current research

International Insights into the Academic Mindset of Economics Students

Coauthors Carlos Cortinhas, Jana Sadeh, Emily Marshall, Brandon Sheridan, Douglas McKee, Michael Cameron, Jennjou Chen, Bei Hong, Chiara Lombardini, Malte Ring, Michael Ryan, Alberto Ruiz, Javier Sierra, and Adeel Tariq.
Abstract This paper investigates the academic mindset of economics students across eight countries using a large-scale dataset collected through the Economic Education Network for Experiments (EENE) in 2023/24 and 2024/25. Surveys from 1,188 students and 14 instructors across 18 modules at 11 universities outside the United States measured four dimensions of academic mindset—belonging, self-efficacy, growth mindset, and perceived relevance—at the start and end of a teaching term. We find that students’ mindsets are dynamic and context-dependent rather than uniformly improving over time. While perceptions of belonging within economics and the discipline’s relevance tended to increase, general self-efficacy and beliefs about the accessibility of economics declined during the academic term. Gender consistently emerged as an important source of heterogeneity: non-male students reported lower self-efficacy and weaker perceived relevance of economics, with several gaps remaining evident by term’s end. Pedagogical context was also associated with outcomes: active learning environments and intermediate-level courses were often linked to stronger mindset measures, while larger institutions and later academic years were sometimes associated with weaker outcomes. Cross-national variation was substantial. These results highlight that student self-efficacy and identity with economics are associated not only with individual characteristics but also with pedagogical practice and institutional context. The findings point to the potential value of inclusive, interactive teaching and culturally sensitive approaches to support diverse participation in economics education worldwide.
My Contributions (CRediT) Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Visualization, Writing – Review & Editing.

Status: Revise and Resubmit

The Use of Generative Artificial Intelligence (Gen AI) in Economics Courses

Coauthors James Staveley-O’Carroll, Petar Stankov, Emily Marshall, Brandon Sheridan, Douglas McKee, Sarah King, Allen Bellas, Wendy Stock, Rik Chakraborti, Megan McCoy Dowdy, Anna Klis, Chelsea Dowell, Kelvin Wong, Justin Jarvis, Siny Joseph, Jonathan Ernst, Brian O’Roark, Kyle Montanio, Phil Ruder, George Orlov, Fikri Pitsuwan, Zahra Akbari, Basak Horowitz, Kristine West, Sarah Jacobson, Adeel Tariq, and Corissa Marson.
Abstract The use of Generative Artificial Intelligence (Gen AI) in economics classrooms has the potential to both improve learning-democratizing education, personalizing tutoring, and summarizing content-as well as harm it-reducing student effort, offloading critical thinking, and encouraging cheating. It thus behooves instructors to understand how Gen AI is used in their classes. To that end, we design comprehensive surveys on the use of Gen AI by both economics instructors and their students. Surveys are completed at the start and end of the 2025 Spring semester and provide a snapshot of perceptions, policies, and usage of Gen AI tools. Based on our results, we find a disconnect between instructor Gen AI policies and student perceptions of those policies. This implies the need for better communication. In addition, survey results show how students use Gen AI to help with both studying and completing assignments. While sentiment about usage of Gen AI for studying aligns between instructors and students, more instructor guidance in how best to use Gen AI for learning is recommended. Unsurprisingly, we find divergence between instructor and student sentiment regarding the use of Gen AI for completing assignment.
My Contributions (CRediT) Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Visualization, Writing – Review & Editing.

Status: Under Review

Evolution of Academic Mindset During Economics Courses

Coauthors Emily C. Marshall, Douglas McKee, George Orlov, William Goffe, Amel Ben Abdesslem, Terry Alexander, Allen Bellas, Brooks Depro, Fulya Ersoy, Paul Graf, Alan Green, Devon Hawkins, Olivia Healy, Basak Horowitz, Justin Jarvis, Siny Joseph, Anna Klis, Caroline Krafft, Marilyn Markel, Stefani Milovanska-Farrington, Gina Pieters, Olena Rarytska, James Staveley-O'Carroll, Jörg Stoye, Kristine West, Cora Wigger, and Kelvin Wong.
Abstract Research shows that non-male students and first generation college students enter their economics courses with lower scores on academic mindset measures (Marshall et al. 2025). This paper explores whether students' mindsets change during an academic term and, if so, which demographic, course, instructor, and institution characteristics predict these changes. A survey is administered at the beginning and end of the academic term, resulting in a sample of over 3,300 students from 37 instructors, and 25 institutions across the US. Results show that non-male students are more likely to report a worsening of their academic mindset and this result is robust to alternative definitions of a changing mindset. However, having a non-male instructor can dampen these effects. Students from underrepresented minority and ethnic groups and first generation college students do not appear to experience much change in their mindsets, for better or worse. Finally, results suggest that higher amounts of active learning may potentially mitigate worsening mindsets. These results serve as an important baseline for exploring interventions to improve the academic mindset of students.
My Contributions (CRediT) Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Visualization, Writing – Review & Editing.

Status: Working Paper

Complementing Collaborative Learning with Generative Artificial Intelligence

Abstract I describe an approach for integrating artificial intelligence (AI) into the economics classroom in a way that promotes critical thinking, engenders trust, and fosters AI literacy skills. Many instructors are understandably apprehensive about the current wave of technology because it brings with it questions about academic integrity, ethics, and equity. I propose a modification of the send-a-problem collaborative learning technique in which students first develop foundational knowledge individually, then probe that knowledge by joining teams and using AI to create complex problems, then finally solving the problems created by their peers. Students are surveyed at the end of the semester to reflect on their experience with the AI assignments, their attitudes towards using AI in an academic context, and their perceptions of the usefulness of the tool as a learning supplement. This study takes place over two semesters and includes two sections of Economics Principles, two sections of Intermediate Macroeconomics, and a Federal Reserve Challenge course, resulting in about 130 students being surveyed. Preliminary findings suggest that students enjoyed the AI activities, appreciated the value of creating problems, and recognized limitations of the technology.

Status: Working Paper

Other Scholarly Work & Research in Progress

Using Social Media to Enhance Teaching and Learning

Sheridan, Brandon J. (2024). EconEdNews, Fall, pp. 3–4.

Invited Contribution

The Success Stool: A Framework for Continually Improving as an Educator

Research in Progress