Interview Assessments: Incentivizing AI Use to Complement Student Learning
Spark Talk
Abstract
Oral examinations aren't new and neither is the temptation for students to shortcut learning. Instead of policing the correct use of AI, we have experimented with using interview assessments to incentivize students to use AI to complement and enhance rather than shortcut or replace their learning. Additionally, these interviews align with our efforts to include assessments consistent with what students will do in practice. In this talk, we will share what we have learned from implementing interview assessments across multiple courses and delivery modes.
Presenters
Marc Dotson
Assistant Professor
Marc Dotson is an Assistant Professor in the Data Analytics and Information Systems Department at the Jon M. Huntsman School of Business and a Project Mentor in the Analytics Solutions Center at Utah State University. Prior to joining the faculty at Utah State, Marc was an Assistant Professor in the Marketing and Global Supply Chain Department at the Brigham Young University Marriott School of Business. He graduated with a BS in Political Science from Southern Utah University, an MSc in International Political Economy from the London School of Economics and Political Science, and a PhD in Quantitative Marketing from The Ohio State University.
Marc is passionate about helping students learn how to use data to inform decision-making. He has taught courses and workshops across a variety of topics, including survey research, conjoint analysis, statistical programming, regression, Bayesian modeling, segmentation, and text analysis. He has mentored students in research projects and case competitions. Marc is always looking for ways to make technical concepts more accessible to students, both in and outside the classroom. His research is at the intersection of data analytics and marketing. This includes causal inference, Bayesian statistics, and machine learning, with a focus on choice modeling, unstructured data, and heterogeneity.
Reagan Siggard
Assistant Professor
Reagan Siggard is an Assistant Professor in the Data Analytics & Information Systems department at Utah State University’s Jon M. Huntsman School of Business. She earned her PhD in Instructional Technology and Learning Sciences, along with bachelor’s and master’s degrees in Management Information Systems, all from Utah State.
In the classroom, Reagan creates hands-on learning experiences that help students build strong technical and problem-solving skills. She teaches courses in Python programming, data warehouses, database management, and data visualization, and is passionate about keeping her curriculum current to reflect evolving industry demands. Beyond the classroom, she mentors students as a faculty advisor for the Data Analytics and Information Systems Student Association (DAISSA), helping them grow as leaders and professionals.
Reagan’s research explores how students learn and retain information, with a focus on information systems pedagogy and peer-to-peer interaction in online learning. She is committed to helping every student feel connected and supported while applying technical skills in meaningful and lasting ways.