Implementing HIPs can be a heavy lift for instructors, particularly in general education (GenEd) courses in which class sizes are often large and, as a result, student engagement challenging. The primary objective of the proposed project is to develop tools and resources through which faculty can assess their course-based implementation of high-impact practices (HIPs) using Generative AI. Our project leads from Georgia State University’s (GSU) Center for Excellence in Teaching, Learning, and Online Education (CETLOE), the College of Arts and Sciences, and GSU's EPIC Program will work with 8 faculty from different disciplines to develop the proposed toolkit. 

This proposal has its foundation in a GenEd course within the Institutional Priority area aligned with the USG’s Core IMPACTS: Perspectives 2003. Our project team has co-instructed the course over the past three years using two HIPs central to the course design: project-based pedagogy in affiliation with Freshman Learning Communities. Further, we integrated these HIPs successfully in large-enrollment settings (approximately 125 students in FA22 and 23; 289 in FA24; pending enrollment of 450 in FA25). 

Within the past year, we piloted using Generative AI as an assessment tool, specifically as one that could provide students with meaningful feedback, as students worked in teams to develop and conduct a semester-long project. To do this, we created a Project Scaffold to guide students through generating research questions. Students utilized our inquiry-based approach by collaborating on questions that they identified as local issues of importance. They then engaged with any Generative AI tool they chose, using prompts we developed to guide them in refining questions to be subject to investigation in a way achievable for freshman-level students. We threaded AI prompts through the entirety of the three-part scaffold in ways that students received real-time feedback on aspects of developing their projects, including generating ideas on potential data sources related to their topic and determining how tasks could be delegated among team members to complete the project.  

Another assessment-focused AI application we piloted, and request support to optimize, was qualitative analysis of student-authored discussion posts. To do this, we exported discussion posts from our LMS and asked the AI tool, Copilot, to extract unique themes that could be used to anchor in-class discussions and identify strong student posts to highlight in class. We encountered various obstacles in our approach and support for this project will help us to explore different tools that could make a significant difference.  

With the support of this grant, our project structure is centered on the curation of an AI-based “HIPs Assessment toolkit” for instructors, particularly, at the level of courses in the GenEd Core Curriculum. Our Project Scaffold and Discussion Post Analysis will be two components of the toolkit, but we will work over the course of the year with an interdisciplinary group of faculty to create additional approaches that will be applicable to courses across the curriculum. 

This project aligns with GSU’s broader efforts to enhance HIPs as part of our University’s Strategic Plan.  Ultimately, by integrating HIPs in this large-enrollment, GenEd course, we are creating Common Intellectual Experiences as our curriculum is horizontally aligned with the first-year experience.  

While this project will be based out of GSU, our expected outcomes are that the products generated through this work will be widely available for dissemination and will be applicable, particularly, across all USG institutions due to the GenEd focus of this proposal. Our ability to successfully bring these tools to fruition will, not only serve students, but also save instructors significant amounts of time as well as add a sense of ease to formative assessments that can be deployed in large-enrollment settings. We posit that because GenEd class sizes tend to be, on average, larger than upper-division courses, this project has the potential to reach thousands of students across the university system at scale. A major advantage, however, to our approaches is that the deliverables that will be produced will be applicable across course levels and class sizes.  

Anticipated challenges are a.) engaging and incentivizing instructors to apply new approaches in their courses; and b.) overcoming potential hesitation in using AI to guide student work. To address this, we propose the majority of support from this grant be used to incentivize instructors to work as part of our team on developing and refining our project deliverables. We propose that this Toolkit will facilitate implementation and assessment of HIPs in large-enrollment, lower-division courses through innovative use of AI-generated feedback for both students and instructors.