AOM-CARMA June 2026 Live Online Short Courses:
Qualitative Methods
CARMA (Consortium for the Advancement of Research Methods & Analysis) is a non-profit academic center at Texas Tech University, proudly celebrating 26 years of providing top-tier research methods education. We are excited to continue our partnership with AOM through our Affiliate Program, which offers access to some of CARMA's many education resources. We want to let AOM members know that we have five great courses focusing on qualitative methods: Generative-AI, Interview Data, Theorizing and Writing, Grounded Theory, and Interpretive Methods. Details on these courses and 18 others are provided below.
Unbeatable Pricing-Register Now!
To support students, educators, and researchers, we are offering our lowest prices ever on CARMA's Live Online June Short Courses. AOM-CARMA Affiliate Program Members register now for just $300 through May 3; registration pricing will be $350 May 4 – May 15. Take advantage of our lowest pricing model ever -review the course list below, find the best courses for you, and register now!.
Choose from 23 Live Online Short Courses in June 2026 Offered Across Two Sessions!
CARMA's June Live Online Short Courses are built to strengthen your research skills alongside leading management scholars. You can choose from 23 courses offered across two sessions, spanning four focus areas: Data Technology, Advanced Methods & Analysis, Introductory Methods & Analysis, and Qualitative Methods. Session I runs June 1–4, followed by Session II on June 8–11.
View the Short Course Preview Playlist
View the full June 2026 Live Online Short Course Preview playlist on CARMA's YouTube Channel.
Qualitative Methods
Session I
o The CARMA Generative-AI for Qualitative Research course provides both a theoretical and practical understanding of the rapidly developing field of Qualitative-AI. The course begins by mapping the landscape of AI in relation to qualitative research processes, covering the principles, practices and ethics of using these technologies throughout the analytic workflow. This includes both traditional and generative-AI. A range of tools designed to facilitate qualitative research that harness AI in different ways are introduced and students have the opportunity to experiment with a selection of them, using sample data and their own research materials, if appropriate.
The emphasis of the course is to critically reflect on the potential role and appropriate use of AI-tools. Ethical issues are central, along with how to document the use of AI transparently, and best practices for integrating AI with human interpretation in qualitative studies. We also discuss the future of qualitative research in the generative-AI world, reflecting on the impact on methods of these technologies.
Students will leave the course with a clear understanding of the implications of employing AI in qualitative studies and with practical experience of several tools. The qualitative AI space is evolving quickly, so the tools focused on during this course are subject to change, depending on what is available at the time of the course, but will include tools from across the qualitative-AI space. Students will have free access to all the tools used for the purpose of the course, and will be provided access ahead of the first sessions.
- Publishing Papers with Interview Data (Dr. Heather Vough)
- In this course, we will focus on collecting, analyzing, writing, and reviewing papers using interview data. In the first section, we will tackle questions around who to choose as your informants, how to access informants, how to put together an interview protocol, and how to perform interviews. In the next section, we'll explore various ways of analyzing interview data. The third section of the course will emphasize the actual writing up of qualitative data, in other words, how to move from coded data to a written findings section. In the final section of the class, we will discuss reviewing qualitative work as well as common hurdles in the review process on the way to publication. Participants in this course should have at least an idea for an interview-based study in mind and would benefit from having initial data to work with over the course of the short course.
- Theorizing and Writing Qualitative Research (Dr. Karen Golden-Biddle)
- This goal of this short course is to increase participant's understanding of theorizing and writing field-based research projects for publication in academic outlets. We will conduct our class as a 'studio.' To that end, we will read about as well as examine and practice different ways of theorizing and writing qualitative data. The theorizing part will focus on the analytic practices of artifact construction and coding. We will practice open and focused coding (Locke, K. 2001) and examine the use of artifacts and coding in published papers. The writing part will examine how researchers construct opportunities for contribution, craft theorized storylines, and justify claims to knowledge in published papers (Golden-Biddle & Locke, 2007). Both parts will focus on the use of discovery and validation processes as mutually constituted in published papers (Locke, Feldman. & Golden-Biddle, 2015; Locke, Golden-Biddle & Feldman, 2008; Locke, Feldman & Golden-Biddle, 2022).
Session II
- Grounded Theory (Dr. Elaine Hollensbe)
- We will explore the process of conducting a grounded theory study, using a variety of readings (exemplar and how-to articles), discussion, and hands-on exercises. We will begin at the beginning with generating research questions and interview protocols. We won't just talk about research questions and protocols but will spend time developing them. Similarly, we will engage in coding data. The goal is to ultimately generate a grounded model that both well represents study findings and contributes to scholarship. In addition, we will examine ways to ensure trustworthiness and rigor in grounded theory research to increase the likelihood that your papers will be accepted.
- Interpretive Methods (Dr. Jane Le)
- This applied module seeks to engage researchers in the practice of doing qualitative research. While it introduces a variety of different approaches to qualitative research methods, the predominant focus is on interpretive designs. In working through how to conduct interpretive research, the module reviews the entire research process, giving particular emphasis to data coding, analysis and presentation. Using a combination of learning techniques, including taught sessions, individual work and group work, the module seeks to demystify the research process. In order to maximize the relevance of this session to your own research, some of the exercises will be based on your current research project and data. Hence, if you have already collected data or conducted analyses, please bring these research materials with you (e.g. full transcripts, field notes, documents; CAQDAS file). Alternatively, if you are in the early stages of your research project, you might like to work on a fictional project for the purposes of the course, e.g. interview peers about doing a PhD, Faculty about being an academic, friends about working from home during lockdown, etc.
Session I: (Displayed as divided by content areas)
- Advanced Methods and Analysis
- Introductory Methods and Analysis
Session II: (Displayed as divided by content areas)
- Advanced Methods and Analysis
- Introductory Methods and Analysis
o Introduction to Meta-Analysis (Dr. Dana Joseph)
o Measurement Development, Evaluation, and Adaptation (Dr. Lisa Schurer Lambert)
Dr. Larry Williams, CARMA Director
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Larry Williams
Professor
Texas Tech University
Lubbock TX
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