Sandrine Zufferey - Introduction to Experimental Linguistics

This example illustrates to what extent quantitative research differs from qualitative research, in that it aims to observe quantifiable elements and to measure a phenomenon. The techniques used for measuring a phenomenon can be extremely varied, depending on how the phenomenon is defined. Going back to our previous example, it is possible to measure language proficiency using a general language test (such as the placement tests used in language schools). Another way of doing this would be to count the number of mistakes students make in a grammar test or to measure the size of their second language lexicon. Choosing the proper measures for undertaking research is a big question in itself. We will return to this in Chapter 2, where we will discuss the different stages of choosing the measures involved in an experiment.

Quantitative research also differs from qualitative research in terms of the type of reasoning on which it is based. We have seen that in qualitative research, we draw upon data in order to outline a structure. In this case, data works as a source of interpretations and explanations upon which hypotheses will be formulated. This type of reasoning, starting from data and leading towards a theory, is called inductive reasoning. On the contrary, quantitative research follows deductive reasoning: it draws on theory in order to formulate hypotheses which will later be verified by data acquired in the field. When choosing a deductive approach, it is necessary to build a preliminary hypothesis, on which the research will be based and that will guide the researchers’ methodological choices.

Going back to the example of learners within an immersion context, there are a large number of hypotheses that could be formulated by using the link between language stay and language proficiency. The first hypothesis could be that a language stay improves second language skills. A second hypothesis, similar to the first, but involving a different research methodology, could be that people who have spent time on a language stay have acquired better skills than those who have not. In order to verify the second hypothesis, we would have to test two groups of learners who may or may not have benefited from linguistic immersion, instead of one group of students before and after the stay. A third hypothesis could focus on one specific aspect of language proficiency, such as pronunciation in a foreign language (accent). We might imagine that the learners who have spent some time on a language stay may have a better pronunciation (an accent closer to that of the native speakers), than those who have not. In order to test this third hypothesis, two groups of students would be required, but this time they would be assessed on their pronunciation.

Even if they differ in their formulation and in the type of elements they have put to the test, the hypotheses mentioned above share a common feature, which is that they all postulate a relationship between what we call variables . In all the hypotheses, the first variable corresponds to linguistic immersion. In the first and second hypotheses, the second variable is the proficiency level in the second language. In the third hypothesis, the second variable corresponds to a weaker non-native accent. We will discuss the notion of variables in further detail in Chapter 2. For the time being, it is important to understand that a variable is something that varies, and can take different values. For example, a variable can be the age of participants in a study, which would result in a broad number of values. A second variable could be the fact of wearing glasses, or eye color, etc. These variables adopt fewer values: either yes or no for wearing glasses, and blue, brown, green or other for eye color.

Let us now take the example of a variable studied in language science: bilingualism. At first glance, this variable may seem to only adopt two values: either bilingual or monolingual. However, things get more complicated when we have to define what we mean by bilingual . For example, we may decide that anyone having knowledge of a second language is bilingual. In that case, there would be great heterogeneity within the bilingual group, containing people who can only speak or understand a second language superficially, and people capable of perfectly mastering both languages. A corollary of such a definition would be that very few people would belong to the monolingual group, since many people are familiar with one or more languages, apart from their mother tongue. On the other extreme, we could consider belonging to the bilingual group as only those with a perfect command of their second language. In this case, the bilingual group as would be more homogeneous, in the sense that all those belonging to it would have similar competences in their second language. But this definition raises additional questions: what do we mean by perfect command and how can command be measured? This example illustrates the need to clearly and precisely define the variables investigated in a research process. This definition procedure is called the operationalization of a research question. It represents a crucial phase in quantitative research, and we will discuss it in depth in Chapter 2.

To summarize, quantitative research aims to investigate the relationship between two or more variables. To do this, it starts from a hypothesis and defines the measures used for studying the chosen variables. Then, it relies on digital data collected from a large number of people and analyzes such data using statistical tests, in order to generalize the results.

Quantitative approaches in linguistics make an important difference between observational research and experimental research. The first example of a research tool, the questionnaire, is frequently used in linguistics to collect data in a quantitative manner. A questionnaire is a set of questions aimed at collecting different types of information about speakers, such as personal characteristics, their use of certain words or linguistic structures, or their point of view about certain linguistic phenomena. Let us now imagine that you wish to know whether there is a difference in the way that French speakers from France, Belgium and Switzerland refer to a yogurt . As Avanzi (2019) did, you could directly ask a large number of French, Belgian and Swiss people to tell you which of the two possible names, yaourt or yoghourt , they use on a daily basis. By counting the responses of more than 7,000 people, Avanzi showed that the form yaourt is mainly used in France, whereas it is never used in Switzerland, where yoghourt is the only form in use. In Belgium, the choice of yaourt and yoghourt varies from region to region.

In a slightly different way, instead of relying on the answers of people in a questionnaire, you could use linguistic data retrieved from natural productions and carry out a corpus study . In such studies, linguistic productions in the form of texts, audio or video recordings are used with the aim of counting the number of word occurrences, a grammatical form or any linguistic characteristic. In order to research the uses of yaourt or yoghourt in France, Belgium and Switzerland, first it would be necessary to select corpora comprising linguistic productions collected from these different regions. This data could come from French, Belgian and Swiss newspapers, for example. The number of occurrences of each form could be counted in each corpus and then compared, in order to reveal differences in the use of these forms from country to country.

Another way of studying quantitative data is to examine the link between two variables. Let us imagine that you wish to study the relation between learners’ age and their ability to acquire a second language. Extensive research has already been devoted to this topic and suggests that the older people are when learning a second language, the more difficult it is for them to reach a high level of proficiency (see DeKeyser and Larson-Hall (2005) for a review). In order to confirm (or refute) this hypothesis, you could test a large number of people who start learning a language at different ages and measure their language proficiency after a certain period of time. In this example, the first variable, the age when learning begins, is a quantitative variable. Likewise, the second variable, language proficiency, can be measured quantitatively using a language test. Using an appropriate statistical test, it is possible to show the existence of a link between these two variables. This type of procedure is called correlational research and unveils the degree of dependence between two variables, which is called correlation. In the case of our example, if age plays a role in second language acquisition, the correlation obtained by our test would show that the older a person is when the process of learning a language begins, the lower their mastery of the language will be after a certain learning period.