Introduction to Experimental Linguistics
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Introduction to Experimental Linguistics

Christelle Gillioz, Sandrine Zufferey

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eBook - ePub

Introduction to Experimental Linguistics

Christelle Gillioz, Sandrine Zufferey

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About This Book

The use of experimental methodology in the field of linguistics has boomed in recent decades. However, implementation of such methods does require an understanding and mastery of specific theoretical and methodological principles. Introduction to Experimental Linguistics presents the key concepts of experimental linguistics in an accessible way, addressing, in turn: the application of experimentation in linguistics; the techniques most frequently used for the study of language; the methodological and practical aspects useful for the implementation of an experiment; and an introduction to the analysis of quantitative data derived from experiments. This didactic book combines the elements presented with examples drawn from the various fields of linguistics. It also includes a number of resources available for people who wish to implement an experimental study, more advanced reading suggestions, and revision questions along with their answer key.

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Experimental Linguistics: General Principles

We start this chapter by outlining the foundations of the experimental methodology and its main features. Then, we discuss the advantages and disadvantages of this type of methodology, as well as the main arguments in favor of its use in the field of linguistics. Last, we present a series of resources offering access to research in experimental linguistics.

1.1. The scientific process

The experimental methodology in linguistics is part of a scientific approach for studying language. It aims to observe language facts from an objective and quantitative point of view. The general idea behind this approach is that it is impossible to rely on one’s own intuitions in order to understand the world. Quite the contrary, it is necessary to observe objective data reflecting reality. For example, by simply observing the world around us, and relying solely on our own intuition, we might believe that the Earth is flat. This is why the scientific approach, used in fields such as psychology or physics, is based on specific principles and stages, instead of relying on the intuition of scientists. Let us briefly go through these stages:
The first stage in the scientific process involves the observation of concrete phenomena and the subsequent generalization of observations, in order to build a scientific fact: a fact which does not depend on a specific place, time, object or person. At this first stage, it is also possible to trace certain regularities concerning the emergence of a phenomenon, and to try to define the conditions in which such phenomenon generally appears. So, let us illustrate this process by reviewing the stages involved in the discovery of gravitation. This finding is usually attributed to Isaac Newton, who is said to have had a revelation after seeing several apples fall from a tree. As he watched the apples fall, Newton wondered why the apples always fell in a perpendicular direction from the apple tree to the ground, never to the side or upwards.
During the second stage, all of the scientific facts concerning the same phenomenon may prompt the development of a law or theory aimed at explaining such facts. A theory synthesizes knowledge about a phenomenon at a given moment and is therefore provisional, insofar as it can evolve according to new knowledge. We should make it clear that the notion of theory in science is rather distant from the meaning of the word theory as we use it in everyday language. While this word can be used to refer to personal ideas or reasoning mechanisms, its use in the scientific field only applies to coherent and well-established principles or explanations. Going back to our example, in Newton’s time, two models coexisted for describing the movement of bodies: one followed Galileo’s law and was devoted to terrestrial bodies, whereas the other was oriented by Kepler’s law and made reference to celestial bodies. On the basis of this knowledge and his own observations, Newton suggested the existence of a force which made objects attract one another and which could explain the movements of both celestial and terrestrial bodies.
At the third stage, a theory is capable of predicting the emergence of observable facts, or to put it differently, to formulate precise hypotheses which can be put to the test. In order to test these hypotheses, it is necessary to collect a large amount of data and check whether they support the initial theory. In this way, it is possible to know to what extent we can rely on our theory. The more the predictions made on the basis of the theory are fulfilled, that is, the more the data collected corresponds to what might be expected according to the theory, the higher the confidence level will be. Otherwise, if the predictions did not come true, the theory should be put into question and re-examined. Newton’s law of universal gravitation has made it possible to predict and explain the movement of the tides thanks to the moon’s gravitational pull on the Earth, the elliptical movement of celestial bodies or the equatorial bulge.
In summary, the scientific approach is a circular and dynamic process, originating in the reality of the facts, abstracting itself from them in an attempt to explain them, and then approaching them again to check the validity of the explanation.

1.1.1. Qualitative and quantitative approaches

It is possible to investigate a research question in different ways and from different perspectives. Let us imagine that you wish to study second language acquisition within the context of linguistic immersion. The first way of doing this could be to contact students attending your university for a language stay and to interview them. These interviews can later be viewed to analyze the opinions of students regarding their experience during their stay, their feelings on its advantages and disadvantages, or their opinion on the impact of such a stay on their linguistic competences. 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...

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