Programmatic Strategies to Engage and Support Undergraduate Women in Applied Mathematics and Computer Science

Abstract

This paper describes the implementation of a STEM scholarship program which utilized a holistic approach to providing a multi-dimensional student support system. The program has been successful in encouraging and supporting women in Applied Mathematics and Computer Science by offering a diverse suite of extracurricular opportunities, actively engaging them in organized events, research projects, and participation in STEM communities, and helping them achieve higher GPAs and shorter times to graduation. The supported women also benefitted from close mentoring relationships with the faculty mentors. The program emphasized the development of empowering settings for women’s engagement and achievement, which act to sustain and expand interest in mathematics and computing, and thereby help them to see themselves as future professionals in the field.

KEYWORDS:

• Women
• mathematics
• Computer Science
• undergraduate
• retention
• support
• Science, Technology, Engineering, and Mathematics (STEM)
• scholarship

1. INTRODUCTION

This paper describes the implementation of a STEM scholarship program at New York City College of Technology (City Tech), a non-residential undergraduate institute in the City University of New York (CUNY) system, that serves a diverse body of students in the New York City metropolitan area. Designated as a Hispanic-Serving Institution, City Tech had a pre-pandemic enrollment of 17,000 students, of whom 34% were self-reported Hispanic, 28% Black non-Hispanic, 21% Asian, 11% White, 2% Other, and 4% Nonresident. Thirty-one percent of our students were born outside of the US, with 143 countries represented. More than 60% self-identified as first-generation college students. A majority of the students (80% incoming freshmen and 67% continuing students) receive need-based financial aid. Sixty-one percent have reported a household income of less than $30,000.¹ The institution offers both associate and baccalaureate degree programs in a flexible, comprehensive “two plus two” model, whereby students may enter an associate degree program while working on developmental and prerequisite coursework and transition at their own pace into a baccalaureate degree program. According to the National Science Foundation (NSF), City Tech leads nationally in the number of associate degrees awarded to minority students.²

In this article, we describe efforts to include, engage, and support women in undergraduate Applied Mathematics and Computer Science programs at City Tech. The efforts were part of a larger scholarship program supported with funding from the NSF S-STEM (2015–2020) with the goal of increasing the participation, retention, and graduation rates of STEM students with financial need. The targeted STEM majors included baccalaureate degree programs in Applied Mathematics, Applied Chemistry, and Biomedical Informatics, and associate degree programs in Computer Science and Chemical Technology. The latter two majors provided the “two plus two” pathway into baccalaureate programs, whereby students in the associate Computer Science program transitioned seamlessly into the baccalaureate Applied Mathematics program, and students in Chemical Technology into Applied Chemistry or Biomedical Informatics.

The STEM scholarship program was modeled to an extent on programs such as the University of Maryland’s Meyerhoff Scholars Program, which has demonstrated success with underrepresented minority students in STEM − perhaps the most successful endeavor to date focused on increasing STEM diversity [20]. Our STEM scholarship program had a strong focus on engaging and supporting women and underrepresented minority students through a holistic approach, encompassing financial, academic, social, and professional support.

Of the 94 students supported by our scholarship program, more than 70% were women or underrepresented minorities.³ Most of the students belonged to one or more disadvantaged groups, i.e., immigrants, non-native English speakers, first-generation Americans, first-generation college students, as well as varied ethnic groups. Our program supported 46 women in STEM majors. Eleven of these women were in the Applied Mathematics program and six in the Computer Science program. The seventeen math and computer science women represented a diverse group of eight Asian, two Black, five Hispanic, and two White students.

In this paper, we report on the design of the programmatic efforts, its inclusion and engagement strategies, and effectiveness in the retention and graduation of mathematics and computer science women. Although the number of women the study focuses on is relatively small, we believe it is important to add to the perspective on best practices for increasing women’s participation and representation in applied mathematics and computer science, particularly for those from underrepresented or disadvantaged ethnic and socio-economic groups.

2. LITERATURE REVIEW

Mathematics and computer science have long been viewed as disciplines dominated by men. Despite efforts to close the gender gap, data from the National Center for Education Statistics (NCES) show that the percentage of degrees in mathematics and computer science earned by women still lags behind. Data from 2019 to 2020 show that only 42% of the mathematics baccalaureate degrees, 21% of the computer science baccalaureate degrees, and 21% of the computer science associate degrees were earned by women [21]. Studies show that factors such as gender stereotypes, unfriendly male-dominated STEM department cultures, lack of female and minority role models, sense of inadequacy, and social and academic isolation experienced by women are some of the key reasons for the gender gap in the mathematics and computer science field [1, 13, 14, 23].

