NSF Org:	SMA SBE Off Of Multidisciplinary Activities
Recipient:	UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE, THE
Initial Amendment Date:	January 10, 2020
Latest Amendment Date:	March 6, 2024
Award Number:	1950814
Award Instrument:	Standard Grant
Program Manager:	Josie Welkom Miranda jwmirand@nsf.gov  (703)292-7376 SMA  SBE Off Of Multidisciplinary Activities SBE  Direct For Social, Behav & Economic Scie
Start Date:	March 1, 2020
End Date:	February 28, 2025 (Estimated)
Total Intended Award Amount:	$313,025.00
Total Awarded Amount to Date:	$313,025.00
Funds Obligated to Date:	FY 2020 = $313,025.00
History of Investigator:	Michael Turner (Principal Investigator) mgturner@uncc.edu Matthew Phillips (Co-Principal Investigator)
Recipient Sponsored Research Office:	University of North Carolina at Charlotte 9201 UNIVERSITY CITY BLVD CHARLOTTE NC  US  28223-0001 (704)687-1888
Sponsor Congressional District:	12
Primary Place of Performance:	University of North Carolina at Charlotte 9201 University City Blvd. Charlotte NC  US  28223-0001
Primary Place of Performance Congressional District:	12
Unique Entity Identifier (UEI):	JB33DT84JNA5
Parent UEI:	N8DMK1K4C2K5
NSF Program(s):	RSCH EXPER FOR UNDERGRAD SITES
Primary Program Source:	01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	062Z, 9250
Program Element Code(s):	113900
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.075

ABSTRACT

This project is funded from the Research Experiences for Undergraduates (REU) Sites program in the Social, Behavioral, and Economic (SBE) Sciences Directorate. This program integrates research and education and has both scientific and societal benefits. The program targets undergraduate students from diverse backgrounds, particularly those from groups where research opportunities are limited and/or participation in research is underrepresented such as women and minority students. The Crime Analytics REU is a ten-week summer program designed to help students develop research skills and technical abilities in the multidisciplinary fields of data science and analytics, and to prepare them for graduate study or employment in a data-saturated economy following graduation. Specifically, the program seeks to: 1) aggressively recruit a diverse subset of undergraduate students to actively participate in innovative research projects that apply analytic tools to make decisions about crime; (2) expose students to foundational analytic methods early in their educational careers in hopes of encouraging their involvement in data science and an analytics-based field of study; (3) expose and engage students to research opportunities that demand communication and cooperation across experts in traditional disciplinary boundaries; (4) enhance students? educational experiences by exposing them to workshops, seminars, and social activities that enrich their professional development and inspire them to pursue graduate school; (5) foster shared interdisciplinary communication skills by offering opportunities to disseminate research findings via an annual undergraduate research symposium, annual professional conferences, and peer-reviewed journal outlets.

The Crime Analytics-REU site will operate by housing selected students on campus, and provide them with a stipend in exchange for their work on faculty-led research projects. The program is modeled around a team-based pedagogical concept in which students will be selected and assigned to interdisciplinary research teams that will use cutting-edge data technologies to explore problems related to crime and criminal justice. Students will be exposed to data science skills that include working with large data sets, data mining and manipulation, machine learning, crime mapping, quantitative modeling, and data visualization. Students will also be taken to visit leaders in the data industry, such as SAS, Google, Apple, and the Charlotte-Mecklenburg Police Department?s Crime Analysis lab. The research projects will culminate with the preparation and submission of a research manuscript for publication in an academic journal, and a public presentation of their research. Students will also participate in social and cultural enrichment activities as well as workshops designed to prepare them for graduate school and or professional employment in the data analytics field.

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.

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