Principal Investigator: Steven Sutherland
CoPrincipal Investigator(s):
Organization: University of Houston – Clear Lake
Abstract:
This project seeks to transform current practices in the teaching of scientific research methods by shifting the fundamental dynamics and focusing in a scientific domain that is relatable to a broad audience: designing and conducting social and behavioral science experiments. Scientific inquiry is key to making societal progress and improving our understanding of the world. Social and behavioral science programs are largely designed to prepare future researchers, but have a minimum expectation that students become critical consumers of research. Understanding the scientific method and the experimental methods used by researchers is necessary for establishing an ability to effectively assess the research that students will encounter in both the media and scientific outlets. Student understanding of scientific inquiry is significantly enhanced when anchored in inquiry experiences; however, opportunities for scientific research experiences are limited, even in research methods courses, due to the challenges of teaching experimental design and problems regarding access to and recruitment of participants. Without these experiences, students in higher education struggle to fully understand scientific inquiry. To address common barriers to learning how to conduct research, this project is designing a flexible, computer-based platform to be collaborative, narrative-based, engaging, and inspired by constructionist theories to facilitate learning with the use of artificial intelligence (AI) support.
The platform developed in this project will serve as a model of a new genre of constructionist research environments, that enable learners to leverage technologies to create, modify, and replicate experiments, recruit participants, and analyze their results to learn about the world. The design-based research approach will operate in two cycles; in each cycle, a revised module and set of tools will be deployed. This results in two major research contributions: (1) Using mixed-methods, the theoretical and educational contribution is to study the process by which students in higher education learn to conduct experimental research, and about the roles of AI assistance, collaboration, narrative, and activities motivated by curiosity, exploration, and reflection. (2) The technological contribution is an innovative, AI-assisted set of scenario creation tools that empower learners to create experiments and that allow us to understand how an intelligent, collaborative, engaging, narrative-based platform can support students in higher education in designing and conducting social and behavioral science experiments. With this system, it will be easier to create, run, replicate, and build upon studies and to reach out to a broader audience than the pool of university students used in typical in-person laboratory experiments. As a result, the platform will make it possible to transform social science research practices and even has the potential to foster new scientific discoveries.