In addition, the share of baccalaureate degrees earned by Black and Hispanic women is dramatically underrepresented – standing at 1.9% and 4.4%, respectively of Mathematics bachelor’s degree awarded, and 2.2% and 2.1%, respectively of Computer Science bachelor’s degree awarded [21]. The intersectionality of gender and ethnicity points to complex factors responsible for the disproportionate underrepresentation and presents barriers to the formation of mathematics identity for Hispanic and African American/Black undergraduate women as they often face multifaceted discrimination based on both their gender and race [5, 15].

Studies further point to an amalgam of social factors, academic difficulties, as well as financial stresses that all act as hindrances to women’s persistence [5, 10]. These factors may be compounded by a difficult transition to college, which is especially true for first-generation students [6, 19] and challenges in completing introductory mathematics courses [4]. The struggles are further exacerbated by the perception of the academic environment as unfamiliar and alienating [2, 22] and academic isolation for having little or no interaction with professors and peers [9, 17].

The conflation of numerous social and academic factors works together against many women’s propensity to maintain an interest and develop an identity as a mathematics or computer science professional [12]. Concerted efforts are required to formulate solutions to these obstacles.

Recent research shows that persistence in mathematics and science programs is associated with students’ ability to identify with relevant careers in the field [3], and to find connections to their personal goals [16]. Additionally, students who are mentored by faculty with a vested interest in the student’s academic success are more likely to be retained and graduate from that major [8]. For women in STEM, women faculty and other female role models may be particularly influential, as exposure to such models increases career motivation, academic and career aspirations, and professional identification [14].

There are numerous models that have resulted in increased participation and graduation rates, as well as successful transition into STEM graduate programs or careers. The PEERS program at UCLA utilizes academic and career seminars, holistic academic counseling, research seminars, and collaborative workshops for first-year STEM students [26]. Other successful programs include the Biology Scholars Program at University of California, Berkeley, Gateway Science Workshops at Northwestern University, and the LA-STEM at Louisiana University. Interventions that are widely recognized as essential and effective STEM support include building a supportive and inclusive environment, team learning, mentoring, advising, peer counseling, research experiences, as well as financial support [11].

To counter alienation and cultural isolation, some mathematics departments put special efforts towards women and minority-student integration through individual mentoring and extracurricular activities, e.g., the Math Mentoring program at Duke University [25] and the Women in Applied Mathematics Mentorship Program at the University of Washington [27]. Some successful programs adopted a “stepping-stone” model, which relies on the multiple influence of various female role models at different stages of students’ academic path [23]. On the other hand, the Women and Computing Initiative (WCI) has been successful in making females feel less isolated by creating a critical mass of women and thereby changing the learning environment from “masculine” to more gender diverse [18]. Dasgupta et al. report a similar outcome with undergraduate engineering women from the University of Massachusetts, Amherst, finding that women participated more actively and performed more successfully when they were placed in teams of either mostly women or an equal number of women and men [7].

3. THE STEM SCHOLARSHIP PROGRAM

The STEM scholarship program was led by a team of four faculty, three of whom were women in STEM, who provided leadership, served as role models, and mentored students who participated in the program throughout the students’ academic career in the institution. In designing the program, we selected components which have demonstrated success in recruiting, engaging, and retaining women and underrepresented minority students. We utilized a holistic approach integrating high-impact practices into different facets of the program through financial, academic, social, and career support (Figure 1).

Figure 1. The STEM Scholarship support structure.

The main components in our design included: (1) Financial support; (2) Active recruitment of women and underrepresented minorities; (3) Robust and sustained one-on-one academic advising and mentoring; (4) Early STEM professional and research experience; and (5) Building a STEM community. In the following sections, we describe each of the scholarship program components in detail. Hereafter, we refer to the STEM Scholarship program as the “scholarship program” and to the participants as “supported students.”

3.1. Financial Support

One of the key goals of the scholarship program was to support academically talented students with financial need. Financial support was a key component of the scholarship program. A criterion for acceptance into the program was a demonstration of financial need. In addition to state and federal financial aid packages, the supported students received up to $3100 per semester to bridge the gap in their “unmet financial need⁴” which on average was approximately $3500 per semester.⁵

College data show that the majority of the students reported working a part-time job while in college, and more than 27% reported working more than 20 h a week. The financial support offered by the scholarship program was significant in the sense that it helped alleviate financial pressure, allowing students to work less and focus more on their studies.

