Developing Modernized Data Science Instruction in Psychology Curricula

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This project aims to serve the national interest by developing, assessing, and sharing psychology-based data science course materials for undergraduate education. Data science is an emerging and rapidly growing interdisciplinary field that uses computational methods to understand information in large datasets. There is an urgent need for evidence-based educational materials that support data science training for undergraduate students pursuing a vast array of academic programs. Psychology is an excellent program for data science integration because it is among the most popular undergraduate academic majors and it is especially attractive to women and underrepresented students. This Engaged Student Learning (Level 1) project will contribute to the development of exemplary STEM education and data science preparation for undergraduate students within psychology. It will reveal effective strategies for teaching modern data science skills and provide scientific guidance regarding best practices in such instruction. Finally, by freely distributing data science-infused psychology course materials that are available to teachers of any discipline, this project will empower educators and learners to adapt evidence-based data science content that has the potential to dramatically increase undergraduate students’ readiness for academic and professional success in a dynamic, information-rich world.This project will lead to the development of psychology laboratory research courses that intentionally embed and scaffold data science skills throughout a 15-week semester. These data science-enhanced courses will strengthen students’ computational skills while providing them with multiple opportunities for future professional and academic growth. The courses will empower students to apply a broad array of valuable, modern data science skills, rooted in computer programming, establish effective data acquisition, coding and analysis, explore large datasets, visualize complex behavioral and physiological data, and transparently communicate algorithmic processes to guarantee analysis replicability. The project includes a three-year, rigorous, pre/post research study to systematically assess the newly developed data science course experiences and determine how they influence students’ capabilities in critical thinking, quantitative literacy, and confidence in scientific and data science skills. The dataset will include a data science in psychology treatment group and a non-data science control group to compare gains in data science skills and data literacy confidence. Finally, the developed course materials will be released as publicly accessible Open Educational Resources (OER) so that the products of this project will contribute to the nascent pedagogy of data science. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.