The Duke Graduate Academy offers free online short courses designed to help emerging scholars strengthen their research, teaching, leadership, and public engagement skills. Open to Duke graduate and professional students, these courses provide practical tools and knowledge that complement students’ academic coursework and research experiences.
Courses focus on topics that are often not covered in traditional graduate curricula or provide intensive introductions to specialized subjects. Sessions are taught by Duke faculty and experienced Duke staff experts. This summer, several workshops are being led by members of Duke’s Social Science Research Institute (SSRI), bringing expertise in applied research, evaluation, qualitative methods, and AI-supported research tools to graduate and professional students across the university.
Summer Term 1
(June 15 – June 26)
Community-Engaged and Community-Partnered Research
GS990 Section 03
Dates: June 15–18 and June 22
(No class on Friday, June 19; make-up class Monday, June 22)
Schedule: Monday–Friday, 9:30 a.m.–12:30 p.m. EDT
Instructor:
Jessica Sperling
Director of Applied Research, Evaluation, and Engagement
Institute for Social and Behavioral Research (ISBR)
Eligibility:
Open to all Duke graduate and professional students. Postdoctoral scholars may enroll with instructor permission.
Course Overview
Community-engaged research (CER/CEnR) and research-practice partnerships (RPPs) help ensure research is grounded in real-world experiences and responsive to community needs. By collaborating with community members and organizations, researchers can strengthen the impact, relevance, and application of their work.
This course explores the foundations, benefits, and challenges of community-engaged and community-partnered research. Participants will examine key concepts and ethical considerations, learn strategies for building effective partnerships, and discuss common logistical and implementation challenges.
Through interactive activities and applied exercises, participants will develop a conceptual framework for community-engaged research and begin designing their own community-engaged research projects.
Summer Term 2
(June 29 – August 7)
Qualitative and Mixed Methods Research
GS990 Section 05
Dates: July 13, 14, 16, 20, and 21
Schedule: Monday, Tuesday, Thursday | 2:00 p.m.–4:30 p.m. EDT
Instructors:
Marissa Personette and Erin Haseley
Senior Research Analysts, Applied Research, Evaluation, and Engagement
Social Science Research Institute (SSRI)
Eligibility:
Open to all Duke graduate and professional students. Postdoctoral scholars may enroll with instructor permission.
Course Overview
This course provides an introduction to qualitative research methods with a focus on integrating qualitative and quantitative approaches through mixed methods research.
Participants will explore the foundations of qualitative research, including when qualitative methods are most appropriate, the unique strengths they offer, and the challenges they can introduce. The course will also examine the value of combining qualitative and quantitative data within a single research design and explore practical applications of mixed methods research.
AI for Qualitative Data Analysis
GS990 Section 06
Dates: July 13–17
Schedule: Monday–Friday | 10:00 a.m.–1:00 p.m. EDT
Instructors:
Lorrie Schmid
Lead, Data Analytics, Social Science Research Institute (SSRI)
Adrian Brown
Assistant Director, Applied Research, Evaluation, and Engagement, SSRI
Eligibility:
Open to all Duke graduate and professional students. Postdoctoral scholars may enroll with instructor permission.
Course Overview
This course introduces participants to the use of artificial intelligence (AI) in qualitative data analysis. Participants will learn the foundations of qualitative research methods and explore the processes involved in analyzing qualitative data.
The course also provides an overview of AI technologies, including large language models (LLMs) and emerging AI tools that support qualitative analysis. Through lectures and discussion, participants will examine practical approaches to incorporating AI into existing research projects while considering the benefits, limitations, challenges, and ethical considerations of using AI in qualitative research.