What shapes statistical and data literacy research in K-12 STEM education? A systematic review of metrics and instructional strategies

Abstract

The pervasive digitization of society underscores the crucial role of data and its significant impact on decision-making across various domains. As a result, it is essential for individuals to acquire competencies in handling data. This need is particularly pertinent in K-12 education, where early engagement with data and statistics can lay a foundational understanding for future academic and professional endeavors. Additionally, K-12 education should provide students with critical skills necessary for navigating the complexities of daily life and making informed decisions in a data-rich society. This systematic review examines the state of research on statistical and data literacy in K-12 STEM (Science, Technology, Engineering, and Mathematics) education. It focuses specifically on cognitive, affective, and behavioral metrics and pedagogical approaches empirically investigated in this context. Using a rigorous selection process, we identified and synthesized 83 original empirical papers. Additionally, we invited the authors of these studies to share their perspectives on future strategies for addressing statistical and data literacy. The results indicate that the included studies primarily focus on the construct of statistical literacy, which is operationalized through a diverse array of metrics, predominantly within the context of mathematics education. We identified effective pedagogical approaches, such as authentic problem-solving and the integration of real-world data. The researchers surveyed emphasized the importance of interdisciplinary teaching, adapted curricula, and improved professional development for pre- and in-service teachers. Our findings underscore the growing relevance of this field, but suggest that integrated perspectives on statistical and data literacy within STEM subjects are limited.