
Introduction to Experimental Linguistics
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
More details
Other editions
Additional editions


Persons
Christelle Gillioz has a doctorate in psycholinguistics from the University of Fribourg, Switzerland, and has taught research methodology and experimental linguistics at the University of Bern, Switzerland.
Sandrine Zufferey is Professor of French linguistics at the University of Bern, Switzerland. She specializes in the use of empirical methods in linguistics and pragmatics.
Content
Preface ix
Chapter 1. Experimental Linguistics: General Principles 1
1.1. The scientific process 1
1.1.1. Qualitative and quantitative approaches 3
1.1.2. Observational research and experimental research 6
1.2. Characteristics of experimental research 9
1.2.1. Research questions and hypotheses 9
1.2.2. Manipulation of variables 11
1.2.3. Control of external variables 12
1.2.4. The notions of participants and items 13
1.2.5. Use of statistics and generalization of results 14
1.3. Types of experiment in experimental linguistics 15
1.3.1. Studying linguistic productions 15
1.3.2. Explicit and implicit measures of comprehension 16
1.3.3. Offline and online measures of comprehension 17
1.3.4. Research designs and experimental designs 19
1.4. Advantages and disadvantages of experimental linguistics 21
1.5. Where to access research on experimental linguistics 22
1.6. Conclusion 23
1.7. Revision questions and answer key 24
1.7.1. Questions 24
1.7.2. Answer key 24
1.8. Further reading 27
Chapter 2. Building a Valid and Reliable Experiment 29
2.1. Validity and reliability of an experiment 29
2.2. Independent and dependent variables 31
2.3. Different measurement scales for variables 32
2.3.1. Qualitative variables 32
2.3.2. Quantitative variables 34
2.4. Operationalizing variables 36
2.5. Choosing a measure for every variable 37
2.6. Notions of reliability and validity of measurements 41
2.7. Choosing the modalities of independent variables 44
2.8. Identifying and controlling external and confounding variables 46
2.9. Conclusion 50
2.10. Revision questions and answer key 51
2.10.1. Questions 51
2.10.2. Answer key 52
2.11. Further reading 54
Chapter 3. Studying Linguistic Productions 55
3.1. Differences between language comprehension and language production 55
3.2. Corpora and experiments as tools for studying production 59
3.3. Free elicitation tasks 63
3.4. Constrained elicitation tasks 67
3.5. Repetition tasks 71
3.6. Conclusion 75
3.7. Revision questions and answer key 75
3.7.1. Questions 75
3.7.2. Answer key 76
3.8. Further reading 78
Chapter 4. Offline Methods for Studying Language Comprehension 79
4.1. Explicit tasks 79
4.1.1. Metalinguistic tasks 80
4.1.2. Acceptability judgments 84
4.1.3. Questionnaires 90
4.1.4. Forced-choice preference tasks 92
4.1.5. Comprehension tests 95
4.2. Implicit tasks 97
4.2.1. Action tasks 98
4.2.2. Recall tasks and recognition tasks 101
4.3. Conclusion 104
4.4. Revision questions and answer key 104
4.4.1. Questions 104
4.4.2. Answer key 105
4.5. Further reading 107
Chapter 5. Online Methods for Studying Language Comprehension 109
5.1. Think-aloud protocols 109
5.2. Using time as an indicator of comprehension 112
5.3. Priming 117
5.4. Lexical decision tasks 119
5.5. Naming tasks 123
5.6. Stroop task 125
5.7. Verification task 127
5.8. The self-paced reading paradigm 128
5.9. Eye-tracking 131
5.10. The visual world paradigm 136
5.11. Conclusion 139
5.12. Revision questions and answer key 139
5.12.1. Questions 139
5.12.2. Answer key 140
5.13. Further reading 142
Chapter 6. Practical Aspects for Designing an Experiment 143
6.1. Searching scientific literature and getting access to bibliographic resources 143
6.2. Conceptualizing and formulating the research hypothesis 146
6.3. Choosing the experimental design 150
6.3.1. One independent variable 150
6.3.2. Several independent variables: factorial designs 154
6.4. Building the experimental material 156
6.4.1. Experimental items 157
6.4.2. Filler items 161
6.4.3. Other aspects of the material 162
6.4.4. The concept of lists 162
6.4.5. Number of items to be included in an experiment 164
6.5. Building the experiment 164
6.5.1. Instructions 165
6.5.2. Experimental trials 166
6.6. Data collection 168
6.7. Ethical principles 171
6.8. Conclusion 173
6.9. Revision questions and answer key 174
6.9.1. Questions 174
6.9.2. Answer key 175
6.10. Further reading 179
Chapter 7. Introduction to Quantitative Data Processing and Analysis 181
7.1. Preliminary observations 181
7.2. Raw data organization 182
7.3. Raw data processing 186
7.4. The concept of distribution 187
7.5. Descriptive statistics 189
7.6. Linear models 192
7.7. Basic principles of inferential statistics 195
7.7.1. The null hypothesis significance testing 196
7.7.2. Effect sizes and confidence intervals (CIs) 197
7.7.3. Potential errors and statistical power 198
7.8. Types of statistical effects 200
7.9. Conventional procedures for testing the effects of independent variables 202
7.10. Mixed linear models 206
7.10.1. Fixed and random effects 206
7.10.2. Building mixed models 209
7.10.3. Testing a mixed model using R 210
7.10.4. Which random structure to choose? 214
7.11. Best-practices for collecting and modeling data 215
7.12. Conclusion 217
7.13. Revision questions and answer key 218
7.13.1. Questions 218
7.13.2. Answer key 219
7.14. Further reading 222
References 223
Index 239
1
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,...
System requirements
File format: ePUB
Copy protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (not Kindle).
The file format ePub works well for novels and non-fiction books – i.e., „flowing” text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our ebook Help page.