Experiential Data science for Undergraduate Cross-Disciplinary Education (EDUCE)

Title Experiential Data science for Undergraduate Cross-Disciplinary Education (EDUCE)
Faculty/College/Unit Science
Status Active
Duration 3 Years
Initiation 04/01/2017
Project Summary

EDUCE seeks to develop a uniform experiential learning framework that is cross-disciplinary and collaborative to equip undergraduate students in the life sciences with basic competency and literacy in data science as it pertains to microbiome sequence information. To achieve this, EDUCE will develop and implement a mechanism to augment undergraduate training in the Department of Microbiology and Immunology (MICB) with basic analyses and statistical principles and microbiome data processing and interpretation – skills that transcend any one course in the department. In phase one, EDUCE will integrate new data science modules into existing third and fourth year courses and offer experiential learning activities including open office hours, social problem solving activities and workshops. Through this combination of integrated course modules and experiential learning activities EDUCE will provide persistent benefits to undergraduate students to better prepare them to address complex social, environmental, and technological challenges in an increasingly collaborative and data-driven workforce.

Funding Details
Year 1: Project Year Year 1
Year 1: Funding Year 2017/2018
Year 1: Project Type Large TLEF
Year 1: Principal Investigator Steven Hallam
Year 1: Funded Amount 81,833
Year 1: Team Members

Nancy Heckman, Department Head, Statistics, Science
Gabriela V. Cohen Freue, Assistant Professor, Statistics, Science
William Mohn, Professor, Microbiology and Immunology, Science
Martin Hirst, Associate Professor, Microbiology and Immunology, Science
David Oliver, Instructor, Microbiology and Immunology, Science