Jennifer Noble, Assistant Dean of the School of Applied Technology at Alfred State, has been named one of seventeen members of the Data Science for Education (DS4EDU) Fellows program.
The program run through Carnegie Mellon University is designed to support learning professionals with a diverse set of skills and experiences. The one-year fellowship provides training in both educational data science methods and the types of edtech tools that are best suited to generating and analyzing robust learning data. Supported by the Department of Education’s Institute for Education Sciences (IES), the DS4EDU program will support cohorts of up to 25 participants, who will spend their fellowship working closely with a team of CMU learning and data scientists.
“I am honored to have this opportunity and excited to strengthen my ability to use data to advance equity and access in education,” commented Noble. “I look forward to collaborating with fellow educators and researchers, engaging in meaningful, impact-driven work, and applying these skills to create more inclusive learning opportunities and improved outcomes for all students at Alfred State.”
The program combines foundational skills in data science and instructional design with training on advanced methods and tools to instrument and research learning. The program emphasizes a trainee-designated project that is the focus of each individual’s work over the year. This approach ensures that the program has real-world relevance and capitalizes on the vision, ingenuity and experiences of the cohort. Fellows will emerge from the program as leaders, with expertise in the tools and methods needed to advance their projects and the field.
Late last semester, Noble and Jeff Stevens, Dean of the School of Applied Technology, co-presented at the Leadership in Higher Education conference in Philadelphia, PA. Their presentation, “Bridging Perspectives: Navigating Leadership Growth through Diverse Career Paths”, explored the evolution of leadership through two distinct career trajectories: one from a traditional academic pathway and the other from a non-traditional background.