Seven professors from the University of Illinois’ Gies College of Business have been selected as Faculty Innovation Scholars for the 2025-26 academic year. The Faculty Innovation Scholars program identifies and supports faculty who undertake innovative learning activities and develop educational materials that advance the College’s commitment to fostering excellence in business education. These learning activities and educational materials often will be adaptable across multiple courses. Launched in 2023, the program has previously funded 16 projects resulting in curricular innovations and scholarship of teaching and learning.

Aric Rindfleisch and Myoung Kim: Rindfleisch and Kim will conduct an experimental study on "Humanized Online Teaching via Instructor’s AI Avatar and Voice," investigating how AI-generated feedback delivered using an instructor avatar and synchronized voice impacts student trust, engagement, and perceived learning outcomes in high-enrollment, asynchronous courses. The ultimate findings will be critical for educators, as the results are intended to guide faculty development and instructional design by providing evidence-based strategies for incorporating AI into asynchronous instruction without sacrificing relational pedagogy.

Elizabeth Luckman: Luckman proposes a Mentorship Project Extension, aiming to build upon a successful pilot in an asynchronous online undergraduate course by creating a more structured and dedicated learning experience for the graduate near-peer mentors. The core innovation is providing graduate mentors with formal coaching and mentoring training that they can apply in real time, This relational learning project focuses on enhancing the undergraduate online learner experience, developing critical people skills that AI cannot replicate, and strengthening the Gies community through cross-program engagement.

Eric Larson: Larson aims to research the effectiveness and viability of using AI grading for subjective, short-answer written responses within the PrairieLearn platform. The innovation directly addresses the ability to maintain academic integrity and quality assessment in high-enrollment environments by comparing traditional objective questions against AI-graded subjective questions. The primary goal is to determine if this approach is a viable assessment tool that can help eliminate the cost and burden of manual grading while allowing instructors to assess real learning objectives.

Hayden Noel: Noel is focusing on enhancing the ethical incorporation of AI into assessment by refining the Technology Acceptance Model for AI Grading (TAM-AIG), specifically by systematically manipulating transparency (rubric disclosure) and human oversight across assignments. This study builds on the findings of a related project and will include undergraduate and graduate courses, incorporate high- and low-stakes assignments, and systematically manipulate transparency to determine the best combination of AI use, rubric disclosure, and oversight for improving fairness, trust, and learning outcomes.

Vishal Sachdev: Sachdev will pursue the development and evaluation of VentureBot, an AI coaching platform that uses specialized AI agents to provide intensive, personalized guidance to entrepreneurship students throughout the startup journey, focusing on market research, competitive analysis, and pitch preparation. The research positions Gies as a pioneer in educational AI implementation, the dissemination plan includes an open source release of the VentureBot codebase with implementation guides for other institutions. This pilot will generate practical frameworks for scaling personalized coaching through coordinated AI assistance, directly addressing Gies' growth in entrepreneurship education enrollment.

Ye Joo Park: Park is focusing on developing an advanced, scalable autograder for Jupyter notebooks, building on the applicant's existing Python package, Jupygrader. The innovation aims to seamlessly integrate the autograder with GitHub Classroom and Canvas. This tool aims to significantly reduce the grading burden for large iMBA courses which often require coordinating 10 or more graders. Furthermore, the autograder provides immediate feedback for students, ensures fair and consistent evaluation, and links automated tests directly to rubric items to provide clarity on learning goals.