3.2. Active Recruitment of Women

Students were recruited from selected STEM and non-STEM majors through multiple efforts. Although primarily by flyers, college announcements, information sessions, and emails, students were also recruited through advisors, instructors, and faculty mentors of undergraduate research. In addition to financial needs, applicants were evaluated by the program team based primarily on the following criteria: a GPA of 3.0 or higher, faculty recommendation letters, and a strong interest in STEM stated in the application essay and interview. Students must declare or change their majors to one of the five STEM programs to be eligible for the scholarship.

Recruitment of women to the scholarship program had been challenging. In the first few semesters, there was no woman applicant from computer science and only a few women applicants from applied mathematics. To increase the number of women applicants from these two majors, we expanded our outreach efforts, and most notably through the recruitment efforts and the encouragement of women program team members, we were able to increase the participation of women in the scholarship program at times (Table 1).

Table 1. Number of students supported by the STEM Scholarship program.

Students Supported by the STEM Scholarship Program (Women/Men)
Semester	Fall 2015	Spring 2016	Fall 2016	Spring 2017	Fall 2017	Spring 2018	Fall 2018	Spring 2019	Fall 2019	Spring 2020	Total
All Supported Students	9/14	12/16	11/12	9/12	13/13	15/15	11/8	15/7	14/9	10/7	119/113
Applied Mathematics	2/6	3/4	3/1	3/3	3/6	4/5	3/2	6/2	6/5	3/5	36/39
Computer Science	0/3	0/4	0/2	0/2	2/1	3/3	4/4	2/4	0/1	0/1	11/25

Forty-seven of the 111 (42%) awards to applied mathematics and computer science students were given to women. This is still slightly lower than the overall scholarship program which gave 119 of the 232 (51%) awards to women. Nevertheless, the initial semester was followed by a period of greater participation of STEM women in the program.

3.3. Robust and Sustained One-on-One Academic Advising and Mentoring

Supported students were required to meet with program faculty two to four times per year for advising, mentoring, and career counseling. Just as other successful programs, we found advising and mentoring to be an essential component in maintaining student momentum and academic success. More than just mapping out the academic plan to graduation, the faculty advisors steered students into undergraduate research, peer leading, and many other STEM opportunities; they were also mentors who connected with students, invested in their success, and encouraged them to pursue graduate study and STEM careers. Collected qualitative data suggested that women participants tended to credit the close contact and advice they received from faculty mentors for the academic success they achieved.

3.4. Early STEM Professional and Research Experience

Studies have shown that early STEM professional and research experience is important in building STEM identity [24]. Through the many institutional and program-sponsored activities, the supported students were exposed to a range of STEM experiences such as seminars, lecture series, lab tours, and field trips to learn from scientists and researchers and to explore a variety of scientific disciplines and subfields. A great effort was made to include a strong representation of women and underrepresented minorities among the speakers and to introduce a wide range of interdisciplinary topics, not only to broaden students’ perspectives, but to help them become aware of the range of job opportunities in mathematics, computer science, and other possible STEM fields.

Although research was not a requirement of the scholarship program, it was strongly promoted and widely publicized to the supported students. Students were connected to and encouraged to participate in various undergraduate research programs that the institution offered. Supported students were also encouraged to collaborate with each other, which led to many interdisciplinary collaborative projects. As a result, about 75% of the supported students were engaged in at least one research project during their time in the scholarship program.

Students were encouraged to present their research at local, regional, and national conferences. Anecdotally, many students indicated to us that they had never been to an academic conference or engaged in any research projects prior to joining the scholarship program. Through undergraduate research, not only did they engage in STEM learning and develop a STEM professional identity, some shared in written reflections and interviews that it was a transformational experience, which helped orient them towards graduate work and STEM careers.

3.5. Building a STEM Community

Beyond its identity as a scholarship program, an advising program or a research program, the scholarship program provided a space for building a STEM community that fostered a sense of belonging through informal gatherings, mixed STEM activities, networking, collaboration, and an exchange of information on internship, research, graduate school, jobs, and other STEM opportunities among the supported students. Whether formal or informal, these events nurtured a friendly learning environment and widened the student support network. Moreover, women from various STEM programs would come together to support each other or collaborate on projects, diminishing the sense of academic and social isolations often experienced by women in STEM. Nearly 100% of supported students attended at least one organized event each semester.

To sustain the STEM community over time, the supported students stayed connected even after graduation. Alumni were invited back to give talks about their current STEM jobs and to share their experience, knowledge, and advice. All supported students opened a LinkedIn account and testified to its importance in enabling them to stay connected and informed.

