Discover how artificial intelligence can streamline workflows, uncover hidden patterns, and empower breakthroughs in your field. Learn practical applications of AI through Odum Institute AI in Research series that can revolutionize your research process.
This course offers an overview of how AI tools such as large language models (LLMS) can enhance early stages of the survey process, including item generation, questionnaire evaluation, and survey refinement. This session will highlight practical ways LLMs such as ChatGPT and Microsoft Copilot can support researchers while also addressing common pitfalls. Participants will learn best practices for questionnaire design focusing on writing questions, response option development, and question ordering. Ideal for researchers seeking to incorporate AI thoughtfully and efficiently during survey development work. The first half of the session will provide structured lecture content, and the second half will offer time for participants to ask questions and discuss the specific projects they are working on.
Mixed methods research (MMR) refers to research design and implementation that combines qualitative and quantitative data collection and/or analysis strategies. This seminar explores strategies for effectively designing, implementing, and integrating MMR. Through discussion of exemplars and theoretical frameworks, we will consider best practices for “mixing” methods and presenting integrated findings. Participants will gain practical skills for aligning methodological choices with research questions, implementing complementary qualitative and quantitative techniques, and articulating cohesive and rigorous mixed methods results.
Join the Children's Research Institute for a seminar with Horacio A. Duarte, MD, MS, an assistant professor in the Division of Epidemiology & Community Health at the University of Minnesota School of Public Health. Duarte is a physician-scientist with clinical training in pediatric infectious diseases and research training in epidemiology, decision analysis, and health economics. His research focuses on developing computer-based simulation models to evaluate the effectiveness and cost-effectiveness of HIV treatment and prevention policies for adults and children in resource-limited settings.
Participate in the seminar at 3116 Mary Ellen Jones Building (with lunch provided). A zoom option is also available.
Qualtrics is a powerful browser-based web-survey tool. It is available to UNC-Chapel Hill faculty, staff, and students, for UNC-related projects. Qualtrics allows users to build complex surveys, distribute them, and analyze the responses all from one place.
In this course, we will cover basic Qualtrics functions beginning with an overview of survey options and settings, followed by hands-on practice programming and distributing a survey and downloading results. We will program some of the most common question and response types, customize requirements and validation, and add display logic, skip logic, and basic branch logic in the “survey flow”. We will then create and upload a contact list and discuss advantages and disadvantages of distributing the survey with a single reusable link vs. the survey mailer. Finally, we will cover a basic overview of the Data & Analysis tab for viewing, editing, and exporting raw data into various formats including .csv, .tsv, .excel, and .spss. Other topics include project sharing/ collaboration, Groups and Libraries, and preventing fraudulent responses and bot activity.
This is an introductory course and will not cover use of the online analysis tools within Qualtrics. Please note, this is a hands-on course. All participants are required to create a Qualtrics account before the course.
This course is the second in a two-part scale development course series on scale development. Part one of the series focused on the general theories and methods used in the scale development process. This second portion focuses on the analytic methods used to statistically test, refine, and validate scale data. These methods include Cronbach’s alpha, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and basic structural equation models testing for predictive validity.
This interactive online workshop will focus on semi-structured interviewing, a data collection method used in qualitative research. Topics covered will include basics of semi-structured interviews, development of interview questions and probes, interviewing skills, and considerations for conducting virtual interviews. Participants will have the opportunity to practice developing interview questions and using interviewing skills.
This event may be recorded. Materials such as slides or handouts will be shared with documented attendees only.
Presenters:
MaryBeth Grewe, MPH
Program Manager, Qualitative Research Service
Research Specialist, Patient and Community Engagement in Research (PaCER) Program
Simone Frank, MPH
Senior Project Manager, Patient and Community Engagement in Research (PaCER) Program
Research Specialist, Qualitative Research Service
For questions about this training, please contact MaryBeth Grewe at
Please join the Department of Health Sciences Office of Research & Scholarship for their February research forum. Bai Li, PhD, MLS (ASCP)CM SHCM, will present Community Health Monitoring Via Decoding Age-stratified Microbiome Signatures in Urban Wastewater; Hiral Master, PT, PhD, MPH, will present Innovating Rehabilitation Through Wearables and Large Data; and Shawn Luby MS, MLS(ASCP)CM, will present Considering Communications: An Examination of Clinical Laboratory Involvement in Patient Education.
The hybrid forum will take place in person (MacNider 321, LUNCH provided) and via Zoom. Please register to attend.
Questions? Contact the Department of Health Sciences Office of Research & Scholarship at