PLC Faculty Facilitator
Dr. Karen Magruder
Karen Magruder, DSW, LCSW-S is an Associate Professor of Practice at the University of Texas at Arlington School of Social Work, where she brings to the classroom a broad social service background in aging, mental health, and environmental justice. A dedicated and award-winning educator, Karen is passionate about integrating evidence-based and innovative techniques to promote student success in online learning. Her current primary focus is leveraging artificial intelligence (AI) to enhance teaching and learning. She manages a small private therapy practice, provides clinical supervision, and maintains a free social work education resources YouTube channel.
Celebrated for her excellence in teaching and student-centered online instruction, was recently honored with the 2025 UT Regents’ Outstanding Teaching Award (ROTA), recognizing her innovation, mentorship, and deep commitment to student success. Prior to this system‑level distinction, she received UTA’s President’s Award for Excellence in Distance Education Teaching and the Provost’s Award for Excellence in Teaching. Her national-level teaching awards include the USDLA’s Excellence in Distance Education Award and the national DSW conference’s Outstanding Contributions to Social Work Education Award. Beyond the classroom, Dr. Magruder also contributes to the scholarship of teaching and learning as co‑editor of the open educational resource AI‑Powered Education: Innovative Teaching Strategies to Elevate Student Learning, a faculty resource currently being utilized at 92 institutions across 77 countries that provides practical, ethical, and discipline‑spanning strategies for integrating AI into higher education. The book is freely accessible through Mavs Open Press at: https://mavmatrix.uta.edu/oer_mavsopenpress/50/.
Areas of interest relating to AI and teaching
- AI policie
- AI for clinical simulations
- AI literacy
- Ethical AI use
Teaching ideas for CRTLE to showcase
Dr. Magruder recently developed a customized LinkedIn Learning AI roleplay bot to simulate cognitive-behavioral intervention therapy for Master of Social Work (MSW) students, allowing them to practice clinical skills in a low-stakes environment where no real clients are at risk. This tool helps students build confidence and competence through repeated practice, receive individualized feedback aligned with criteria she developed, and engage in skill-building on demand. Because access is available anytime, it is especially valuable for online students who may not always have another person available to practice with.
PLC Faculty Fellows
Dr. Farnaz Farahanipad
Farnaz Farahanipad, Ph.D., joined academia in 2022 and is currently a Lecturer in Computer Science at The University of Texas at Arlington. She teaches undergraduate and graduate courses in machine learning, programming, and software engineering, and is passionate about creating practical, hands-on learning environments that connect theoretical concepts with real-world applications and industry practices. In recognition of her exceptional dedication and positive impact on student engagement and success, she was honored by the Division of Student Affairs in 2025. She also serves as Assistant Lab Director of the Heracleia Human-Centered Computing Lab, where she supervises Ph.D. and undergraduate students on assistive technology projects, including the development of a smart cane designed to enhance accessibility and independent mobility.
Areas of Interest Related to AI
I am particularly interested in how AI can support personalized learning, provide timely feedback, improve student engagement, and increase instructional efficiency while maintaining academic integrity. One area I am especially interested in exploring is the use of AI as a “peer-like learning companion.” Since collaborative learning with peers is known to reduce stress and improve understanding, I am interested in implementing AI agents that can act as supportive peer guides. Such AI agents could help students practice concepts independently, answer questions in real time, provide hints rather than direct solutions, and adapt their guidance based on each student’s learning pace and progress. Over time, these agents could personalize their support by learning from students’ interactions, identifying knowledge gaps, and adjusting feedback to match individual learning needs.
Teaching Innovation Related to AI/Technology
To enhance student learning and provide more practice opportunities, I have incorporated AI-supported tools into my computer science courses to create low-stakes, hands-on learning environments. For example, in my Software Engineering courses, I focus on introducing students to the most recent AI tools used in modern development environments and guiding them in applying these technologies to build real-world software applications. As part of project-based learning activities, students use AI to support key stages of the software development lifecycle, including refining requirements, generating and visualizing design ideas, assisting with coding and debugging, creating test cases, and improving documentation. This hands-on exposure helps students understand how contemporary AI tools are practically integrated into professional workflows.
