Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…

How can we prepare students for a world where data-driven decision-making shapes nearly every aspect of life? "Data Minds: How Today's Teachers Can Prepare Students for Tomorrow's World" helps K-8 educators infuse data literacy into everyday lessons across disciplines, without overwhelming existing curricula. Data literacy is an ability…

Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it…

The application of big data in education sparks debates on its effects. Researchers explore its impact on learning outcomes, with divergent views on neural networks' potential and negative consequences. This study assesses big data's influence on basic literacy skills in music education for 5th graders. Using clustering and k-density analyses,…

Computer-mediated social learning contexts have become increasingly popular over the last few years; yet existing models of students' cognitive-affective states have been slower to adopt dyadic interaction data for predictions. Here, we explore the possibility of capitalizing on the inherently social component of collaborative learning by using…

This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…

To develop competency in science practices, such as data analysis and interpretation, chemistry learners must develop an understanding of what makes an analysis and interpretation "good" (i.e., the criteria for success). One way that individuals extract the criteria for success in a novel situation is through making social comparisons,…

As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…

This dissertation seeks to investigate how digital gestures connect to students' mathematical understanding when playing "From Here to There!" (FH2T). This investigation explores the intersection of three fields, game-based learning, embodied cognition, and mathematics education. I used three studies which break down the different…

Business analytics has become a critical tool in today's data-driven world, enabling organizations to extract insights, optimize decisions, and gain competitive advantages. As the demand for skilled professionals in business analytics grows, higher education institutions are increasingly focused on equipping students with the necessary knowledge…

Being able to understand, interpret, and critically evaluate data is necessary for all individuals in our society. Using the PreK-12 Guidelines for Assessment and Instruction in Statistics Education-II (GAISE-II; Bargagliotti et al., 2020) curriculum framework, the current paper outlines five evidence-based recommendations that teachers can use to…

Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…

This study was grounded in the spatial computational thinking model developed by the "3D Weather" project funded by the NSF STEM+C program. The model reflects a discipline-based perspective towards computational thinking and captures the spatial nature of computational thinking in meteorology and the reliance of computational thinking on…

This dissertation adopted the three-article format. The entire dissertation aims to explore Describing Critical Statistical Literacy Habits of Mind (CSLHM). The first article describes the creation of the CSLHM framework. The second describes how secondary preservice mathematics teachers enact CSLHM. The third article describes a common and an…