The Center for Teaching Excellence and Innovation is pleased to announce the recipients of the 2025–26 Teaching and Learning Grants. These grants support faculty-led initiatives that advance innovative, inclusive, and high‑impact teaching practices across the University of Hartford. Congratulations to this year’s awardees—whose project summaries appear below—for their creativity, dedication, and commitment to enhancing student learning and academic success. Their work represents an exciting range of approaches that will enrich our classrooms, curricula, and community
Recipients:
Mehdi Danesh has been awarded a 2025–26 CTEI Teaching and Learning Grant to strengthen student learning in environmental systems and building performance. His project develops simulation-based instructional materials that help students evaluate daylighting and energy strategies through applied, real-world case studies.
Lillian Kamal is delighted to receive the CTEI grant and will use it to implement the use of CoPilot as a tutor for applied math and graphing skills for introductory Economics courses. The generative AI agent will be trained based on specific solved examples (complete with steps) and will then be able to generate new practice questions for students to access on-demand tutoring. This innovation aligns with the quantitative literacy value rubric.
Gengyun Le's project introduces an AI-enhanced digital educational escape room (DEER) framework to strengthen active learning, critical thinking, and interdisciplinary engagement in undergraduate Biology courses at the University of Hartford. By integrating Copilot as a real-time support tool within gamified, puzzle-based challenges, the model fosters productive problem-solving, reduces cognitive overload, and builds both STEM content mastery and AI literacy. Co-investigators, Mingjun Li, PhD, Department of Computing Sciences and Somaye Seddighi-Khavidak, PhD, Department of Architecture
Shreya Malhotra's proposal focuses on redesign of the Principles of Macroeconomics (EC110) course to transform it from a passive survey of abstract models into an active laboratory for applied economic reasoning. The redesign is centered on three core pillars: Interactive Data Analysis, Collaborative Case-Based Learning, and Real-World Application, aiming to address the problem of low student engagement and superficial comprehension.
Solaleh Miar's proposal redesigns BE 402 (Biomaterials) by incorporating AI-supported machine-learning activities using Copilot to help students understand real biomaterials data more clearly and confidently in different applications, such as Tissue Engineering and Drug Delivery Systems. The goal is to make computational thinking more approachable for everyone while improving how students interpret and communicate engineering results.
Anastasiia Minenkova's project is aimed to redesign Applied Mathematics for Civil Engineers (M246) into an integrated, accelerated course that consolidates a substantial, multi‑discipline sequence of advanced mathematics with writing, collaboration, and MATLAB‑based computational modeling. Grounded in inclusive, active learning strategies, the course creates a cohesive interdisciplinary environment that supports diverse learners while building deep conceptual understanding and real‑world problem‑solving skills.
Laura Pence is planning an immersive AI experience for her students in the honors seminar, “Science and Public Policy.” In addition to discussing issues of AI regulation, data privacy, and intellectual property, the students will refine their prompt engineering skills as part of partnering with AI to produce professional-quality documents.
Carolyn Pe Rosiene's project introduces low-stakes coding challenges in CS 220P to reduce anxiety, build confidence, and promote mastery of core Data Structures topics through consistent practice and instant feedback. By leveraging auto-grading tools and reflective prompts, the approach fosters metacognitive growth and an inclusive learning environment, with potential for long-term scalability across different programming courses.
Amy Weiss' project "Teaching Generative AI: Ethics, Equity, and Innovation in the UHart Classroom" will explore various ways to incorporate generative AI into classroom activities and at-home assignments. The goal of the project is to demonstrate how AI can be used as a tool in the humanities classroom to 1) improve student engagement in class, 2) build students' AI literacy, and 3) increase students' career-readiness.