By incorporating current AI technologies into authentic development tasks, student engagement and opportunities for experiential learning are enhanced. This approach not only strengthens students’ technical skills but also helps them develop the ability to use AI tools responsibly and effectively in real-world contexts.
Dr. Hanna Haran
Hanna Haran, PhD, MSW, is an Assistant Professor at the University of Texas at Arlington School of Social Work. Her research focuses on employment, wealth attainment, culturally sensitive financial literacy, and economic justice among populations with histories of forced migration. Her research is comprised of three primary components: (1) expanding the scope of social work to enhance financial capability and asset development among forced migrant populations; (2) investigating the influence of trauma and displacement on financial behaviors and the cultural perceptions of money; and (3) prioritizing participant-centered inquiry through mixed-methods approaches and community-engaged research. Collectively, these efforts seek to inform the design of programs, services, and policies that foster economic equity among refugees and other forced migrants.
In the classroom, Dr. Haran integrates artificial intelligence into discussions of bias and ethics, particularly as they relate to social work practice and research. Her work also explores how AI literacy shapes emerging forms of digital inequality, with a focus on understanding who has access to AI technologies, the injustices that arise from unequal access, and strategies to prevent the next wave of the digital divide. In addition to her research and teaching at UTA, Dr. Haran contributes to the broader social work profession and serves on the Editorial Board of the Journal of Ethnic and Cultural Diversity in Social Work.
Areas of Interest Related to AI and Teaching
- Ethical AI use
- AI in Social Work simulation
- AI literacy and the digital divide
Teaching Ideas for CRTLE Showcase
Dr. Haran plans to use Adobe Express to help students translate their research papers into an infographic or research brief for dissemination to social work agencies. Adobe Express allows students to distill complex findings into clear, accessible visuals that highlight key data, implications, and practice recommendations quickly. The infographics provide a digestible way to disseminate research to community partners, helping bridge the gap between research and practice. Through this format, students will build skills in Adobe Express, knowledge translation, and learn how to communicate evidence in a way that supports agency decision-making and community impact.
Dr. Jaclyn Kirsch
Jaclyn Kirsch, PhD, LISW-S, is an Assistant Professor at the University of Texas at Arlington School of Social Work. Dr. Kirsch brings over a decade of social work practice experience across diverse settings, which informs both her research and teaching. She is particularly passionate about working with immigrant and refugee communities and advancing culturally responsive clinical adaptations for diverse populations. Her teaching spans the social work curriculum, including courses on clinical mental health, diagnosis and assessment, and research methods. She is actively engaged in curriculum development at the bachelor’s, master’s, and doctoral levels. Dr. Kirsch is especially committed to experiential education and the integration of innovative tools, including artificial intelligence (AI), to provide students—particularly online learners—with hands-on opportunities to develop strong clinical skills for future practice. In recognition of her teaching excellence, she was recently nominated for the UTA President’s Award for Transformative Online Education.
Areas of interest relating to AI and teaching
- AI for clinical simulations
- Ethical AI use
- AI and research
Teaching ideas for CRTLE to showcase
Dr. Kirsch plans to use the online video platform HeyGen to develop high-quality, professionally produced instructional videos for a new mental health course designed for undergraduate and graduate social work students. This platform will allow her to present complex clinical concepts in a clear, engaging, and consistent format, enhancing the learning experience—particularly for online students who rely on asynchronous instruction. The use of professionally developed video content will help ensure students build a strong foundational understanding of mental health, diagnosis, and clinical practice. To complement these videos, Dr. Kirsch will integrate activities using NotebookLM, enabling students to engage with course material through multiple formats, including AI-generated podcasts, brief quizzes to assess understanding, and interactive presentations. These tools will promote active learning, support diverse learning styles, and provide flexible opportunities for students to reinforce their knowledge and develop clinical competence.
