This research explores both survey design and how students engage with AI-based educational tools. From an survey perspective, key questions include how AI-generated reflective prompts can be tailored to maximize engagement and high-quality data collection, as well as how AI-driven tools can bridge the gap between traditional surveys and interviews in education research.

We also examine how students interact with AI-based educational tools through the lens of activity theory. A core question is how students conceptualize and respond to AI-generated feedback in the context of their collaborative learning experiences. This research considers how AI-mediated reflections shape students’ understanding of teamwork, decision-making, and group dynamics. By studying these interactions, we aim to better understand how AI can serve as a meaningful mediator in reflective learning and teamwork development.

Relevant Publications

• Rong, K., McColley, C. J., Werth, A., & Mburu, T. K. (2025). BOARD# 100: Work In Progress: Analyzing the effects of AI powered tools on STEM Learning and Pedagogical Research. 2025 ASEE Annual Conference & Exposition. [Link to Google Scholar]
• Mburu, T. K., Rong, K., McColley, C. J., & Werth, A. (2025). Methodological foundations for artificial intelligence‐driven survey question generation. Journal of Engineering Education, 114(3), e70012. [Link to Google Scholar]

Investigating Faculty Pedagogical Practices in Teamwork

Our team developed the Instructor Mindsets on Pedagogy and Attitudes towards Collaborative Teaming in Engineering (IMPACT) survey. This tool is designed to capture a wide range of engineering instructors’ perspectives across the United States, shedding light on the challenges and motivations surrounding the integration of teamwork into their curricula.

The respondents of this survey are engineering educators who have instructed an engineering course incorporating teamwork in any form within the past three years. This encompasses professors and instructors of all ranks across various disciplines and types of institutions (public, private, 2-year, 4-year, etc.), providing a comprehensive view of engineering instructor motivations and experiences across the country.

In the survey, participants are initially asked to reflect on a specific course that incorporates teamwork in any form. Keeping this in mind, instructors respond to a series of survey items grouped into six primary themes: (1) internal mindsets of student learning and intelligence, (2) external institutional and course contexts shaping the teaching and learning environment, (3) social support and challenges for instructors, (4) current teaching practices and experiences in the classroom, (5) motivations and attitudes towards teamwork, and (6) demographic information.

We conducted the survey with over 100 faculty members nationwide, representing a variety of institution types. We found that over 75% of the instructors reported that students feel safe bringing team-related issues to the instructional team; however, nearly the same percentage (72%) felt ill-equipped to effectively resolve these conflicts. This discrepancy underscores the pressing need to develop a more comprehensive and use-inspired understanding of teamwork, enabling instructors to facilitate it more effectively and equitably in their classrooms. Similarly, instructors reported that their students require assistance when it comes to teamwork skills: 62% agreed that students need guidance on how to work effectively with others. And 44% found it too difficult to assess individual contributions when students work in teams.

Relevant Publications

• McColley, C. J., & Werth, A. (2025). Faculty Espoused versus Enacted Beliefs on Teamwork in Engineering Education: Results from a National Faculty Survey. 2025 ASEE Annual Conference & Exposition. [Link to Google Scholar]
• McColley, C. J., & Werth, A. (2024). WIP: Initial Development of a Faculty Survey Tool to Measure Instructor Attitudes About Learning and Teaming in Engineering Coursework. 2024 IEEE Frontiers in Education Conference (FIE), 1-5. [Link to Google Scholar]
• Sivagnanamoorthy, I., Werth, A., Shah, R., & Shah, R. (2025). Towards an AI-Motivated Mathematical Skills Inventory for Future Engineers. 2025 IEEE Global Engineering Education Conference (EDUCON), 1-3. [Link to Google Scholar]

Course Redesign for Biomedical Engineering Design Education

Through the Cornell Course Redesign Initiative to Support Teaching for Engaged Learning (CRISTEL), we are transforming biomedical engineering design education by embedding reflective practices that cultivate expert-like design thinking. This effort includes redesigning a four-week design project in the introductory BME course and overhauling the BME 2080/2081 sequence.

Relevant Publications

• Bocian, R., Werth, A., & McColley, C. J. (2025). BOARD# 29: Work In Progress: Redesigning a biomedical engineering course to enhance design mindsets and skills. 2025 ASEE Annual Conference & Exposition. [Link to Google Scholar]
• Adaramola, A. O., Werth, A., & McColley, C. J. (2025). BOARD# 19: WIP: Students’ Perceptions of an Innovative Attendance Policy for a Biomedical Engineering Seminar Course. 2025 ASEE Annual Conference & Exposition. [Link to Google Scholar]
• Khojah, R., Werth, A., Broadhead, K. W., Dobrucki, L. W., Geiger, C., & Rubenstein, D. A. (2025). Integrating Generative Artificial Intelligence Tools and Competencies in Biomedical Engineering Education. Biomedical Engineering Education, 1-17. [Link to Google Scholar]
• Fuchs, S., Werth, A., & Butcher, J. T. (2024). Work in Progress: Evaluating the impact of student cognitive and emotional responses to real-time feedback on student engagement in engineering design studios. 2024 ASEE Annual Conference & Exposition. [Link to Google Scholar]