Course Syllabus

Course Overview

Students will gain experience applying large language models (LLMs) for key purposes in psychology research, following the APA guidelines on using LLMs in Psychology. These purposes include:

1. Measurement - Probing psychological patterns in large text datasets
2. Experimentation - Generating stimuli and responses to refine factorial designs
3. Practice - Simulating realistic conversations to train therapists, counselors, teachers, or managers

Part 1: Generative AI and Psychology Research Practicum (Dr. Yoon Kyung Lee)

Students will engage in hands-on research practice building and using AI agents for:

• Generating research ideas
• Formulating hypotheses
• Designing studies
• Analyzing data
• Ensuring ethical AI use in research

Part 2: Scientific Writing (Prof. Jiook Cha)

Students will learn how to write various forms of academic writing, including abstracts, grant proposals, white papers, and APA manuscripts, and learn to promote their research through various media.

Prerequisites (Recommended)

• Psychology research methods course
• Basic understanding of programming (e.g., introduction to Python programming)

Required Tools for Hands-on Workshop

• [Required] Gemini Pro Student Plan (Free)
• [Recommended] ChatGPT Pro
• [Recommended] Claude Pro

Course Format

This course combines:

• Short lectures (literature review)
• Paper presentations
• Group discussions
• Team project

Assignments

Weekly homework to apply class concepts (e.g., using LLMs for data generation, AI-assisted research protocols, reports, or visualizations). Group work is encouraged for hands-on activities.

In-Class Activities

Paper Presentation (~15 min per student)

• Problem statement
• Contributions
• Methodology
• Results
• Strengths/weaknesses
• Discussion questions

Group Discussion (~20 min)

• Prepare for the team project
• Share AI-generated artifacts
• Receive peer feedback

Team Project

Students propose an original research idea applying AI agents to psychological science methods. Projects may be individual or team-based (up to 3 members; larger teams are expected to produce higher-quality work). Students are encouraged to form teams with diverse interests and expertise.

Project Requirements

The project should include (but not be limited to):

• Research question and rationale
• AI tool used and design process (agent/interface)
• Methods, Results
• Discussion, AI ethics
• Reproducibility
• Expected outcomes and limitations

Each team gives a proposal presentation and clearly defines member roles.

Learning Objectives

By the end of this course, students will be able to:

1. Apply LLMs effectively for psychological research purposes
2. Design and implement AI-assisted research protocols
3. Write Nature/Science-level abstracts and grant proposals
4. Critically evaluate AI-generated content and ensure research integrity
5. Collaborate in interdisciplinary teams using AI tools
6. Understand ethical considerations in AI-assisted research

Grading

Academic Integrity

You may use AI as a writing assistant, but the work must be original. No simple copy-and-paste of AI-generated output - put it into your own words. No copying others' work.

All assignments should demonstrate your understanding and critical thinking, not just AI-generated responses.