Asee peer logo

Using Data Science to Create an Impact on a City Life and to Encourage Students from Underserved Communities to Get into STEM

Download Paper |


2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Computing and Information Technology Division Technical Session 1

Tagged Division

Computing and Information Technology

Tagged Topic


Page Count


Permanent URL

Download Count


Request a correction

Paper Authors


Elena Filatova City University of New York

visit author page

Assistant Professor at CUNY, New York City College of Technology, Department of Computer Systems Technology. Director of the Bachelor of Science in Data Science program.

visit author page


Deborah Hecht Center for Advanced Study in Education

visit author page

As Director of the Center for Advanced Study in Education, at the CUNY Graduate Center I am involved in a wide range of educational evaluations of funded and local projects. I also mentor graduate students interested in careers in evaluation.

visit author page

Download Paper |


In this paper, we introduce a novel methodology for teaching Data Science. Our methodology relies on the outlook of the student body in our college. Our college is an urban, commuter, HSI (Hispanic Serving Institution) school with 34% Hispanic and 29% Black students. 61% of our students come from households with an income of less than $30,000+. Thus, many students in our college come from the communities that are underrepresented in the STEM fields and in the decision-making positions in the government (on the city level, state level, country level). However, in our methodology, we want to flip the situation so that our students’ living situation does not hold them back but on the contrary, gives them an edge in their education. Our methodology combines case-based learning and the diversity of our student body who come from different city communities (location-wise, ethnicity-wise, income-wise). We demonstrate that this combination can be the basis of a powerful teaching method that delivers STEM material and engaging students in the learning process.

To evaluate our novel methodology we run a pilot study within one of our introductory classes designed specifically for the BS in Data Science program. In this program, we teach data analysis utilizing the data sets collected by the city agencies. We demonstrate that using real-life data sets encourages our students to compare the results of what they learn from the data about their communities and their everyday experiences. We believe that using such teaching approach can be a great start for igniting the interest in the field as well as in society-aware aspects of data analysis.

Filatova, E., & Hecht, D. (2021, July), Using Data Science to Create an Impact on a City Life and to Encourage Students from Underserved Communities to Get into STEM Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2021 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015