REU Site: Leveraging The Learning Sciences & Technologies to Enhance Education and Learning in Secondary Schools

Worcester Polytechnic Institute, Worcester MA

Investigators

Abstract

This Research Experiences for Undergraduates (REU) Site at the Worcester Polytechnic Institute will provide a ten-week summer undergraduate research experience in learning sciences and technologies, with a focus on understanding achievement gaps among secondary school students. It will host three cohorts of eight students each summer, engaging 24 unique students. The increased use of educational technology has increased the amount of educational data available to researchers. These data have higher external validity than short-term laboratory studies, supporting the potential for making stronger conclusions about effective instructional practices. These data contain knowledge that could be analyzed to enhance understanding of how students best learn and how best to teach them. This REU will enable young researchers to analyze this data and contribute to understanding high-impact teaching practices, how to group learners for instruction, and what type of feedback or remediation is most applicable to a learner. These research activities will provide new information about the effectiveness of both technological and traditional educational interventions for a variety of learners in secondary school classrooms. REU undergraduates will experiment with deep learning approaches to analyze data from secondary school classrooms that use learning technologies. The goal will be to interpret and understand classroom activities that lead to meaningful student learning. Undergraduate researchers will use data collected by ASSISTments and Graspable Math. These are learning environments for mathematics developed by researchers at Worcester Polytechnic Institute and deployed in several schools throughout the United States. Undergraduates will analyze data using educational data mining techniques, such as student modeling to better estimate intervention impacts and clustering to determine which students are most similar. In addition, they will use E-TRIALS, a platform that simplifies running A/B experiments, to test educational interventions such as new hints or video instruction developed by teachers. To analyze classroom engagement, they will use ACORN, a deep-learning technology that assesses classroom dynamics by automatically monitoring student gaze and learner engagement. This project is supported by the NSF Improving Undergraduate STEM Education Program: Education and Human Resources, which supports research and development projects to improve the effectiveness of STEM education for all students. By funding REU sites, the program supports development of the next generation of STEM professionals. 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.