Beyond the program, supported students were encouraged to contribute to the larger STEM community in their departments or the institution, for instance, to serve as peer leaders in the Peer-Led Team Learning (PLTL) program. The amalgam of academic and social support benefitted both the peer leaders, as they gained confidence and leadership experience, and the students they helped, creating a better sense of shared identity within the STEM community.

In short, we believe that factors such as collaborative work in small teams, the inclusion of peer support, and the participation of women role models such as scientists, faculty, peer leaders, and program alumni have been crucial to the success of the scholarship program.

4. RESULTS

Below, we report on the academic performance of the applied mathematics and computer science women supported by the STEM scholarship program in terms of degree completion rate, graduation data, credits earned, and GPA.

4.1. Retention and Graduation of Women in Applied Mathematics and Computer Science

From Fall 2015 through Spring 2021, a total of 29 women graduated from the Applied Mathematics degree program, of whom 10 (or 34%) were supported by the scholarship program. During the same period, a total of 41 women graduated from the Computer Science degree program, of whom 5 (or 12%) were supported by the scholarship program. Although these numbers seemed small, they were not insignificant, as they represented a considerable portion of the graduates who were impacted by the scholarship program.

In addition, Table 2 shows that 100% of the supported women in applied mathematics completed their programs compared to only 59% of the unsupported women in the comparison group⁶ with GPA of 3.0 or greater. The unsupported women with GPA below 3.0 had a completion rate of about 30%.¹¹

Table 2. Degree completion status of all applied mathematics and computer science students (Fall 2015–Spring 2022)⁷

Degree Status of All Applied Mathematics and Computer Science Students (Fall 2015–Spring 2022)
				$N$	Active students	Completed a degree	Discontinued without a degree	% Completed a degree
Applied Mathematics	Women	Supported	All	11	0	11	0	100
		Unsupported	GPA ≥ 3	29	7	13	9	59
			GPA < 3	57	17	12	28	30
	Men	Supported	All	20	0	18	2	90
		Unsupported	GPA ≥ 3	96	20	43	33	57
			GPA < 3	130	28	41	61	40
Computer Science	Women	Supported	All	6	0	5	1	83
		Unsupported	GPA ≥ 3	74	22	21	31	40
			GPA < 3	153	48	31	74	30
	Men	Supported	All	10	0	8	2	80
		Unsupported	GPA ≥ 3	324	91	109	124	47
			GPA < 3	949	298	131	520	20

Similarly, in Computer Science 83% of the supported women have completed their degrees versus 40% of the unsupported women with comparable GPA and 30% of the unsupported women with lower GPA. Overall, between Fall 2015 and Spring 2022, the percentage of the supported women (and men) in applied mathematics and computer science who completed degrees far exceeded that of the unsupported women and men in the comparison group with comparable GPA.⁷ Sixteen (94%) of the supported women in applied mathematics and computer science graduated successfully with a degree.

4.2. Semester Credits Earned and GPA

Using number of credits earned and GPA, we compared the academic progress of the supported women with a comparison group of women in the same major who were not supported by the scholarship program but who had a GPA above 3.0. The supported women in Applied Mathematics outperformed the unsupported women in terms of mean semester credits earned and mean semester GPA. See Table 3. On average, the supported women in Applied Mathematics earned 13.7 credits per semester and a GPA of 3.8 compared to the comparison group, which on average earned 11.2 credits and a 3.1 GPA. It also seems that the supported women were more likely to maintain a full-time status, compared to the unsupported women.⁸ In Computer Science, our data are inconclusive due to the low number of supported Computer Science women. In some semesters, there was only one supported woman–thus, the GPA average is based on one person. See Table 3. For additional details, see Table A5 in the Appendix.¹²

Table 3. Mean semester credits and GPA earned by applied mathematics and computer science students.¹⁰

Mean Semester Credits and GPA Earned (Fall 2015–Spring 2020)
				Mean credits	Mean GPA
Applied Mathematics	Women	Supported	All	13.7	3.8
		Unsupported	GPA ≥ 3	11.2	3.1
			GPA < 3	8.2	2.2
	Men	Supported	All	14.5	3.4
		Unsupported	GPA ≥ 3	11.3	3.2
			GPA < 3	8.2	2.1
Computer Science	Women	Supported	All	11.5	3.3
		Unsupported	GPA ≥ 3	11.8	3.4
			GPA < 3	8.4	1.9
	Men	Supported	All	14.3	3.6
		Unsupported	GPA ≥ 3	11.3	3.3
			GPA < 3	7.7	1.8

