By doing this, you would be carrying out what is called qualitative research.
The qualitative approach helps us to explore and understand a phenomenon by studying it in detail and trying to take hold of it in a holistic manner, based on the meanings that people assign to the phenomenon. This type of research takes a long time when conducting interviews and interpreting the results; hence, only a small number of individuals can be questioned. Due to this characteristic, the results of a qualitative study are strongly anchored to the context in which the study was carried out, and cannot be generalized to other people or to other contexts. This is not a problem insofar, as qualitative studies do not aim to make such a generalization. The subjectivity of the individuals involved in the study is acknowledged as an integral part of qualitative research. This methodology is built on the principles of a constructivist vision of knowledge, according to which there is not only one, but many realities construed by people’s interpretations and the meanings they attribute to events or things, on the basis of their own experience.
When reading this first proposal for investigating second language acquisition within a context of linguistic immersion, you might think that although it may be interesting to know learners’ opinions about their experience in a language stay, you also desire to know more about the benefits of such a stay on the evolution of their linguistic competences. The conclusions drawn based on the opinions of a few interviewees may not reflect the reality of all learners. It is possible that the interviewees could subjectively overestimate or underestimate the evolution of their skills, or that these particular cases do not mirror the typical experience learners have during a language stay. One possibility, to obtain more objective data on the advantages of a language stay for improving linguistic competences, could be to take into account the experience of more people and to measure their linguistic competences at the start and end of the stay, for example, with an assessment test. By comparing the results before and after the stay with the help of a statistical test, you could determine whether the students’ linguistic skills have evolved and in what aspect. If you chose this second option, your research would follow a quantitative methodology, in the sense that your conclusions would be drawn from the analysis of numerical data pertaining to a large number of people, and objectively assessed through a test. Your results would depend little on the respondents, their subjective perceptions or your interpretation of their declarations. If learners have really benefited from their language stay, this should be reflected in their results to the test, probably higher at the end than at the beginning of the stay, and this is what you would measure directly.
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.
1.1.2. Observational research and experimental research
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
