An AI-Augmented Phenomenographic Approach to Conceptualizing Undergraduate Students Experiences of Intercultural Team Cognition in STEM
Effective Years: 2022-2025
As society becomes increasingly globalized, STEM graduates are increasingly called upon to work with individuals from different cultures and backgrounds. Thus, organizations and governments expect STEM graduates to contribute as productive members and leaders of intercultural teams. This project is designed to conduct fundamental research on team cognition, an important component of teamwork training. Team cognition refers to the knowledge, interactions, and processes essential to effective team functioning. This project aims to examine intercultural team cognition specifically within computationally-intensive fields and, in the process, further develop the principal investigator’s STEM education research expertise. The project is supported by NSF's EHR Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators’ capacity to carry out high-quality STEM education research.
The mixed-method project will be based on data gathered through student reflections, video recordings of teamwork, a series of validated survey items, and semi-structured interviews from students enrolled in computationally-intensive courses that entail semester-long team projects. Three specific objectives guide this project. First is to develop the principal investigator’s STEM education research skills and expertise relating to artificial intelligence enabled methods of analysis. Second is to carry out a fundamental STEM education research project that will examine the ways undergraduate students experience intercultural team cognition in the context of solving computational challenges. Third, and finally, is to engage in phenomenographic research that employs both traditional coding methods and artificial intelligence-augmented techniques to analyze qualitative data. The project will enable comparisons of findings and has the potential to provide methodological insights. The PI will work with a mentor and advisory board from her institution that have extensive expertise in machine learning, natural language processing, deep learning algorithms, and building trustworthy systems that facilitate explainability, fairness, and accountability. An external advisory board will also include individuals with expertise in intelligent design tutors as well as individual and team cognition. The research, associated presentations, and interaction with the advisory boards aim to contribute to the fundamental knowledge about team cognition in an educational context.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.