Dr. Diane Mitschke
Diane Mitschke is a Professor at the University of Texas at Arlington School of Social Work. She is a member of the Academy of Distinguished Teachers and the Academy of Distinguished Service Leaders. Diane is passionate about teaching, learning, and social work, and is always on the lookout for innovative ways to engage students in the classroom by connecting content to real world communities. She served as Associate Dean for Academic Affairs in the School of Social Work from 2020-2024, and as Program Director from 2015-2020. Diane’s scholarship focuses in two areas: refugee resettlement and student success and well-being. She has authored nine peer-reviewed journal articles focused on student engagement in higher education.
Areas of interest relating to AI
- Qualitative analysis of research data
- Accessible and engaging content creation
- Enhancing and facilitating grading of low-stakes assignments
- Enhancing student writing and study skills
Current Research and Teaching Showcase using AI
Dr. Mitschke is using AI to create and produce engaging overview videos in several courses that are in development. Harnessing the dynamic tools available in tools like Notebook.LM and Adobe Firefly enable faculty to develop polished and professional content that are accessible in an expedient manner, enhancing student engagement and understanding of key course concepts.
Dr. Yangjin Park
Yangjin Park, Ph.D., MSW, is an Assistant Professor at the University of Texas at Arlington School of Social Work, where he brings a robust background in violence prevention, trauma, and family systems to the classroom. A dedicated researcher and educator, Dr. Park is passionate about examining the protective role of family resilience in the context of environmental risks, such as bullying and interpersonal violence. His current primary focus involves leveraging advanced quantitative methods and Artificial Intelligence (AI) to identify risk patterns among adolescents and military families, ultimately informing more effective preventative interventions. He also brings clinical depth to his work, possessing advanced training in family systems theory and technique from the Ackerman Institute for the Family.
Celebrated for his impactful scholarship and research excellence, Dr. Park was recently honored with the 2024 and 2025 Barbara Thompson Award for Excellence in Research on Military and Veteran Families. His published work was further recognized with the 2024 Best Quantitative Article Award from Families in Society. Prior to joining UTA, he received the Outstanding Dissertation Award in Social Science from New York University. He is currently a candidate for the 2026 President’s Award for Excellence in Teaching – Untenured at UTA. Beyond the classroom, Dr. Park contributes to the scholarship of his field as an Editorial Manager for the Journal of Psychiatric Research and a Review Editor for Frontiers in Psychology.
Areas of Interest
- AI-Enhanced Clinical Training: Developing multi-agent simulations for family therapy education.
- Predictive Analytics in Social Work: Using AI to understand risk patterns in interpersonal violence and trauma.
- Family Resilience & Military Well-being: Leveraging technology to support family systems under stress.
- Adolescent Mental Health: Addressing bullying victimization through digital and systemic interventions.
Current Research and Teaching Showcase: AI Integration
Dr. Park is currently piloting a "Multi-Agent" AI Family Simulator for his Seminar in Family Therapy students. While traditional roleplays often rely on a single peer playing a client, this tool simulates a full military family system—including a deployed parent and a distressed adolescent. The AI dynamically adjusts the family members' reactions based on the student's ability to maintain neutrality and use circular questioning. This allows students to practice the complex skill of managing triangulation and family conflict in a safe, repeatable digital space before entering clinical practicum.
