rich variety we see across the world's languages?

In addition to these big picture questions, our research also has important implications for language learning-in particular how cognitive biases and our prior experience together impact how we learn a new language. For example, our results will show how prior language experience-coming from both first and second language knowledge-affects adults' ability to acquire linguistic patterns hypothesized to present a learning challenge. These findings will have clear implications for language education practitioners who work with learners from a range of linguistic backgrounds (e.g. English for Speakers of Other Languages (ESOL) support workers, or primary school staff teaching modern languages to children with English as an Additional Language). The research also speaks directly to an important strand of current research which seeks to uncover the effects, both positive and negative, of multilingualism. Bilingualism Matters is a Centre at the University of Edinburgh, based in the same school as the PI. The Centre is dedicated to research and knowledge exchange around language education and bilingualism and has a proven track record in shaping public policy in this field (e.g., advising Scottish Government on their 1+2 policy for language learning in primary schools). The proposed grant will benefit from the Centre's existing networks (including language practitioners, key organisations such as Education Scotland and Scotland's National Centre for Languages, and members of local and national government). These non-academic stakeholders will be invited to contribute to the project from the outset (e.g., by discussing how the research and tools developed in the project might feed into Continued Professional Development for practitioners), as well as being key audiences for the dissemination of research results.