Where Research and Analytics Drive Educational Innovation

This research examines how blended and HyFlex course designs shape student learning, engagement, equity, and instructor experience. The work began with pilot studies exploring student and instructor experiences in blended and HyFlex courses and has since expanded through the NSF-funded project, Improving Learning Outcomes and Equity in Blended Online and Face-to-Face Learning.

The project investigates how students engage across online and face-to-face learning modalities, how course design influences learning outcomes, and what types of instructional support help educators create effective blended courses. Findings have informed instructor resources, professional development opportunities, conference presentations, and scholarly publications. The project has also collected data across multiple blended courses and supported a learning community for instructors engaged in blended teaching.

This work focuses on research and partnership-building related to artificial intelligence literacy and ethics. Through an NSF-funded planning grant, one component brings together Indigenous community members, learning scientists, university educators, and technology industry experts to explore how culturally centered AI literacy can be defined and advanced through community-engaged partnerships.

An NSF-funded conference supported the development and facilitation of a three-day HyFlex Generative AI Ethics Module Design Sprint, which equipped educators with ethical frameworks, pedagogical strategies, and structured support for creating discipline-specific AI ethics modules. In collaboration with the MSU Ethics Institute and the Center for Teaching and Learning Innovation (CTLI), CERA engaged more than 60 educators from 30 institutions representing 41 disciplines to support the broader adoption of ethics-centered AI literacy across higher education.

This project evaluates how students and educators understand, use, and perceive emerging AI tutoring systems. Initial work examined student awareness, perceptions, and use of Tailored Tutor, an AI tutoring tool, using pre-survey data collected from students in a business course. The evaluation combines quantitative and qualitative evidence to understand better how students interacted with the tool and how they assessed its usefulness for learning.

In spring 2025, this work expanded to evaluate HiTA, and fall 2025 research examines faculty perceptions of HiTA using post-survey data. Together, these efforts help MSU partners make evidence-informed decisions about AI tutoring implementation, instructional support, and future research on AI-assisted learning.

As part of the Math Fellows project, CERA is analyzing data from fall 2024 and spring 2025 to better understand the impact of the Support Undergraduate Learning Assistant Program. The findings will help instructors and program leaders identify supports that can enhance student experiences and improve outcomes in gateway mathematics courses.