As society explores AI for personal or professional use, it is critical to establish guardrails and AI literacy among all users. To further our understanding of AI in education, researchers in the College of Education are tackling the subject from a variety of angles. From topics in AI ethics and educator working conditions to how secondary educators may advance their own AI understanding, six faculty members have received funding from the University of South Carolina Office of the Vice President for Research to advance their research efforts. These projects lay the groundwork for further investment from extramural funding.
Join us in celebrating our six Advanced Support for Innovative Research Excellence (ASPIRE) AI funding recipients:
Lucas Vasconcelos, Ph.D. GRAD-AI: Graduate Readiness for Ethical & Digital AI Use
Vasconcelos’ project examines the impact of GRAD-AI, an asynchronous online training program, on doctoral students' ethical AI use, critical evaluation of AI and AI literacy. Using a postmodern critical framework and a mixed-methods design, the study explores how students distinguish ethical from unethical AI use and apply AI responsibly in graduate education. The findings will inform institutional policies, faculty practices and AI literacy initiatives that promote academic integrity in doctoral education.
Ruiqin Gao, Ph.D., University Students’ Judgment of their Use of Generative Artificial Intelligence in Assessment Tasks
Generative Artificial Intelligence (GenAI) tools are now widely used by university students to support assessment tasks, including brainstorming, drafting and revising coursework. However, institutional policies on appropriate AI use remain inconsistent, leaving students to independently determine when, how and to what extent to rely on these tools. This project conceptualizes these decisions as matters of judgment, defined as students’ evaluative and regulatory processes regarding the appropriateness, reliability, ownership and learning alignment of GenAI use. Using survey data from approximately 500 undergraduate and graduate students across disciplines, findings will inform evidence-based assessment design and support responsible, learning-oriented integration of GenAI in higher education.
Angela Starrett, Ph.D. and Kathrine Masyn, Ph.D., From Classification to Measurement: Integrating AI-Coded Open-Ended Survey Responses into Quantitative Models of Teacher Working Conditions
Every year, thousands of South Carolina teachers share in their own words what's supporting them and what's wearing them down. That written data has never made it into the statistical models we use to understand teacher retention. This project changes that: by using LLMs to code open-ended survey responses at scale and developing the methodological framework needed to integrate that text data into the same models as traditional survey ratings.
The work builds directly on a year of validation research by our SC TEACHER team, and it's designed as the empirical foundation for an NSF Methodology, Measurement, and Statistics proposal in January 2027. Because SC TEACHER partners with roughly 75% of SC school districts, the payoff isn't just methodological — it's a richer, more specific picture of what drives teachers to stay or leave, straight from teachers themselves.
Yingxiao Qian, Ph.D., Designing an Authentic AI-integrated Biomedical Curriculum to Develop Rural High School Students’ AI Literacy
Artificial intelligence (AI) is transforming biomedical research and healthcare, yet many students, particularly those in rural communities, have limited opportunities to learn about AI or explore AI-related careers. This project will leverage ongoing partnerships with medical research organizations to develop an AI-integrated biomedical learning experience for rural high school students in South Carolina. Through hands-on activities and real-world biomedical examples, students will build foundational AI knowledge while exploring how AI can be applied to health and biomedical questions. The project also aims to increase awareness of AI-enabled STEMM (science, technology, engineering, mathematics and medicine) career pathways and promote responsible and ethical uses of AI. By expanding access to AI education in rural schools, the project seeks to broaden educational opportunities and support students’ awareness of future educational and career pathways in AI-enabled STEMM fields.
Ismahan Arslan-Ari, Ed.D., Project TEACH-AI: Teaching AI Literacy for Secondary Teachers
Prioritizing the training of AI-literate teachers is crucial for preparing AI-literate students. This interdisciplinary project aims to address this need by increasing the number of high school teachers who are equipped with AI literacy knowledge and skills for ethical and effective integration of AI into language and literacy courses. To achieve this goal, we will design and develop an AI professional development (PD) training, implement the AI PD training in school districts in South Carolina, and evaluate the implementation from the perspective of high school teachers in order to use AI PD sessions in a variety of courses for a broader audience. This study will make a significant contribution to the field of AI in education by addressing a critical need related to teacher training in South Carolina. Participating teachers will not only develop technical knowledge about how various AI tools operate, but also pedagogical knowledge about how to integrate AI effectively into language and literacy classes. In addition, findings from this study will generate preliminary insights into teachers’ experiences with AI PD and offer empirically grounded implications for future research, PD design, and scaled implementation efforts.