4.3. Time to Graduation and Degree GPA

A comparison between the supported and unsupported women shows that the supported women in Applied Mathematics graduated with a higher mean degree GPA than the supported men and the unsupported women and men in Applied Mathematics.⁹

The supported women in Applied Mathematics earned on average a cumulative GPA of 3.8, which is 0.3 higher than the supported men and 0.7 higher than the unsupported women and men in the same major (see Table 4). More significantly, supported women and men completed the Applied Mathematics degree in fewer number of semesters than the unsupported women and men finishing the same degree. On average, the supported women completed the baccalaureate degree in Applied Mathematics in 8.8 semesters – that is, 2.4 semesters earlier than the comparison group, and 3.6 semesters earlier than the average number of semesters to graduation of all unsupported women. To a large extent, this was a result of advising and reduction of credits not counting towards the degree, more credits taken on average per semester, and fewer interruptions in the supported women’s study due to fewer financial pressures. The comparison is less remarkable for the supported women in Computer Science. The latter graduated with the same mean degree GPA and took the same amount of time to graduate as the comparison group.¹³

Table 4. Mean degree GPA, number of semesters to graduation, and credits earned in Applied Mathematics and Computer Science¹² (Fall 2015–Spring 2021).

Mean Degree GPA, Number of Semesters to Graduation, and Credits Earned (Fall 2015–Spring 2021)
				$N$	Mean degree GPA	Mean no. of semesters to graduation	Mean total no. of credits
Applied Mathematics graduates	Women	Supported	All	10	3.8	8.8	136
		Unsupported	GPA ≥ 3	11	3.4	11.2	135
			GPA < 3	8	2.7	13.9	147
			All	19	3.1	12.4	140
	Men	Supported	All	16	3.5	9	139
		Unsupported	GPA ≥ 3	38	3.5	9.3	132
			GPA < 3	31	2.6	15	140
			All	69	3.1	11.7	135
Computer Science graduates	Women	Supported	All	5	3.4	5.8	95*
		Unsupported	GPA ≥ 3	17	3.4	5.8	66
			GPA < 3	19	2.7	7.7	69
			All	36	3.1	6.8	68
	Men	Supported	All	7	3.4	5.1	67
		Unsupported	GPA ≥ 3	86	3.4	6.4	71
			GPA < 3	98	2.6	8.2	74
			All	184	2.9	7.4	72.5

*There is an outlier − a student with 126 transfer credits prior to earning the Computer Science degree. If excluded, the mean total number of credits earned would be 77.

5. EXPERIENCES AND CURRENT STEM PURSUITS OF SUPPORTED WOMEN IN APPLIED MATHEMATICS AND COMPUTER SCIENCE

At the time of this article submission, all 11 applied mathematics women supported by the STEM scholarship program have graduated with the baccalaureate degree in Applied Mathematics with distinction. Six received Summa Cum Laude; the rest received Magna Cum Laude or Cum Laude. Among them were a valedictorian and a salutatorian. Three of these women are currently pursuing a master’s degree in computer or data science. One woman is in a computer science PhD program, and another in an economics PhD program. Two of the women are working in STEM-related fields.

Five of the six computer science women graduated with an associate degree in Computer Science. Three of them are pursuing or have earned a bachelor’s degree in Computer Science; one has earned a bachelor’s degree in Computational Physics and is currently pursuing a master’s degree in nanoscience; another has earned a bachelor’s degree in management. The supported women in both baccalaureate and associate degrees demonstrated STEM persistence beyond their program, and many went on to pursue higher or post-baccalaureate degrees or careers in STEM-related fields.

Anecdotally, some of these women shared with us that before joining the scholarship program they had low self-esteem and self-doubts about what they could accomplish. They faced a lack of support from their families, where women’s education was not valued in their culture. Many were first in their family to attend college. Several women talked about their struggles as immigrants, having to overcome the language barrier and navigating through an unfamiliar academic environment.

Some recounted concerns as they advanced to higher-level STEM courses where gender imbalances became prominent and uncomfortable. As a result, one applied mathematics woman changed her major to economics which she felt had a better gender parity, but later changed back and completed the degree in Applied Mathematics. Another woman reported situations when her male classmates did not take her seriously because she was a female, which made her feel ignored and slighted. One woman who initially majored in accounting said she experienced self-doubt every day until she encountered a mathematics professor who encouraged her to major in Applied Mathematics, mentored her in undergraduate research, and recommended her to the scholarship program.

The women reported that the support provided by the STEM scholarship program was essential in helping them persist and complete their degree program. More than the financial and academic support, the social, emotional, and career support was essential. They appreciated the inclusive environment at the gatherings where they felt a sense of being equal, being heard, and being valued for their contributions. The experiences they underwent as a result of involvement in the STEM community and research projects helped to clarify their motivation and led towards the next step in their STEM pursuit.

