Scholarship of Teaching and Learning (SoTL) Faculty Learning Community

Abbigail Walsh (Occupational Therapy): This SoTL project examines the integration of an AI-supported study bot designed to enhance student learning in OT 642: Occupational Performance II; Adults. The study bot provides structured, ethical, and course-aligned prompts to guide students in reviewing content, applying clinical reasoning, and preparing for assessments without replacing independent learning. Rather than offering direct answers, the bot encourages active engagement through case-based questions, concept clarification, and self-reflection. The project aims to evaluate the impact of the study bot on student confidence, study efficiency, and academic performance, as well as perceptions of AI as a learning support tool in occupational therapy education. Data will be collected through pre- and post-intervention surveys, and course performance metrics. Findings hope to contribute to emerging evidence on responsible AI use in health professions education and offer practical strategies for integrating technology to support clinical reasoning development in occupational therapy students.
Jennifer Maloney (Occupational Therapy): Using AI-Generated Vignettes to Support Clinical Reasoning Development in Level I Fieldwork, this SoTL project explores how AI-generated vignettes, used before and after short-term pediatric and adult fieldwork, impact occupational therapy students’ clinical reasoning skills. Using structured, case-based reflection, students analyze scenarios to practice decision-making, problem-solving, and prioritizing client needs across diverse settings. The study examines how pre- and post-fieldwork engagement with these AI-supported cases strengthens students’ ability to connect theory to practice. Findings aim to show whether integrating AI-generated materials into fieldwork preparation and reflection enhances readiness for real-world clinical practice, supporting safe, effective, and client-centered occupational therapy care.
Toni Woods Maignan (Nursing): In NURS 311: Quest Toward Individual Well-Being, students build a foundation for holistic nursing practice. Building on her doctoral research, Dr. Woods Maignan is exploring how generative AI can enhance this framework by strengthening clinical judgment and cultural humility through AI-supported reflection.Within a tight curriculum, generative AI offers a timely opportunity to scaffold self-reflection and evidence-based reasoning. Her work examines which AI supports, such as feedback on reasoning and culturally attuned scenarios, most effectively foster holistic thinking without replacing nursing judgment. She is designing a rigorous, classroom-based research project to evaluate AI’s impact on cultural humility. The study utilizes AI-generated cultural vignettes, employs pre- and post-surveys to measure growth, and compares scores between AI-assisted students and a control group. This work aligns with her goal of preparing students to deliver compassionate, culturally humble care in modern healthcare.
Carolanne Carty (Education)
Mary Jo Rosania (Education): This project is a self-study of teaching practice situated within EDUC 250: Art and Child Development that examines how the intentional integration of AI-supported reflective tools influences pedagogical Dr. Rosania's decision-making and role as an educator. Guided by self-study methodology (LaBoskey, 2004), this inquiry is iterative, reflexive, and improvement-oriented, positioning Dr. Rosania's teaching practice as both the site and subject of investigation. The study is embedded within a course with an established intergenerational partnership with a third-grade classroom at William Penn Elementary School and grounded in the Fred Rogers Institute’s Six Fundamentals of Learning and Growing. Within this context, Dr. Rosania designed a lesson in which undergraduate students use AI to synthesize multiple self assessments and learning artifacts, followed by structured critique of AI-generated outputs for clarity, accuracy, bias, and alignment with human experience. Data sources include reflective teaching memos, student artifacts, observation notes, and iterative lesson revisions. With a class of 24 students, the purpose is not to evaluate AI tools alone, but to document how engaging AI as a reflective partner reshapes Dr. Rosania's teaching practice within human-centered, arts-integrated pedagogy.
Randy Ziegenfuss (Education): From Learners to Co-Designers: Cultivating Collective Leadership in Doctoral Education, this SoTL project examines how doctoral learners transition from individual performers to collaborative co-designers within EDUC 811: Becoming a Stronger Practitioner. Drawing on the program’s four compass points—Objector, Inventor, Curator, and Storyteller—students engage in an advanced co-design experience in which they collaboratively design and facilitate learning for their peers. The central challenge lies in unlearning deeply embedded norms of individual accountability and cultivating the trust, structures, and culture required for authentic shared creation. This inquiry explores how intentionally designed space and scaffolds can support that shift, and how co-design experiences deepen leadership capacity, agency, and collective learning.
Klaire Brumbaugh (Speech-Language Pathology): The School of Rehab Sciences has numerous post-professional asynchronous doctoral programs that attract professionals from a variety of geographic locations. Due to the remote nature of the programs, building community requires intentionality. One strategy is to develop a community through communities of practice (CoP) groups designed around individual interests. This capitalizes on the role of self-efficacy, a critical element of adult education and universal design for learning. The goal of this project is to co-construct and establish student-supported CoP groups to foster a sense of belonging in the speech-language pathology doctorate program.
Catherine Brandes (Environmental Studies): This project examines how structured, reflective use of generative AI can support students’ sense of agency, conceptual understanding, and critical thinking in undergraduate science and technical communication courses. Focusing on two of Dr. Brandes's courses, Introductory Geology and Science Communication, the project investigates instructional designs that require students to articulate their own ideas first, then use AI as a tool for comparison, exploration, and revision rather than as a primary source of content or answers. Students engage in guided reflection on how AI influenced their thinking, what suggestions they accepted or rejected, and why. Drawing on student artifacts, reflective writing, and survey data, the study explores how intentional AI scaffolding shapes students’ confidence in their own reasoning and their ability to critically evaluate information and their own learning process. This work contributes to ongoing conversations about ethical and pedagogically sound AI integration in higher education, with particular attention to fostering a sense of agency, voice, and intellectual responsibility in learning.
Jen Norton (School of Professional Studies & Innovation): Through “Prompting Relevance: AI-Supported Task Design,” this SoTL project will investigate the intersection of generative artificial intelligence and student-centered pedagogy. As AI continues to reshape higher education, this study explores how technology can be leveraged not just as a tool for efficiency, but as a scaffold for deep, personalized learning. Focusing on adult learners in foundational psychology coursework, the project employs a constructivist framework to turn students into active co-creators of their curriculum. Participants will use generative AI to design customized assignments that bridge abstract psychological theories with their unique professional and personal realities. By documenting their "prompt-crafting" process and reflecting on their decision-making, students move from passive content consumption to active meaning-making. This research seeks to identify how such agency influences student engagement and metacognitive awareness. Ultimately, the project aims to establish a human-centered model for ethical AI integration that prioritizes relevance and disciplinary fluency.