# University of Phoenix Study Links Trauma-Informed Practices to Online Learning Success > This innovative study reveals how psychological safety and generative AI can transform online learning for nontraditional students, offering crucial insights into course design and student engagement strategies. **Source**: phys.org | **Published**: 2026-10-12 | **Type**: research ## Key Facts - Trauma-related strain increases cognitive load, impacting online student engagement and performance. - GenAI offers temporary relief for overwhelmed students, highlighting dependency risks in learning. - Institutions must prioritize psychological safety to enhance persistence and reduce cognitive demands. - Clear course structures and supportive presence are essential for improving student retention rates. - TIAIP Model suggests strategic shifts in online education design, integrating trauma-informed practices. ## Summary A recent study by researchers at the University of Phoenix has unveiled a new model that integrates trauma-informed pedagogy with generative artificial intelligence (GenAI) to enhance online learning for nontraditional students. This research, published in *Innovative Higher Education*, is significant as it addresses the complex interplay between psychological factors and educational design, particularly for learners juggling multiple responsibilities. The findings suggest that educational institutions must rethink course structures to foster persistence and engagement among students facing various stressors. The study, conducted by a team from the university's Center for Educational and Instructional Technology Research, involved 45 online undergraduate students. It revealed that trauma-related regulatory strain can exacerbate cognitive demands, making it difficult for students to navigate their courses effectively. Participants reported that feelings of belonging and psychological safety were crucial for maintaining engagement. They also identified GenAI as a potential tool for alleviating cognitive overload, helping them initiate tasks during overwhelming periods, though concerns about dependency and ethical usage were prevalent. The researchers introduced the Trauma-Informed AI Persistence (TIAIP) Model, which connects trauma-informed educational practices with digital course design and guided GenAI use. This model posits that student persistence is not solely a function of individual resilience but is significantly influenced by institutional design and support systems. The TIAIP Model emphasizes the need for educational environments that minimize cognitive strain, enhance feelings of belonging, and provide structured guidance for using AI tools. The implications of this research are profound for the online education sector. As more institutions adopt online learning modalities, understanding the psychological dynamics at play will be crucial. The study indicates that institutions should prioritize clear course structures and supportive instructional presence to help students manage the cognitive load associated with their studies. This approach not only aids in student retention but also enhances overall educational outcomes. The findings also highlight the importance of ethical considerations in the integration of GenAI into learning environments. While GenAI can serve as a valuable support tool, institutions must establish clear boundaries regarding its use. This includes educating students about the capabilities and limitations of AI, ensuring that technology complements rather than replaces human interaction and critical thinking. As the landscape of higher education continues to evolve, the TIAIP Model signals a shift towards a more holistic understanding of student needs. Institutions that adopt this framework may find themselves better equipped to support nontraditional learners, who often face unique challenges. By fostering environments that prioritize psychological safety and clear guidance, educational leaders can enhance student engagement and persistence. Looking ahead, the integration of trauma-informed practices and guided AI use may become a standard in online education. Institutions that embrace this model could gain a competitive edge by not only improving student outcomes but also attracting a broader demographic of learners. As the demand for flexible learning options grows, those that effectively address the psychological and cognitive needs of students will likely lead the way in shaping the future of higher education. ## Entities - **Companies**: University of Phoenix - **Products**: Generative Artificial Intelligence (GenAI) - **People**: Sadie Harley, Andrew Zinin, Melinda Kulick, Jessica Sylvester, Chunfu Cheng, Christina Bergren, Jim Croushore - **Organizations**: Center for Educational and Instructional Technology Research (CEITR) ## Key Concepts psychological safety, trauma-informed pedagogy, online learning design, cognitive load, GenAI integration, student persistence, nontraditional learners, institutional support ## Definitions - **Trauma-Informed AI Persistence (TIAIP) Model**: A framework that integrates trauma science, online learning design, and guided use of generative AI to enhance student persistence in online education. - **Generative Artificial Intelligence (GenAI)**: A type of AI that can generate content and assist students in task initiation and cognitive relief. - **psychological safety**: A belief that one will not be penalized or humiliated for speaking up with ideas, questions, or concerns, which supports student engagement. - **cognitive load**: The total amount of mental effort being used in the working memory, which can be affected by stress and course navigation challenges. - **nontraditional learners**: Students who may have different educational backgrounds, responsibilities, and life experiences compared to traditional college students. ## Use Cases - Integrating GenAI to assist students in managing academic tasks. - Designing online courses that reduce cognitive demands. - Enhancing student engagement through psychological safety. - Providing support for nontraditional learners balancing multiple responsibilities. - Using the TIAIP Model to inform institutional course design. ## Frequently Asked Questions **What is the TIAIP Model?** The TIAIP Model is a conceptual framework that connects trauma-informed pedagogy, online learning design, and guided use of generative AI. It aims to improve student persistence by addressing cognitive demands and enhancing engagement. **How does GenAI support students?** GenAI can provide cognitive relief by helping students initiate tasks and manage their workload during overwhelming periods. It serves as a situational support rather than a replacement for human interaction. **What are the main findings of the study?** The study found that trauma-related stress can increase cognitive load, while belonging and psychological safety enhance engagement. It also highlighted concerns about AI dependency among students. **Who conducted the research?** The research was conducted by a team of fellows and scholars affiliated with the University of Phoenix's Center for Educational and Instructional Technology Research, including several doctoral-level educators. **What limitations were identified in the study?** The study's findings are context-specific and based on self-reported experiences from a single online university. It also did not analyze data by intersecting demographic identities, which may limit generalizability. ## Links - [Read on Welcome.AI](https://welcome.ai/content/university-of-phoenix-study-links-trauma-informed-practices-to-online-learning-success) - [Original source](https://phys.org/news/2026-10-links-psychological-safety-ai.html) --- Source: Welcome.AI | https://welcome.ai/content/university-of-phoenix-study-links-trauma-informed-practices-to-online-learning-success