Presenter: Justinas Grigaitis from UZH Department of Economics
I would like to showcase a few interactive web applications that I developed for my PhD research in behavioural economics and education. I used these applications for conducting field experiments with ~1,000 students at the University of Zurich over the past year and I am currently developing new applications for an experiment with ~600 middle-school students in India. My web applications involve AI features (e.g., chatbots and other Generative AI tools to improve student learning), behavioural tests, and surveys. I also develop separate applications for live experiment monitoring, so that PI and other researchers could see live data and always be in control without needing to run any code on their end.
The intended audience are assistant software engineers or researchers who conduct experiments with human subjects in behavioural economics, psychology, cognitive science, education, and other similar disciplines.
The main point will be to inspire ideas for new research questions that involve AI chatbots or leveraging Generative AI to facilitate the creation of behavioural experiments. In addition, I would emphasise the need for shared infrastructure and best practices within university labs or departments to make development of behavioural experiments more efficient and robust.
Finally, I would present arguments why using a modern web stack (e.g., React and Next.js) with Agentic AI is more effective than relying on third-party infrastructure like Qualtrics or oTree.