The Latest Projects in Business Education

Students in the modular classroom, news as an influencer on stock market returns, and using data to discover anomalies.


In a working paper, Heikki Lehkonen, assistant professor at the University of Jyväskylä School of Business and Economics in Finland, and Kuntara Pukthuanthong, associate professor of finance at the University of Missouri Trulaske School of Business in Columbia, are using the tenets of behavioral finance to discover whether the positive and negative emotions expressed in news and social media posts can influence or even help predict stock market returns in the days after such content appears. The researchers will first focus on U.S. markets and media and next on those in different countries to determine whether national cultures and institutions change how emotional sentiments affect global markets.


Researchers at the University of Michigan College of Engineering in Ann Arbor have received a US$300,000 Improving Undergraduate STEM Education Program grant from the National Science Foundation to study how professors and students use classrooms with movable tables and flexible seating. Cindy Finelli, associate professor of electrical engineering, and research fellow Aaron Johnson are observing how students learn and interact in modular classrooms and asking faculty to share how the spaces have affected their teaching. So far, faculty have noted that monitors minimize distractions, while circular tables on wheels encourage students to get to know each other and work more effectively in teams. View a video of the classroom in action.


Bijan Raahemi of the University of Ottawa’s Telfer School of Management in Ontario, Canada, has received a CAN$105,000 Discovery Grant from Canada’s Natural Sciences and Engineering Research Council to design and verify algorithms in the areas of healthcare, corporate finance, and engineering. As part of his research, Raahemi will analyze the data that social networks and organizations gather about their users and customers to discover behavioral and statistical anomalies. Such anomalies could be predictors in a range of contexts, from the severity of a particular flu season to the likelihood of a cyberattack.