Dr. Donna L. Schuman
Donna L. Schuman, PhD, LCSW, Assistant Professor, School of Social Work, University of Texas at Arlington Donna L. Schuman is an Assistant Professor at The University of Texas at Arlington School of Social Work, where she brings expertise in neuroscience-informed social work, trauma, and military/veteran populations to her teaching. A dedicated educator, Dr. Schuman, is passionate about integrating evidence-based and innovative digital techniques to promote student success in online and hybrid learning. In her cornerstone course, Brain and Behavior (SOCW 5315), she uses HeyGen AI to create professional avatar-based instructional videos and has designed an innovative AI activity, “Creating Safe Spaces for Persons with Alzheimer’s,” where graduate-level students
social work students apply AI tools to develop trauma-informed, neuroscience-grounded environments. Dr. Schuman is currently an active participant in UTA’s yearlong Professional Learning Community (PLC) Series for Faculty: “Future-Ready Teaching” (2025–2026), with a dedicated focus on Artificial Intelligence. She was awarded the President’s Teaching Award for Non-Tenured Faculty in Spring 2025, recognizing her innovation, mentorship, and deep commitment to student success. Prior to this distinction, she received the Certificate of Exploration and Innovation (2022) and was selected as a PLC Faculty Fellow (2021). Beyond the classroom, Dr. Schuman contributes to innovative training solutions as the Principal Investigator of the Veteran Suicide Assessment in Virtual Reality (VET-SAVR) project, funded by the American Foundation for Suicide Prevention and UTA’s Center for Rural Health and Nursing, to create and test a virtual reality simulation focused on rural veteran suicide prevention.
Areas of interest relating to AI and teaching
· AI for creating immersive, trauma-informed learning experiences
· Neuroscience-grounded AI applications in social work education
· Ethical and innovative use of AI tools in hybrid/online courses
· AI literacy for social work students and practitioners
Teaching ideas for CRTLE to showcase
Dr. Schuman has developed multiple innovative AI-integrated activities and resources in her cornerstone course, Brain and Behavior (SOCW 5315). In the assignment “Creating Safe Spaces for Persons with Alzheimer’s,” Master of Social Work (MSW) students apply AI tools of their choice to design trauma-informed, neuroscience-grounded environments for individuals with Alzheimer’s disease. Dr. Schuman is using HeyGen AI to develop professional avatar-based module overviews and lectures and has begun incorporating them into her SOCW 5315. She is currently working on an AI-generated video podcast using HeyGen AI focused on AI ethics in social work education and practice, to share with her classes to facilitate thoughtful discussions on responsible technology use, bias mitigation, privacy concerns, and equitable integration of AI tools.
Dr. Ling Xu
Ling Xu, PhD, LMSW, is an Associate Professor in the School of Social Work at the University of Texas at Arlington, bringing over two decades of expertise in dementia care, aging and mental health, family caregiving, and culturally responsive social work practice. Trained as a gerontological scholar since 1999, Dr. Xu has conducted extensive research on aging and built a nationally recognized academic career advancing research, teaching, and community engagement to support older adults and their families.
A prolific scholar, Dr. Xu has published over 100 peer-reviewed articles in high-impact journals and secured 15 funded grants (8 external, including an NIH R15, and 7 internal). Her scholarly excellence has been recognized with numerous honors, including the Milkes Moore Fellowship and Professorship, a Fulbright Scholarship in Taiwan, election as a Fellow of the Gerontological Society of America (GSA), and selection as a Fellow of the Advanced Research Institute (ARI) in Mental Health and Aging. An award-winning educator, she received the 2024 President’s Award for Excellence in Teaching (Tenured Faculty) and the 2022 UTA Faculty Mentor Award. Her classrooms emphasize cultural responsiveness, critical thinking, and interdisciplinary evidence to prepare students for careers in aging, health, and family caregiving.
Beyond the classroom, Dr. Xu contributes to her field through extensive professional service. She serves on advisory boards for community agencies supporting older adults, reviews grants for federal agencies including NIH and NIDILRR and serves on the editorial boards of two gerontology journals. She has also been a guest editor and symposium chair for leading academic journals and GSA annual meetings.
Areas of Interest Relating to AI and Teaching/Scholarship in Aging
- AI-Enhanced Gerontological Education & Interprofessional Training: Integrating AI-powered instructional tools and simulations to strengthen teaching and skill development in aging, dementia care, and family caregiving across social work and allied health professions.
