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Using Data Analytics for Advisors: StudentPaths and Concept Progression Maps
Abstract
Currently many advisors (e.g., in Computer Science) lack deep knowledge of all programs they are stewards of. Our proposal will move towards learning-centered advising by providing School of Computing and Information’s advisors with additional information that will improve student performance.
Advisors will be given student paths detailing student success and challenge groups when completing the program (StudentPaths), and on-going concept-level student performance (Concept Progression Maps). These tools will augment advisors’ memory and analytical power, and allow advisors to focus on student issues. We evaluate the tools with surveys and statistical analysis over a three-semester study.
Collaborators
Principal Investigator - Daniel Mosse
Sean Bridgen
Nathan Ong