I believe that a good teacher needs to demonstrate the mastery of three general skills, which are preparing learning-centered syllabus, creating effective learning experience, and assessing student learning progress. It is an iterative to master these skills.
The courses I teach at Cornell are listed below. Feel free to email me for a copy of syllabus if interested.
Environment and Development (GDEV 2065), Fall 2023
Course description: This course delves into the intricate relationship between development and environmental issues from local to global scales. The ways we organize our economy, our culture, our social interactions, and the environment to meet our development needs have a profound impact on our ability to sustain ourselves, our society, and the planet. Through this course, you will explore the interconnected theoretical and practical aspects of environment and development, as well as the diverse dimensions of sustainability and the complex tradeoffs and synergies they entail. By taking a holistic perspective on development trajectories and the accompanying transformation of landscapes, you will critically analyze the barriers and sustainability challenges we face. Additionally, you will examine the social, environmental, economic, and institutional dimensions of these challenges and evaluate proposed solutions. By engaging with these multifaceted topics, you will gain a deeper understanding of the intricate dynamics between development and the environment, equipping yourself to address real-world sustainability issues with a well-rounded perspective.
Learning objectives: 1) Discuss, critique, and analyze the environmental, social, and economic aspects of sustainable development; 2) Examine the trajectory of development and the associated landscape transformation; 3) Evaluate diverse development outcomes for society, the environment, and economy; 4) Identify real-world examples to examine the synergies and tradeoffs between environment and development; and 5) Develop and apply basic research skills and systems thinking to investigate sustainability issues, and enhance interpersonal communication abilities through research proposal writing and peer mentoring.
Introduction to Data Science in Global Development with R (GDEV 3295), Fall 2023
Course description: In this course, you will learn how to program in R and use R for effective data analysis and visualization, with demonstration examples and practice datasets focusing on the interdisciplinary field of global development. You will convert raw data into understanding and knowledge by using R for importing data, managing variables, executing basic functions, developing loops, creating linear models, and generating various kinds of graphs. You will also learn how to use R Markdown to turn your analyses into high quality documents, reports, presentations and dashboards.
Learning objectives: 1) Implement the syntax of base R and ggplot2 package; 2) Import a variety of data formats into R; 3) Clean a dataset and make it ready for analysis; 4) Conduct basic summary statistics for a dataset;4) Perform basic statistical analysis (e.g. linear regression); and 5) Produce data visualization using base R and more advanced packages.
Introduction to Data Science with R (GDEV 4290/5290), Spring 2023
Course description: This workshop style course gives students an opportunity to use the public domain and free software R to perform basic quantitative analysis. The R language provides a rich environment for working with data, especially for statistical modeling and graphics. In this course we will cover data import and management, basic functions, plotting tools, loops and functions, basic linear models, and various graphing tools. By bringing their own data to the class, students will identify appropriate methods for data manipulation, visualization, and analysis using the R environment. This is a hands-on, project-based course to enable students to develop skills and solve statistical problems with their own datasets of interest using R.
Learning objectives: 1) Manage datasets and manipulate variables; 2) Apply basic functions for summary statistics and other computation; 3) Use various plotting and graphing tools, as well as more advanced packages, for data visualization and analysis; 4) Develop basic functions and loops to improve computing efficiency; 5) Perform basic statistical analysis; and 6) Visualize data elegantly.
Liao Research Group 