Introduction to Experimental Linguistics

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