Teaching and Learning with Technology worked with faculty as part of the 2024 Faculty Engagement Awards that focused on the theme of “Generative Artificial Intelligence (AI) for Teaching.”
UNIVERSITY PARK, Pa. — Thirteen Penn State instructors recently completed their 2024-2025 participation in Penn State University Libraries’ Teaching and Learning with Technology (TLT) Faculty Engagement Awards program by using generative artificial intelligence (Gen AI) to aid in course design and planning, content delivery, and increasing student engagement. As the 2025-2026 program theme is being finalized, three cohort participants shared how they worked with TLT to incorporate Gen AI into their teaching.
Nikki Mattson, teaching professor of applied linguistics, explored Gen AI to create interactive learning experiences, particularly generating role-plays, case studies, and structured student discussions. She also used Gen AI to co-develop assessments and evaluations, such as an Interpersonal Reactivity Index (IRI) survey, Kahoot quizzes, and case-study-based evaluations. Mattson also shared her Gen AI experience with students while teaching them responsible AI engagement through structured assignments.
By applying these practices in her courses, Mattson said, she found that “these applications led to higher engagement, increased confidence in academic English, and more personalized learning experiences tailored to different student backgrounds and language proficiency levels in my classes.” She also used Gen AI to change her approach to scholarship and project management, including providing targeted feedback, aiding in qualitative data analysis and producing templates for proposal development.
Michelle Kaschak, associate teaching professor of English at Penn State Lehigh Valley, focused on using Gen AI in courses that have primarily first-year students, such as ENGL 15S: Rhetoric and Composition and ENGL 83S: Fist-Year Seminar in English. She was interested in better understanding Gen AI, how it can be used for lesson planning and teaching, how students were using it, and how she could encourage them to use it in ways that do not violate academic integrity.
Kaschak said she used Gen AI for rubric creation, co-formulating summative feedback for student papers and aiding in writing lesson plans particularly for scenario and discussion questions. She also crafted assignments for students to use Gen AI in their papers’ revision process.
“After playing with AI for the past year, I have learned that the prompt is the key. Students who do not write good prompts are not getting a good output,” Kaschak said. She plans to elevate her students’ assignments by integrating GenAI “in little pieces and have them look at the outputs critically.”
Christina Olear, assistant teaching professor of accounting at Penn State Brandywine, said she focused on using Gen AI within ACCTG 405: Principles of Taxation I to streamline processes, enhance course organization and design, and elevate teaching methods to engage and challenge students. Olear used Gen AI to break down her existing content into more digestible formats like tables, charts, and bullet points. Similarly, she used AI to create infographics and flow charts to help students easily understand difficult material.
Olear’s use of Gen AI convinced her that “Generative AI has transformative potential in education, particularly in improving accessibility, fostering inclusion and preparing students for a technology-driven future” and that utilizing “AI for administrative purposes has been especially valuable, as it has allowed me to develop skills that I can apply in helping students leverage AI within the accounting discipline.”
Olear said she has used Gen AI to incorporate more relevant and up-to-date examples into her lessons without spending exorbitant amounts of time searching for them. She has crafted concise and effective Canvas course announcements more efficiently, created an Excel assignment that focused on an advanced area of filtering tools applied to statistics, and enhanced her course materials for accessibility by creating alternative text content for images.
Faculty Engagement Award participants are chosen through an application process that is expected to open in late March 2025. They work closely with TLT instructional designers to explore effective ways to integrate a particular technology. Award winners also collaborate with other participants through faculty meet-ups to share insights and best practices.
To learn more about the TLT Faculty Engagement Awards program, email Amy Kuntz at [email protected].
