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A Learning Management System-Based Early Warning System for Academic Advising in Undergraduate Engineering

By Andrew E. Krumm, Richard Joseph Waddington, Stephanie D. Teasley and Steven Lonn

Abstract

This chapter describes a design-based research project that developed an early warning system for an undergraduate engineering mentoring program. Using near real-time data from a university’s learning management system, we provided academic advisors with timely and targeted data on students’ academic progress. We discuss the development of the early warning system and detail how academic advisors used it. Our findings point to the value of providing academic advisors with performance data that can be used to direct students to appropriate sources of support

Topics: Learning Analytics, Assessment, Testing and Evaluation, Data Mining and Knowledge Discovery
Publisher: Springer New York
Year: 2014
DOI identifier: 10.1007/978-1-4614-3305-7_6
OAI identifier: oai:deepblue.lib.umich.edu:2027.42/107974

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