STEM Workforce Development  

STEM Learning and Learning Environments  

Broadening Participation in STEM

Understanding Cueing Gesture within Video Learning Environments for Statistics Education

Effective Years: 2024-2027

Mathematical literacy and statistical reasoning are critical for making day-to-day decisions in a world that is quickly moving online and increasingly data driven. For example, many lifestyle choices such as smoking, eating meat, or using a seatbelt while driving require individuals to think and reason about the probability of different outcomes rather than simple cause and effect. Unfortunately, a large percentage of students have misconceptions about probability and statistics that can lead to incorrect reasoning. More concerning is that these inaccurate ideas often persist even after taking courses in statistics. One promising line of research demonstrates that mathematics instruction that utilizes visual representations, authentic problem-solving, and physical manipulatives can help address these concerns when these components are connected through instructor and student gestures. However, less is known about how gestural strategies apply to statistics education, and even less is known about how to apply these strategies to online and remote learning environments. Therefore, this project aims to conduct a large-scale study using a diverse sample of high school and undergraduate students to examine how prompting learners to gesture when learning statistics content in video-based learning environments may improve their understanding of statistical concepts and procedural knowledge. The main objective of this project is to evaluate an approach to designing video learning environments (VLEs) for teaching statistics concepts that use gestures during instruction and cue learners to perform gestures. Using a mixed methods approach, researchers will employ design-based methods to create VLEs that incorporate instructional gestures, cue students to perform these gestures, and monitor and provide feedback about student gestures during statistics instruction using webcams that are standard on most computers. Researchers will also utilize randomized control trials to assess the impact of VLE design quantitatively on conceptual understanding of statistics concepts, procedural knowledge about how to solve statistics problems, transfer of understanding to future learning, and the impact on self-regulated learning. Case-study methods will examine which features of gesture effectively scaffold student learning and enhance transfer during online instruction. The project will contribute to our understanding of embodied learning, specifically the impact of metaphorical gesture on self-regulated learning and conceptual understanding of foundational math concepts. It will also contribute to an emerging body of literature situated at the junction between gesture and video-based, online learning. Researchers will make the resulting VLEs freely available to educators and researchers on the project’s website, where they will also post a design guide highlighting the gestures and other pedagogical features that were successful as well as those that were not. This project is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. This Level II project focusing on STEM Learning and Learning Environments is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. 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.