Faculty Fellows Program
The Division of Academic Affairs, in partnership with the CTLE, is sponsoring the Faculty Fellows Program for the 2023-2025 academic years. This program supports faculty in integrating the ethical use of AI, student-centered pedagogy, and the Saint Leo Core Values. It aims to enhance teaching methodologies and enrich the student learning experience. Faculty Fellows will explore ways to incorporate AI into classrooms to foster active engagement, critical thinking, and student-centered learning across disciplines. The program runs from January 2024 to May 2025, with two cohorts participating in either Spring and Fall 2024 or Fall 2024 and Spring 2025.
For any inquiries or further information, please feel free to reach out to Dr. Candace Roberts – candace.roberts@saintleo.edu, in the Center for Teaching and Learning Excellence.
Program Overview and Responsibilities
The Faculty Fellows Program will emphasize integrating AI into academic disciplines while upholding ethical practices and aligning with Saint Leo’s Core Values.
Faculty Fellow will:
- Actively participate in a two-semester program and attend meetings (approximately 4 hours per month).
- Participate in individual and group learning activities throughout the year to further develop knowledge and skills and to foster conversations about the relationship of AI, active learning, critical thinking, and value-based education.
- Identify areas in the curriculum, within the specific faculty discipline, where AI may play a role in advancing student learning and competitiveness when entering the workforce.
- Collaborate, provide feedback on teaching projects, and brainstorm with colleagues.
- Engage in being the discussion leader, reading and presenting articles related to the focus and purpose of this FFs Program.
- Serve as leaders among the faculty and university community in disseminating and implementing FF learning experiences.
- Collaborate with other faculty members not part of the FFs cohort on values-based AI integration into current curricula.
Faculty Fellows Expected Deliverables:
- Identify one course within your discipline that you regularly teach. You will re-design this course to integrate AI, adhering to sound pedagogical principles grounded in active learning, critical thinking, and SLU Core Values.
- Form a Special Interest Group (SIG) focused on AI applications related to your discipline. This SIG can be for faculty, students, or a combination of both populations. You will pilot it during your first semester and conduct regular meetings on your second semester (four meetings total). Ideally, you, your colleagues, and students will continue the SIG beyond this program.
- Facilitate workshops or webinars for faculty and/or students on meaningful AI integration into the curriculum or preparing students for the workforce. At least two workshops or webinars are required (one for faculty and one for students in your program).
- Create at least two AI-integrated classroom activities (template provided). These classroom activities will be archived in the Faculty Fellows “Curated List of AI Resources for Teaching and Learning Across the Disciplines”.
- Lead the group discussion at least twice during the year.
- Write a conference proposal/presentation or grant that fits within effective AI practices and ethical principles.
Qualifications
Faculty Fellows must be full-time faculty members who agree to participate voluntarily. Priority is given to faculty members who can impact at least one master syllabus, preferably a master syllabus for a course required in a major or a high-impact course. The Faculty Fellows must also be committed to strengthening their teaching skills while integrating AI. As members of a teaching institution, Faculty Fellows are expected to engage in pedagogies that are grounded in ethical principles, critical thinking, active learning, and the SLU Core Values. Selection was conducted by a Faculty Fellows Selection Committee appointed by Academic Affairs.
Remuneration for the Faculty Fellows Program is $2550 or a course release per semester per faculty member.