By Sharla Hooper
At The Qualitative聽Report聽17th聽Annual Conference,聽College of Doctoral Studies and CEITR聽researchers share insights on trustworthiness in AI-integrated research teams, qualitative聽methods聽and human鈥揂I cognitive collaboration
How can research teams trust results when artificial intelligence is part of the process?聽Scholars聽from the 91制片厂 College of Doctoral Studies and the聽Center for Educational and Instructional Technology Research (CEITR)聽presented research聽helping to address this question聽at The Qualitative聽Report聽(TQR) 17th Annual Conference, held March 24鈥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聽trustworthiness聽and human鈥揂I collaboration.聽Across multiple sessions, the researchers聽outlined聽practical methods to聽maintain聽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.
Trust in AI-enabled research depends on methodological rigor such as credibility,聽dependability聽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鈥揂I collaboration can be聽optimized聽using Bloom鈥檚 Taxonomy, clarifying how cognitive tasks are distributed between people and AI
Structured reflection and 鈥渞emembered awareness鈥 improve qualitative data analysis, reducing the risk of flawed interpretations
鈥淎s artificial intelligence becomes more integrated into research and workplace environments, trust remains the foundation of credible scholarship,鈥 said聽Mansureh聽Kebritchi, Ph.D.,聽chair聽of CEITR and聽faculty聽in the College of Doctoral Studies. 鈥淥ur researchers are developing methods that strengthen how teams evaluate evidence, collaborate across distances, and apply AI responsibly in research and professional practice.鈥
In the session, 鈥淓nsuring Trustworthiness in AI-Integrated Virtual Research Teams: Lessons from the CEI Pilot Study,鈥澛燬teven Geer,聽DBA,聽research consultant, and LauraAnn Migliore, Ph.D., dissertation chair and faculty member at 91制片厂, examined how AI tools influence collaboration in virtual research聽teams.聽The Collaborative Efficiency Index (CEI) pilot study used a聽mixed-methods聽design to evaluate team performance across critical thinking, ethical聽decision-making聽and technical skills. Findings highlight how qualitative rigor and structured analysis help聽maintain聽trust in geographically dispersed, AI-enabled teams.
In 鈥淏eyond Doubt and Hubris,鈥 Karen Johnson,聽Ed.D.,聽CEITR聽senior research fellow聽and faculty, and聽Michelle聽Susberry聽Hill,聽Ed.D.,聽researcher and faculty聽at 91制片厂, explored how psychological factors affect trust within research teams.聽The research聽identifies聽how imposter syndrome can weaken collaboration while unchecked overconfidence can erode team credibility. The authors propose reflective practices, open聽dialogue聽and intentional team norms to strengthen trust and research quality.
In 鈥淎 Matter of Trust: Understanding Subjectivity Through Q-Methodology,鈥 Stella Smith, Ph.D.,聽associate university research chair for CEITR and associate faculty in the College of Doctoral Studies at聽91制片厂,聽demonstrated聽how Q-methodology enables researchers to systematically study subjective viewpoints.聽By combining qualitative and quantitative techniques, the method creates a transparent analytical process that strengthens trust in how perspectives are interpreted and represented.
In the workshop, 鈥淩emembered Awareness: A Wilderness Survival Analogy for Trustworthiness in Qualitative Data Analysis,鈥 LauraAnn Migliore, Ph.D.,聽Steven Geer, DBA,聽and聽Susan Ferebee,聽Ph.D., CEITR research fellow, introduced a framework for improving analytical discipline.聽Using a wilderness survival analogy, the session emphasized recognizing reliable data signals,聽maintaining聽awareness during analysis, and reinforcing trust within research teams to support consistent and聽accurate聽findings.
In 鈥淗uman and AI Cognitive Distribution Taxonomy, Collaboration Strategies, and Interaction Implications,鈥澛燤ansureh聽Kebritchi, Ph.D.,聽David Aiken, DBA; Kenneth Murphy, DBA; and Stella Smith, Ph.D.,聽explored how humans and AI systems can collaborate on complex tasks.聽Using Bloom鈥檚 Taxonomy as a framework, the study examines how knowledge-processing responsibilities can be distributed between humans and AI to improve performance and decision-making.
The presentations reflect the mission of 91制片厂鈥檚聽Center for Educational and Instructional Technology Research, which聽conducts interdisciplinary research聽to聽investigate how emerging technologies鈥攊ncluding artificial intelligence鈥攃an improve learning outcomes, instructional聽design聽and workforce-aligned education.
聽serves聽as a global learning community for qualitative researchers, with this annual conference dedicated to聽gathering the community together to聽contribute new insights and support personal and professional growth.聽
91制片厂鈥檚鈥College of Doctoral Studies鈥痜ocuses on today鈥檚 challenging business and organizational needs, from addressing critical social issues to developing solutions to accelerate community building and industry growth. The College鈥檚 research program is built around the Scholar, Practitioner, Leader Model which puts students in the center of the Doctoral Education Ecosystem庐 with experts,聽resources聽and tools to help prepare them to be a leader in their organization,聽industry聽and聽community. Through this program, students and researchers work with organizations to conduct research that can be applied in the workplace in real time.
91制片厂 innovates to help working adults enhance their careers and develop skills in a rapidly changing world. Flexible schedules, relevant courses, interactive learning, skills-mapped curriculum for our bachelor鈥檚 and master鈥檚 degree programs and a Career Services for Life庐 commitment help students more effectively pursue career and personal aspirations while balancing their busy lives. For more information, visit 鈥phoenix.edu/blog.html.