Machine Learning/AI-Based Research Methodologies in Child and Family Studies

Instructor: Professor Wonkyung Jang (Dept. Instructional Leadership and Academic Curriculum, The University of Oklahoma)

Textbook: Lecture notes

Topics: Introduction to Data Science and R Programming (Importance and concepts of data science, Introduction to the R programming language, its basic syntax, and RStudio environment setup. Understanding data types, variables, and data structures, Overview of data visualization algorithms, Statistical pitfalls in social sciences: Common errors and strategies to avoid them. Hands-on practice with basic statistical methods (e.g., T-test, ANOVA, Regression) using R), Machine Learning/AI Techniques for Structured and Unstructured Data (Introduction to supervised and unsupervised learning methodologies, Overview of text mining: Text preprocessing and natural language processing techniques. Hands-on machine learning practice using R, focusing on U.S. child and family studies datasets)

For Students: Before the first session, it is recommended to install the data science program R (https://cran.yu.ac.kr/) and RStudio (https://posit.co/download/rstudio-desktop/).

If you encounter any issues or have further questions, feel free to email me. I will respond as soon as possible.