Data Analysis for Applied Linguistics and Second Language Research Using R and ChatGPT

A Practical Guide With Large Language Models
1. Auflage 2027
ISBN: 978-1-041-03243-4
Verlag: Taylor & Francis

Buch, Englisch, 266 Seiten, Format (B × H): 174 mm x 246 mm

Data Analysis for Applied Linguistics Second Language Research Using R and ChatGPT introduces the concepts and practical skills needed to analyse and visualise second language research data, using R for statistical analysis and ChatGPT to support learning.

Designed for readers with little or no experience of data analysis, the book covers R programming, data manipulation and visualisation, and statistical techniques ranging from introductory to advanced. Case studies and examples help explain complex concepts, while guidance on interpreting and reporting statistical results enables readers to communicate their findings effectively. The book also introduces open-science practices that support transparent and reproducible research. Throughout, ChatGPT is incorporated as a learning tool, with an emphasis on understanding research goals and developing practical problem-solving skills.

This book is ideal for students and researchers in applied linguistics and second language acquisition who are beginning to undertake quantitative research or wish to develop their data analysis skills using R and ChatGPT.

The book is supported by supplementary online materials.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Yi, Wei

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung
• Geisteswissenschaften Sprachwissenschaft Sprachwissenschaften
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Preface  1. Data Analysis for Applied Linguistics and Second Language Research  2. Introduction to R Programming 3. Data Preparation and Cleaning in R 4. Data Exploration and Visualization in R  5. Fundamental Statistical Concepts 6. Examining Relationships Between Variables Using Correlation 7. Comparing Means Using t-Tests  8. Chi-Square Test of Independence for Categorical Data 9. Comparing Means Across Conditions Using ANOVA 10. Predicting Continuous Outcomes Using Linear Regression 11. Predicting Categorical and Count Outcomes Using Generalized Linear Models (GLMs) 12. Modeling Dependent Data Using Mixed-Effects Models 13. Modeling Change over Time Using Growth Curve Analysis 14. AI-Auditable Statistical Analysis and Open Science Practices

Über Autor(innen)

Wei Yi is an Associate Professor in the School of Chinese as a Second Language at Peking University. His research on the processing of multiword expressions appears in journals including Language Learning, Studies in Second Language Acquisition, and Applied Linguistics. He also designed GuaSpeak, an AI-powered, multilingual language learning app.