Researchers develop trauma-informed AI model to support online student persistence

University of Phoenix researchers have published a new peer-reviewed study examining how stress, self-regulation, resilience, belonging, psychological safety and generative artificial intelligence (GenAI) interact in the experiences of non-traditional online students. The article, "Designing for Persistence in Online Higher Education: A Trauma-Informed, GenAI-Integrated Model for Non-Traditional Learners," was published July 15, 2026, in Innovative Higher Education. The research was conducted by fellows and scholars affiliated with the University's Center for Educational and Instructional Technology Research (CEITR): Melinda Kulick, EdD; Jessica Sylvester, EdD; Chunfu Cheng, EdD; Christina Bergren, PhD; and Jim Croushore, EdD.

The descriptive phenomenological study of 45 online undergraduates found that trauma-related regulatory strain intensified cognitive demands associated with course navigation, pacing expectations and limited instructional presence. Participants described belonging and psychological safety as supporting engagement, while GenAI could provide short-term cognitive relief and help students initiate tasks during periods of overwhelm. Participants also raised concerns about AI dependency and unclear ethical boundaries. The study introduces the Trauma-Informed AI Persistence (TIAIP) Model, which connects trauma-informed pedagogy, digital course architecture, and guided GenAI use.

Study identifies connections among cognitive load, belonging, and GenAI

The researchers found that trauma-related regulatory strain can intensify the cognitive load associated with navigating courses, managing pacing expectations, and learning with limited instructional presence. Belonging and psychological safety supported engagement, while participants described GenAI as providing short-term cognitive relief and helping them initiate tasks during periods of overwhelm. Students also raised concerns about becoming dependent on GenAI and uncertainty about the ethical boundaries of its use for learning.

Participants described how ongoing stress and competing responsibilities affected concentration, problem-solving, and their ability to engage fully in academic work: one stating, "stress for me creates a lot of brain fog. If I am stressed out, my ability to problem solve diminishes incredibly," and another, "my current source of stress is managing school, work and my household all at the same time…it detracts from my ability to fully engage in my academic work."

Participants also described that unclear instructions, inconsistent course organization, and difficulty knowing where to begin could increase cognitive strain and make task initiation more difficult but also identified how simple acknowledgements help: "when my instructor acknowledged how hard it is to juggle everything, I felt seen. It made me want to stay engaged."

Participants described GenAI as a situational support that could reduce overwhelm and help them initiate academic tasks, while also raising questions about appropriate use and dependence: "when my brain is overloaded, AI helps me get started. It takes away the panic of a blank page"; and "when I'm feeling overwhelmed by an assignment or unsure where to start, AI helps break things down into smaller, manageable steps. That structure helps reduce my stress and gives me a clearer plan of action."

"For students managing work, family responsibilities and other pressures alongside their education, persistence cannot be understood simply as a matter of motivation or individual resilience," said Kulick, assessment manager, associate faculty in the College of Doctoral Studies and a research fellow with CEITR. "Our findings point to the importance of designing online learning environments that reduce unnecessary cognitive demands, strengthen students' sense of connection and give learners appropriate support for navigating moments when the demands on them become especially high."

Researchers introduce Trauma-Informed AI Persistence Model

Building on the findings, the authors introduce the TIAIP Model, a framework integrating trauma science, online learning design and guided GenAI use. The model connects trauma-informed pedagogy, digital course architecture and GenAI integration and conceptualizes student persistence as an outcome shaped in part by institutional design and support rather than solely by individual learner characteristics.

TIAIP Model is a conceptual model that positions student persistence in online higher education as an institutional outcome shaped by the interaction of trauma-related demands, online learning design, and guided use of GenAI.

TIAIP addresses how trauma-related regulatory strain can intensify the cognitive demands of course navigation, pacing, and limited instructional presence, while belonging and psychological safety can influence engagement. It also recognizes GenAI as a conditional scaffold that may provide short-term cognitive relief and support task initiation, while requiring clear ethical and instructional boundaries.

In practice, TIAIP encourages institutions to design learning environments that reduce unnecessary barriers to persistence through clearer course structures, supportive instructional presence, attention to belonging and psychological safety, and purposeful guidance for GenAI use.

"GenAI is not presented in this research as a replacement for human support or student thinking," said Sylvester, senior manager of College Operations, associate faculty and a CEITR research fellow. "The more useful question is how can institutions create the conditions in which technology serves as an intentional scaffold - alongside clear expectations, thoughtful course design and meaningful human connection? That requires helping students understand both what these tools can support and where their limitations and ethical boundaries lie."

About the study

The qualitative study used purposive sampling to recruit 45 undergraduate students enrolled in six bachelor's programs within the College of Social and Behavioral Sciences at a large U.S. online university. Participants ranged in age from 18 to 51 and older, with most between ages 36 and 50, and represented varied employment, caregiving and prior educational experiences commonly associated with non-traditional online learners.

Participants completed an anonymous online questionnaire with open-ended prompts exploring stress, self-regulation, resilience, belonging, psychological safety and GenAI use, responding in writing or by audio. Researchers analyzed the responses using Colaizzi's descriptive phenomenological method, identifying significant statements and meanings and organizing them into thematic clusters. Five themes emerged and informed development of the Trauma-Informed AI Persistence (TIAIP) Model. The study did not assess specific trauma histories or clinical diagnoses; instead, it examined participant experiences involving stresses such as financial pressure, caregiving, employment instability and competing life demands.

Study limitations

The findings provide context-specific qualitative insights from students at one online university and should not be generalized to all higher education populations. The study relied on self-reported experiences, and the open-ended questionnaire provided less opportunity for follow-up probing than interviews. Findings were not analyzed by intersecting demographic identities. The TIAIP Model is a preliminary conceptual model derived from the qualitative findings and requires further study and validation across institutions and learner populations.