6. CONCLUSION

This article describes programmatic strategies for engaging and supporting undergraduate women in Applied Mathematics and Computer Science. It outlines the program components that have contributed to the retention and graduation of the participating women. The measurable outcomes have pointed to the participants accumulating more credits per semester and earning higher GPAs, thus facilitating faster degree completion and a better position from which to pursue graduate study or join the STEM workforce. The success of the program includes more intangible impacts, such as a heightened sense of belonging, self-efficacy, STEM identity, and persistence by the participants.

The design of a STEM scholarship program involving several dimensions, as opposed to a single one, appears to have been beneficial in ensuring the academic, social, and career support of women. Together with women in other STEM degrees, women in applied mathematics and computer science attained a strong presence through the critical mass strategy; they formed collaborative relationships and supported each other in combating gender stereotypes, which contributed to their increased confidence and sense of empowerment.

A key contributing factor to the success of the program was the women on the faculty team, who served as role models, mentors, and advisors and maintained close relationships with the supported women throughout their academic journey. The faculty team was committed to providing an inclusive and supportive STEM community that acted to sustain and expand student interest in mathematics and computer science, thereby helping them to see themselves as future professionals in the field. The critical work involved in fostering the academic success of women in mathematics and computer science is (and should be) a critical national priority, and we believe that our approach represents a contribution to its realization.

ACKNOWLEDGEMENTS

The STEM scholarship program and research were supported by funding from NSF S-STEM grants #1458714 (IRB approval #2018-0083) (2015–2020) and #1930437 (IRB approval #2019-0627) (2020–2024). All participants signed a consent to participate in the research study. The authors thank the students for their participation.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Science Foundation [S-STEM grant #1458714/2015 and #1930437/2020].

Notes on contributors

Sandie Han

Sandie Han is Professor of Mathematics at New York City College of Technology of the City University of New York (CUNY). She received her bachelor’s degree from Bryn Mawr College, master’s from Queens College, and doctorate from CUNY Graduate Center. She has extensive experience in program design and administration. She was the mathematics department chairperson from 2015–2021. Prior to that, she was the Computer Science program director and a college/high school collaborative program coordinator. She was PI on a US DOE MSEIP grant and Co-PI on a NSF S-STEM grant. Her research interests include number theory and mathematics education. Her work on Self-Regulated Learning and Mathematics Self-Efficacy won the 2013 CUNY Chancellor’s Award for Excellence in Undergraduate Mathematics Instructions. She is passionate about increasing student engagement and participation in STEM, particularly to empower women and underrepresented minorities. She organized many CUNY wide faculty and student events and is the 2022–23 CUNY faculty leadership fellow serving in the role of Assistant Dean for Academic Technology & Pedagogy.

Nadia Stoyanova Kennedy

Nadia Stoyanova Kennedy is Associate Professor in the Department of Mathematics and Program Director of Mathematics Education at the New York City College of Technology. Between completing her master’s and doctoral degrees, she spent 15 years as a full-time high school mathematics teacher and a curriculum developer. She serves regularly as a consultant for the International Baccalaureate (IB) program on curriculum, assessment, and examiner training. Her research interests center on philosophy of mathematics education, dialogic teaching, teacher professional identity, and teacher professional learning, with a particular emphasis on critical approaches to mathematics education and on the promotion of dialogue in the mathematics classroom. In addition to authoring numerous articles, she is Editor of the volume, Dialogical Inquiry in Mathematics Teaching and Learning: A Philosophical Approach.

Diana Samaroo

Diana Samaroo earned her PhD in Biochemistry from the CUNY Graduate Center. She is Professor in the Chemistry Department at New York City College of Technology. She has experience in curricular and program development, as well as administration as the Chairperson of the Chemistry Department for six years. She served as co-PI on several federal grants, which include NSF S-STEM, NSF RCN-UBE, and NSF HSI-IUSE grants. Many of her projects focus on academic success, integrating undergraduate research into the curriculum, improving student retention, and first-year experience. Additionally, she has mentored several undergraduates at the college. Dr Samaroo’s research interests include nanomaterials, drug discovery, and therapeutics.