- AI for Dementia Care & Clinical Decision Support: Using machine learning and AI systems to identify care needs, risk factors, and intervention pathways for older adults living with dementia and their caregivers.
- Culturally Responsive & Ethical AI in Aging: Advancing equitable, bias-aware AI applications that enhance cultural humility and support diverse aging populations.
- AI-Supported Digital Interventions & Community Engagement: Exploring AI-based tools to promote emotional well-being, aging in place, and strengthen community engagement, needs assessment, and program evaluation.
Current Research Showcase Using AI
Dr. Xu recently partnered with small businesses to submit two NIH Small Business Innovation Research (SBIR) proposals to support persons living with dementia (PLWD) and their family caregivers. Building on her expertise in reminiscence therapy and related pilot work, she and her collaborators are developing an AI-powered autonomous reminiscence therapy system and a gamified reminiscence platform designed to enhance the social and emotional well-being of PLWD.
Dejan Terzic, MBA
Dejan Terzic, MBA, (Professor T) is an Assistant Adjunct Professor at The University of Texas at Arlington. He is a Swiss-born banking and insurance professional turned educator. For more than a decade, he advised international clients in German, English, and French while designing business processes, worked with various internal and external stakeholders, and implemented software solutions that automated daily operations (long before AI 😀).
Mentoring new hires, collaborating with people across different teams, and creating instructional materials were always some of his favorite parts of the job, and those passions ultimately led him to teaching. Today, he teaches Business Communication, where he emphasizes clear, audience‑focused messaging, cross‑cultural fluency, and persuasive writing and presenting. He draws heavily on my hands‑on industry experience to give students practical tools they can apply immediately.
Areas of interest relating to AI and teaching
- Build your own AI Class Agent: It’s Not Rocket Science – Conference Topic for ABC-SW 2026
- Can PowerPoint Karaoke Teach STAR Interviews Better Than You? (with a little help from AI, maybe) – Conference Topic for ABC-SW 2026
- AI-Enhanced Writing in Business Communication: Using GenAI as a tool rather than a means
- GenAI is not replacing a human writer but enhancing the process, making writing more accessible and helping ideas flow faster and brighter.
Current Research and Teaching Showcase using AI
Professor T is the main author for the upcoming conference session titled “Build Your Own AI Class Agent: It’s Not Rocket Science.” His presentation introduces a practical approach for instructors who feel uncertain about bringing AI into the classroom or worry about students relying on quick, one‑prompt answers. He demonstrates how customized AI class agents can support business communication courses by answering routine questions, guiding peer review, generating practice scenarios, and turning course materials into study-ready tools. The session shows faculty how to design agents that follow program policies, stay offline, i.e. avoid web searches, avoid invented facts, reflect course tone, and help students move toward a more thoughtful cycle of planning, checking, and revising. The focus is on giving instructors clear, adaptable use cases they can implement immediately, along with a simple workflow for building an AI agent that makes classes smoother and strengthens students’ critical thinking and writing habits.
He is also a co‑author for another AI-focused conference session titled “Can PowerPoint Karaoke Teach STAR Interviews Better Than You? (with a little help from AI, maybe).” In this presentation, he shows how a playful improvisation activity can be transformed into a structured interview‑skills workshop by combining spontaneous storytelling with AI‑supported coaching. The session demonstrates how students can use Generative AI to rehearse STAR responses, practice thinking under pressure, build story libraries, and receive individualized feedback at scale. By pairing narrative scaffolds with live PowerPoint Karaoke rounds, the workshop offers instructors a creative, classroom‑ready way to help students improve clarity, confidence, and adaptability during behavioral interviews.
