CARMA Invites AOM Members to Four AI Research Methods Workshops
CARMA (Consortium for the Advancement of Research Methods & Analysis) is a non-profit academic center at Texas Tech University now in our 26th year of providing research methods education. We are excited to be continuing our collaboration with the Academy of Management with our free AOM-CARMA Affiliate Program.
As part of this Affiliate Program, we want to invite you to join four upcoming Topic Area Workshops; all are focused on data technology and the practical use of AI and LLMs in research. Each session is designed to be interactive, focused, and immediately useful, giving you tools and insights you can start applying right away. Topics, presenters, and dates/times are listed below.
No registration is required. You can access the workshops directly from your CARMA User Area under the Access Live Events tab.
· Psychometrics of AI-Scores
Dr. Andrew Speer
Friday, February 13 | 10:30 AM ET
In this session, I will discuss using AI/ML to derive psychological scores and the process of establishing psychometric properties for those scores. The talk will pay particular attention to unique considerations when establishing reliable evidence for large language model scores.
· On the Limits of Algorithmic Insights: Navigating the Hype and Hazards of Generative AI in Qualitative Data Analysis
Dr. Catherine Welch and Dr. Duc Nguyen
Friday, March 6 | 10:30 AM ET
This workshop examines the proposed use of generative artificial intelligence (GenAI) tools to automate or augment qualitative data analysis. Traditionally, qualitative researchers have been regarded as the research instrument in a qualitative project, with their interpretive and context-sensitive judgements forming the foundation of rigorous analysis. Over time, this human-centered approach has been complemented by technological tools (particularly Computer-Aided Qualitative Data Analysis Software, or CAQDAS) that aimed to support the organization and management of qualitative data. More recently, the turn to technology has intensified with the advent of generative AI and its integration into CAQDAS, along with standalone bespoke GenAI-platforms that promise to automate or augment core analytical practices traditionally understood as inherently human.
To navigate the hype and the hazards, the workshop first examines the enthusiastic uptake of GenAI among management researchers as a means of automating or augmenting qualitative data analysis. This discussion is grounded in a technologically informed assessment of what these tools can and cannot do. The workshop then turns to the foundational principles of qualitative data analysis, encouraging participants to recognize more explicitly the human elements that underpin rigorous analysis. The workshop concludes by examining how these elements can be preserved, and potentially strengthened, inviting participants to rediscover what lies at the core of qualitative inquiry-the act of human interpretation.
· LLMs as Research Tools: Data Annotation and Mechanism Discovery in Management Research
Dr. Natalie Carlson
Friday, March 27 | 11:30 AM ET*
*Note change in time from other events at 10:30 AM ET*
This presentation draws on two papers to introduce complementary applications of large language models in empirical management research. The first, Carlson and Burbano (2025, Strategic Management Journal), develops a framework for using LLMs to annotate unstructured text at scale, illustrated through classifying sustainability claims in crowdfunding campaigns. A key finding is that prompt design choices can meaningfully shift downstream research conclusions, motivating systematic sensitivity analysis as standard practice. The second, on gendered work and earnings differentials in microenterprise, uses LLMs to systematically discover candidate mechanisms driving the gender earnings gap. A four-stage pipeline - prediction, discovery, human interpretation, and validation - surfaces candidate business characteristics from World Bank survey data across 26 countries, producing dimensions that collectively explain over half the observed gap. Both applications highlight a complementary relationship between computational tools and researcher judgment: LLMs are well-suited to searching large, unstructured spaces, but evaluation, interpretation, and causal inference remain the domain of human researchers.
· Using LLMs to Generate Materials, Individualize Participant Experiences, and Role-Play in Studies
Dr. Richard Landers
Friday, April 17 | 10:30 AM ET
This workshop will focus on five ways to use large language models (LLMs) in research. It will cover using LLMs as a research assistant, an adaptive content creator, an external resource, a conversation partner, and as a research confederate. Open source software will be introduced, while emphasizing ethics and appropriate research design.
Accessing your 2025-2026 AOM-CARMA Affiliate Program Benefits
For 2025-2026, AOM Members will no longer be able to access CARMA program benefits from their AOM Member area. Instead, they must have a CARMA User Account and must sign up for the 2025-2026 CARMA-AOM Affiliate Program. If you are an AOM member, follow the steps below.
New to CARMA – Create a New CARMA User Account
- If you've never registered with CARMA through an Institutional or Affiliate Membership:
- Create a CARMA User Account (Note: Gmail, Yahoo, Hotmail, and other webmail addresses are not accepted.)
- Check your email for a verification link.
- Verify your email, then log in to your CARMA User Area to finish setting up your account.
Current AOM Affiliate Members – Create a new CARMA User Account Password
- If you've previously registered through the AOM-CARMA direct connection, you already have a CARMA User Account but will need to create a new password:
1. Visit CARMA User Area Forgot Password, and enter the same email address you use for your AOM account.
2. Click on E-Mail Reset Password Instructions.
Register for the 2025-2026 CARMA-AOM Affiliate Program:
To access the CARMA-AOM Affiliate Program benefits, now that you have your CARMA account and password sign up for the 2025-2026 CARMA-AOM Affiliate Program:
1. Once logged in to your CARMA User Area, click the Register/Purchase tab.
2. Choose 2025-2026 CARMA-AOM Affiliate Program.
3. Click Continue, then Proceed to Checkout. (Even though it's free, checkout is required to complete registration.)
Once you have signed up for the free 2025-2026AOM-CARMA Affiliate Program, no additional registration is required to attend the special event or CARMA's Live Online Webcast Lectures. Access will be found in your CARMA User Areaunder the Access Live Events tab.
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Larry Williams
Professor
Texas Tech University
Lubbock TX
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