Urmi Duttagupta

Urmi Duttagupta joined the Math Department at New York City College of Technology in 2003. She received her baccalaureate degree in mathematics from The Ohio State University and her MS and PhD in Applied Mathematics jointly from New Jersey Institute of Technology and Rutgers University. Her research interests include optimization, epidemiology, graph theory, and biodiversity. She served as a visiting research faculty at the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) at Rutgers numerous times. She also worked as a short-term visitor at the National Institute of Mathematical and Biological Synthesis (NIMBioS) at University of Tennessee, Knoxville and was invited to participate in several investigative workshops. She has numerous publications in peer-reviewed journals to her credit and is the recipient of several grants including CURM-mini grant, multiple MAA NREUP grants, a SENCER leadership fellowship, numerous NSF grants, PSC-CUNY, and Department of Homeland Security (DHS) awards. Dr Duttagupta has extensive experience mentoring more than 40 students through various programs.

Notes

1 The data reported in the article is based on the institution data from Fall 2019. Current and past institution data can be found at the link https://www.citytech.cuny.edu/about-us/facts.aspx.

2 https://facultycommons.citytech.cuny.edu/sponsored-programs/institutional-description/.

3 We use the NSF definition for underrepresented minority groups which include Blacks or African Americans, Hispanics or Latinos, and American Indians or Alaska Natives.

4 The “unmet financial need” was determined by the Financial Aid office on the basis of students’ completed Free Application for Federal Student Aid (FAFSA).

5 This was based on the average unmet need of the supported students in Spring 2019.

6 The comparison group was comprised of students of the same gender and major whose cumulative GPA were 3.0 or greater.

11 This table considers all students enrolled in Applied Mathematics and Computer Science degrees from Fall 2015 to Spring 2022. Each student is either active or inactive; if inactive, a student has either completed (earned) a degree or discontinued their education without a degree. The percent completion is the number of students who completed a degree divided by the total number of students excluding active students. Students who double majored in Applied Mathematics and Computer Science are counted in Applied Mathematics, not in Computer Science.

7 The comparison group was comprised of students of the same gender and major whose cumulative GPA were 3.0 or greater.

8 At City Tech, the minimum required semester credits for full-time status are 12 credits.

12 For semester by semester credits earned and GPA details, see Appendix Tables A3–A6.

9 City Tech follows a semester-based system and allows students to take courses during the winter and summer intersessions. 120 credits are required to graduate with an Applied Mathematics degree.

13 Students with dual Applied Mathematics and Computer Science degrees are counted in Applied Mathematics, not in Computer Science.

10 In tables A3 – A6, the “supported student” means the student had been supported by the program. The support may not be for the respective semester indicated.

APPENDIX

Table A1. The major, gender, and ethnicity of all supported students in the STEM Scholarship program 2015–2020

All supported students’ major, gender, and ethnicity
		Asian (women/men)	Black (women/men)	Hispanic (women/men)	White (women/men)	Unknown (women/men)	Subtotal (women/men)
Bachelor degree program	Applied Mathematics	4/11	1/5	4/3	2/1		11/20
	Applied Chemistry	2/1	2/0	2/4	1/0	1/0	8/5
	Biomedical Informatics	5/3	8/5	3/1	2/2	1/0	19/11
Total Bachelor		11/15	11/10	9/8	5/3	2/0	38/36
Associate degree program	Computer Science	4/6	1/1	1/3			6/10
	Chemical Technology	0/2	1/0		1/0		2/2
Total Associate		4/8	2/1	1/3	1/0		8/12
Total		15/23	13/11	10/11	6/3	2/0	46/48

Table A2. Institutional enrollment data on applied mathematics and computer science programs.

Institutional enrollment data on Applied Mathematics and Computer Science
	Applied Mathematics enrollment			Computer Science enrollment
Semester	Number of women	All students	% women	Number of women	All students	% women
Fall 2013 (Pre-grant)	23	108	21	31	292	11
Fall 2014 (Pre-grant)	22	96	23	38	326	12
Fall 2015	20	98	20	49	361	14
Spring 2016	25	109	23	42	328	13
Fall 2016	25	109	23	52	393	13
Spring 2017	32	108	30	39	336	12
Fall 2017	27	108	25	49	392	13
Spring 2018	22	91	24	44	302	15
Fall 2018	21	93	23	61	338	18
Spring 2019	22	86	26	40	256	16
Fall 2019	27	91	30	48	315	15
Spring 2020	32	93	34	35	241	15
Fall 2020	31	90	34	54	364	15

