Data Science Education

This research area investigates the principles and practices of data science education. Scholars examine how to effectively teach data science concepts, tools, and methodologies across various educational levels, from K-12 to higher education and professional development. Research includes developing curricula, exploring pedagogical approaches for computational thinking and data literacy, and assessing student learning outcomes in data science. Methodologies often involve qualitative studies of teaching practices, quantitative analyses of student performance, and the design and evaluation of educational interventions.

The development of data science expertise is crucial for Arkansas's growing technology sector, advanced manufacturing, and agricultural industries, which increasingly rely on data-driven decision-making. Research in this area contributes to building a skilled workforce capable of analyzing complex datasets relevant to the state's economy and addressing challenges in areas like public health surveillance and environmental monitoring. Understanding how to best educate the next generation of data scientists and data-literate citizens is a key objective.

This field draws on expertise from higher education research, interdisciplinary education, and innovative teaching methods. Engagement spans multiple institutions across Arkansas, fostering a collaborative environment for advancing data science education throughout the state.