Another noteworthy example of AI class integration is Professor T’s custom software developed for the Steam Deck, a handheld computer that runs Linux as its operating system. With help from AI, he built a fully offline tool that displays randomized student names and lets him mark each student as “attended” or “absent” with a single button press. The interface is completely customizable, including names, button labels, and functions, which makes it useful for attendance tracking, fair cold‑calling, and engagement activities. Because the system stays private, is offline, and never connects to any cloud service, it protects student information while still delivering a fun, attention‑grabbing moment when students see it in action.
Dr. Heather Philip
Heather E. Philip, Ph.D., is an Associate Clinical Professor of Marketing experienced in designing and teaching in-person and online asynchronous courses such as Business Communication, Consumer Behavior, Digital Marketing, and Social Media Marketing. Since 2018, she has refined her approach to teaching classes ranging from 40 to 180 students in Canvas, continually experimenting with practical, interactive strategies that strengthen student engagement and connection. Her recent scholarship includes a chapter in the open‑access book AI‑Powered Education (Mavs Open Press), which examines how AI can support meaningful student reflection and help learners publish polished LinkedIn articles.
Her more recent work focuses on AI‑ and technology‑supported communication instruction, including several projects presented at Association for Business Communication conferences:
- RIFF Before You Present: Using ChatGPT to Build Improvisational Agility in PowerPoint Karaoke
Structured improvisation for interpreting unfamiliar slides, organizing spontaneous ideas, and strengthening real‑time communication with AI‑guided cues.
- From Copy‑Paste to CAPE: Reclaiming the Learning Process in the Age of AI
Prompt‑development and revision routines that move students beyond first‑draft AI output and toward clearer, audience‑aware communication.
- Can PowerPoint Karaoke Teach STAR Interviews Better Than You? (with a little help from AI, maybe)
Scaffolded behavioral‑interview preparation using AI roleplay agents, visual STAR storytelling, and guided improvisation to build transferable narrative skills.
- Build Your Own AI Class Agent: It’s Not Rocket Science
Course‑aligned agent design using the A.G.E.N.T. structure to encode expectations, generate practice scenarios, and support consistent reasoning habits.
Showcase Student Work: Embedding Slides, Polls, and Projects Made Easy
Interactive LMS design using simple HTML embeds, H5P elements, and media‑rich layouts to reduce clicks and create seamless spaces for student work and feedback.
Dr. Jiyoon Yoon
I am an Associate Professor of Science Education at the University of Texas at Arlington, specializing in inquiry‑based and culturally responsive teaching practices that deepen student understanding of scientific concepts in K-12 science classrooms. My research and teaching focus on developing universal curriculum and instruction that supports all learners and promotes conceptual reasoning through hands‑on models, real‑world phenomena, and data analysis. I am committed to preparing future educators to design effective, equitable learning experiences grounded in both research and practice, and to fostering students’ scientific literacy and curiosity across all grade levels.
AI Teaching Interests:
I am particularly interested in exploring how artificial intelligence can enhance science education, including AI-supported inquiry, personalized learning, and curriculum design. I aim to leverage AI tools to help students investigate scientific phenomena, analyze data, and refine their understanding through iterative exploration.
AI-Related Teaching Innovations:
I am developing AI-supported curriculum modules that go beyond simply adding AI tools to lessons. These innovations systematically integrate AI throughout a unit or module, allowing students to interact with AI as an active learning partner. For example, in science education, students use AI to model scientific processes, generate hypotheses, and analyze experimental data while progressing through the curriculum. This approach embeds AI as a structured tool for reasoning, exploration, and reflection, empowering students to engage more deeply with content and scientific practices.
