AI-Supported Quantitative Data Analysis in Foreign Language Research provides a practical and methodologically grounded guide to using artificial intelligence throughout the quantitative research process while keeping analytical judgment and scientific responsibility firmly in human hands.

Written for students, teachers, and researchers in foreign language education and applied linguistics, the book shows how AI can support data preparation, statistical analysis, interpretation, verification, visualization, documentation, and reporting. Rather than presenting AI as a substitute for statistical reasoning, it demonstrates how researchers can use AI to make quantitative analysis more accessible, transparent, interactive, and reproducible.

Drawing on authentic research datasets, the book guides readers through the full analytical workflow. It begins with understanding research questions, data files, reporting conventions, data-file creation, data entry and import, variable transformation, and case selection. It then covers frequency analysis, descriptive statistics, crosstabulation, internal consistency, exploratory factor analysis, and the evaluation of analytical conditions. Later chapters address regression, correlation, t-tests, analysis of variance, pre-test-post-test and repeated-measures designs, nonparametric procedures, and data visualization.

Structured AI prompts are integrated throughout the book to help readers inspect datasets, clarify analytical objectives, generate and evaluate code, conduct statistical procedures, verify results, produce visualizations, and prepare research reports. These prompts are not intended as fixed commands or shortcuts. Instead, they encourage researchers to work progressively with AI and to evaluate each stage of the analytical process.

Verification is treated as an essential part of quantitative research. Readers are encouraged to check data structures, sample sizes, assumptions, calculations, tables, figures, and interpretations, while paying careful attention to uncertainty, effect sizes, confidence intervals, measurement quality, missing data, unusual observations, and the limits of causal claims.

The book does not depend on a particular AI platform or statistical software package. Its emphasis is on analytical reasoning and methodological control. Whether AI is used to explain a statistical concept, generate Python or R code, inspect a dataset, create a visualization, or assist with reporting, researchers remain responsible for selecting appropriate methods, evaluating evidence, and determining what conclusions their studies can reasonably support.

By connecting statistical procedures with meaningful research questions and methodological decisions, AI-Supported Quantitative Data Analysis in Foreign Language Research offers both a practical introduction to quantitative analysis and a framework for using AI responsibly in contemporary research.

• Publisher ‏ : ‎ LREplus

• Publication date: ‎ September 25, 2026

• Language: ‎ English

• Print length: ‎ 317 pages

• ISBN-10: ‎ 6259060793

• ISBN-13: ‎ 978-6259060798

• Item Weight: ‎ 1.74 pounds

• Dimensions: ‎ 8 x 0.72 x 10 inches