CAREER: Teaching to Empower with Learning Analytics for College Students by College Students

University Of Maryland Baltimore County, Baltimore MD

Investigators

Abstract

CAREER: Teaching to Empower with Learning Analytics for College Students by College Students This project will explore an innovative approach to empower students to become productive users and creators of “learning analytics,” tools that use educational data to enhance learning. Despite being the primary beneficiaries, students have yet to be involved in the development of learning analytics. This project adopts a student-centered framework called TEEM (Teaching to Empower) by integrating data science and data literacy education at the undergraduate level. TEEM involves designing and implementing data science and analytics educational activities where students collect, analyze, and reflect on data about their own learning, well-being, and study habits. Based on those activities, the project will design and develop “Live Data Lab,” a hands-on, self-guided learning platform that will be accessible to a broader student community beyond data science majors. This platform will be piloted with about 500 first-year undergraduates and students enrolled in the pre-service teacher training program, at the University of Maryland Baltimore County and from community college partners. This project will enhance students’ skills in data science, analytics, data literacy, and self-regulation and contribute to educating a diverse workforce with the increasingly necessary skills to understand, process, and make use of data. TEEM is a research-education integrated framework that aims to engage and empower students in creating a more effective learning analytics system to enhance self-regulated learning while improving students’ data science and data literacy competency. It consists of three main parts: (1) design-based research in data science courses on active-learning-based learning-analytics-themed activities leveraging students’ intuitive knowledge; (2) design and development of a dual-purpose, hands-on, self-guided platform called “Live Data Lab” to disseminate student-created, expert-reviewed learning resources; and (3) pilot studies with a diverse group of students, including 500 first-year undergraduates, pre-service teachers, and community college students. The project's impact will be assessed through quantitative measures of data literacy and self-regulation and qualitative methods, including content analysis and interviews. This project will advance knowledge in learning analytics research and data science education. The insights gained from students’ involvement in the design process will inform the design of learning analytics tools that better reflect their needs. Moreover, deep involvement with their own data could lead to new ways to improve self-reflection and self-regulation. The open-source platform, teaching methods, and resources can be adapted for wider educational use, potentially benefiting students from higher education institutions, including community colleges and K-12 schools, both in formal and informal spaces. This CAREER project is funded by the NSF IUSE: EHR Program and the EDU Core Research Programs which support projects to improve the effectiveness of STEM education for all students. 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.