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At The Qualitative Report 17th Annual Conference, College of Doctoral Studies and CEITR researchers share insights on trustworthiness in AI-integrated research teams, qualitative methods and human–AI cognitive collaboration

How can research teams trust results when artificial intelligence is part of the process? Scholars from the ������ý College of Doctoral Studies and the Center for Educational and Instructional Technology Research (CEITR) presented research helping to address this question at The Qualitative Report (TQR) 17th Annual Conference, held March 24–26, 2026.

Researchers from the College of Doctoral Studies and the Center for Educational and Instructional Technology Research (CEITR) shared studies on AI-integrated research teams, qualitative trustworthiness and human–AI collaboration. Across multiple sessions, the researchers outlined practical methods to maintain credibility in virtual, AI-enabled environments, including frameworks for evaluating team performance, strategies to strengthen trust within research teams, and models for distributing cognitive tasks between humans and AI systems.

Key research insights from the presentations include:

• Trust in AI-enabled research depends on methodological rigor such as credibility, dependability and confirmability in distributed teams

• Self-awareness and humility directly influence research team performance, helping mitigate risks like imposter syndrome and overconfidence

• Q-methodology strengthens the study of human perspectives by combining qualitative depth with quantitative structure

• Human–AI collaboration can be optimized using Bloom’s Taxonomy, clarifying how cognitive tasks are distributed between people and AI

• Structured reflection and “remembered awareness” improve qualitative data analysis, reducing the risk of flawed interpretations

“As artificial intelligence becomes more integrated into research and workplace environments, trust remains the foundation of credible scholarship,” said Mansureh Kebritchi, Ph.D., chair of CEITR and faculty in the College of Doctoral Studies. “Our researchers are developing methods that strengthen how teams evaluate evidence, collaborate across distances, and apply AI responsibly in research and professional practice.”

Research: Trust in AI-integrated virtual teams

In the session, “Ensuring Trustworthiness in AI-Integrated Virtual Research Teams: Lessons from the CEI Pilot Study,” Steven Geer, DBA, research consultant, and LauraAnn Migliore, Ph.D., dissertation chair and faculty member at ������ý, examined how AI tools influence collaboration in virtual research teams. The Collaborative Efficiency Index (CEI) pilot study used a mixed-methods design to evaluate team performance across critical thinking, ethical decision-making and technical skills. Findings highlight how qualitative rigor and structured analysis help maintain trust in geographically dispersed, AI-enabled teams.

Research: Building trust through self-awareness and team dynamics

In “Beyond Doubt and Hubris,” Karen Johnson, Ed.D., CEITR senior research fellow and faculty, and Michelle Susberry Hill, Ed.D., researcher and faculty at ������ý, explored how psychological factors affect trust within research teams. The research identifies how imposter syndrome can weaken collaboration while unchecked overconfidence can erode team credibility. The authors propose reflective practices, open dialogue and intentional team norms to strengthen trust and research quality.

Research: Advancing qualitative methods with Q-methodology

In “A Matter of Trust: Understanding Subjectivity Through Q-Methodology,” Stella Smith, Ph.D., associate university research chair for CEITR and associate faculty in the College of Doctoral Studies at ������ý, demonstrated how Q-methodology enables researchers to systematically study subjective viewpoints. By combining qualitative and quantitative techniques, the method creates a transparent analytical process that strengthens trust in how perspectives are interpreted and represented.

Research: Strengthening qualitative analysis through “remembered awareness”

In the workshop, “Remembered Awareness: A Wilderness Survival Analogy for Trustworthiness in Qualitative Data Analysis,” LauraAnn Migliore, Ph.D., Steven Geer, DBA, and Susan Ferebee, Ph.D., CEITR research fellow, introduced a framework for improving analytical discipline. Using a wilderness survival analogy, the session emphasized recognizing reliable data signals, maintaining awareness during analysis, and reinforcing trust within research teams to support consistent and accurate findings.

Research: Human–AI cognitive collaboration and task distribution

In “Human and AI Cognitive Distribution Taxonomy, Collaboration Strategies, and Interaction Implications,” Mansureh Kebritchi, Ph.D., David Aiken, DBA; Kenneth Murphy, DBA; and Stella Smith, Ph.D., explored how humans and AI systems can collaborate on complex tasks. Using Bloom’s Taxonomy as a framework, the study examines how knowledge-processing responsibilities can be distributed between humans and AI to improve performance and decision-making.

Advancing research in learning technologies and workforce-aligned education

The presentations reflect the mission of ������ý’s Center for Educational and Instructional Technology Research, which conducts interdisciplinary research to investigate how emerging technologies—including artificial intelligence—can improve learning outcomes, instructional design and workforce-aligned education.

 serves as a global learning community for qualitative researchers, with this annual conference dedicated to gathering the community together to contribute new insights and support personal and professional growth. 

About the College of Doctoral Studies

������ý’s College of Doctoral Studies focuses on today’s challenging business and organizational needs, from addressing critical social issues to developing solutions to accelerate community building and industry growth. The College’s research program is built around the Scholar, Practitioner, Leader Model which puts students in the center of the Doctoral Education Ecosystem® with experts, resources and tools to help prepare them to be a leader in their organization, industry and community. Through this program, students and researchers work with organizations to conduct research that can be applied in the workplace in real time.

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