Dr. Rose Tompkins
Rose Tompkins, PhD, MSN, RN is an Assistant Professor for the University of Texas at Arlington (UTA) College of Nursing and Health Innovations where her scholarly work is bridging behavioral health, prevention science, and innovative teaching practices in health professions education. Her scholarship centers on adolescent commercial tobacco and substance use prevention, culturally responsive care, and community-engaged approaches to health promotion. With a background in nursing and public health focused research, Dr. Tompkins integrates evidence-based prevention frameworks with experiential and technology-enhanced learning strategies. Her teaching philosophy is grounded in human-learner centered pedagogy, holistic and ethical practice, and the belief that AI innovations should enhance rather than replace relational learning. She actively participates in the UTA Professional Learning Community (PLC), focused on artificial intelligence (AI) in higher education and future-ready instructional design. Through this work, she explores how AI can be responsibly integrated into nursing and health sciences curricula while maintaining rigor, cultural responsiveness, and professional integrity. She is particularly committed to preparing both youth and future health professionals to think critically in technology-rich environments. Her instructional innovations reflect a balance between evidence-based content, ethical AI use, and interprofessional collaboration.
Areas of Interest: AI, Research, Teaching
Dr. Tompkins’ interests in AI and teaching focus on the digital adaptation and redesign of traditional in-person curricula using AI-enhanced assistive technology. Her scholarly work examines how AI can:
- Support the adaptation of face-to-face prevention programs into high-quality online learning experiences
- Enhance instructional design efficiency without compromising evidence-based integrity
- Improve learner engagement through adaptive and interactive technologies
- Provide formative assessment analytics that inform instructor decision-making
- Scaffold developmentally appropriate learning experiences for adolescent populations
- Strengthen facilitated discussion and critical thinking rather than automate instruction
She approaches AI as an assistive instructional partner and tool that augments faculty expertise, rather than replacing professional judgment or relational teaching presence. Her work emphasizes ethical oversight, transparency, and faculty control in AI integration, particularly in youth-focused and health-related educational contexts.
Teaching Areas for CRTLE Showcase
AI-Enhanced Digital Adaptation of an Evidence-Based Prevention Curriculum
As part of her exploration of future ready teaching strategies, Dr. Tompkins developed and is piloting a 10-session, 60-minute per session online substance use prevention curriculum designed for facilitated delivery.
The innovation was not simply a process of digitizing existing materials. Instead, it involved a deliberate redesign process that integrated AI-supported instructional tools to create an adaptive, engaging, and developmentally appropriate learning experience grounded in prevention science.
Key features of the innovation include:
- AI-assisted scenario development using branching simulations that model real-world adolescent decision-making
- Interactive dialogue exercises based on evidence-based prevention scripts
- Embedded formative assessments aligned with clearly defined learning outcomes
- Adaptive feedback mechanisms to support differentiated learning
- Structured facilitator-guided discussion components to preserve relational pedagogy
- Data-informed instructional adjustments through AI-supported analytics
Each 60-minute session follows a consistent structure: engagement prompt, interactive mini-lecture, simulation scenario based storytelling, guided discussion, and reflective journaling
The design preserves the essential elements of evidence-based prevention instruction—skill rehearsal, normative correction, and protective factor development, while enhancing accessibility and scalability through technology.
Innovation Impact
This AI-enhanced approach resulted in:
- A reduction in curriculum development time through structured AI-assisted content generation
- Increased instructional adaptability based on learner response analytics
- Enhanced student engagement through interactive simulations
- Preservation of facilitator-centered teaching and ethical oversight
The project demonstrates that AI integration in teaching can be both responsible and transformative when aligned with strong pedagogical foundations and disciplinary expertise.
Vision for Future-Ready Teaching
Dr. Tompkins’ work reflects a broader commitment to designing learning environments that are:
evidence-based, culturally-grounded, interactively engaging, technology responsive, human-learner-centered, and effectively feasible, acceptable, and usable. Her teaching innovation illustrates how AI can support the thoughtful digital adaptation of in-person curricula without compromising quality, rigor, or relational engagement. Through continued collaboration with CRTLE and interdisciplinary faculty, she aims to expand faculty capacity for responsible AI integration and innovative instructional design in nursing and health sciences education.
Dr. Abeer Omar Almughrabi,
Assistant Professor of Instruction
Civil Engineering