Table A3. Mean semester GPA and credits earned by applied mathematics women.¹³

Mean semester credits and GPA earned by applied mathematics women
	Supported women			Unsupported women (cumulative GPA ≥3)			Unsupported women (cumulative GPA <3)
Semester	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA
Fall 2015	4	13.75	3.75	5	13	2.9	13	7.1	1.8
Spring 2016	6	12.2	3.9	4	11.75	3.6	18	8.9	2.1
Fall 2016	6	12.7	3.8	5	9.6	2.9	18	9.3	2.5
Spring 2017	6	13.2	3.7	10	12.3	3.2	17	9.1	1.9
Fall 2017	6	13.7	3.8	9	11.6	3.4	16	8.3	2.3
Spring 2018	6	16	3.9	8	9.5	2.9	9	9.4	2.5
Fall 2018	7	14.3	3.8	11	9.3	2.7	11	7.1	2.3
Spring 2019	6	14.7	3.8	10	11.6	3.1	11	10.1	2.3
Fall 2019	6	15.3	3.9	10	11.5	3.5	15	7.9	2.2
Spring 2020	5	10.4	4.0	12	11.8	3.1	15	4.7	1.4
Weighted average		13.7	3.8		11.2	3.1		8.2	2.2

¹⁰

Table A4. Mean semester GPA and credits earned by applied mathematics men.

Mean semester credits and GPA earned by Applied Mathematics men
	Supported men			Unsupported* men (cumulative GPA ≥ 3)			Unsupported men (cumulative GPA < 3)
Semester	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA
Fall 2015	8	16.25	3.3	31	11.4	3.2	46	7.8	2.0
Spring 2016	7	14	3.4	34	11.2	3.4	42	9.3	2.1
Fall 2016	9	14.9	3.7	27	11.7	3.3	50	6.9	1.7
Spring 2017	10	14.9	3.5	34	10.9	3.2	42	9.0	2.3
Fall 2017	10	13.6	3.4	26	10.9	3.0	48	8.8	2.0
Spring 2018	9	13.6	3.6	24	11.8	3.0	39	9.2	2.3
Fall 2018	6	16.3	3.1	26	10.4	3.4	40	6.6	1.7
Spring 2019	6	13.7	3.3	24	12.2	3.3	35	8.2	2.2
Fall 2019	5	13	3.3	24	11.3	3.2	36	8.1	1.9
Spring 2020	6	14.8	3.7	29	11.2	3.4	29	8.2	2.4
Weighted average		14.5	3.4		11.3	3.2		8.2	2.1

Table A5. Mean semester GPA and credits earned by computer science women

Mean semester credits and GPA earned by Computer Science women
	Supported women			Unsupported women (cumulative GPA ≥ 3)			Unsupported women (cumulative GPA < 3)
Semester	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA
Fall 2015	0			19	11.4	3.3	29	8.6	1.7
Spring 2016	1	7	4.0	12	10.75	3.3	30	7.6	1.5
Fall 2016	3	13.7	3.6	22	10.4	3.3	35	8.8	1.9
Spring 2017	3	13	3.1	17	11.4	3.1	22	8.9	2.4
Fall 2017	6	12.5	3.4	16	9.9	3.3	31	9.9	2.0
Spring 2018	6	12	3.1	19	12	3.4	19	11	2.3
Fall 2018	5	10.8	3.0	25	12.0	3.5	33	7.7	2.0
Spring 2019	4	11.5	3.1	14	13.1	3.5	28	7.4	1.7
Fall 2019	1	8	4.0	15	12.5	3.3	37	8.4	1.9
Spring 2020	1	3	3.7	19	14	3.4	22	6.3	1.6
Weighted average		11.5	3.3		11.75	3.4		8.4	1.9

Table A6. Mean semester GPA and credits earned by computer science men

Mean semester credits and GPA earned by Computer Science men
	Supported men			Unsupported men (cumulative GPA ≥ 3)			Unsupported men (cumulative GPA < 3)
Semester	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA	N	Mean credits	Mean GPA
Fall 2015	8	14.4	3.7	89	11.3	3.4	228	7.7	1.7
Spring 2016	7	14.9	3.6	82	11.6	3.3	203	8.0	1.9
Fall 2016	4	11.5	3.4	97	11.3	3.3	236	7.8	1.7
Spring 2017	4	12.25	3.5	82	10.8	3.3	210	8.0	1.9
Fall 2017	6	14.2	3.6	106	12.0	3.4	227	8.0	1.7
Spring 2018	5	14.6	3.8	86	11.0	3.3	176	7.7	1.7
Fall 2018	5	15.8	3.7	87	11.1	3.1	185	7.4	1.7
Spring 2019	7	15.1	3.3	70	10.4	3.1	140	7.6	1.8
Fall 2019	2	14	3.5	82	11.4	3.2	184	7.4	1.8
Spring 2020	1	15	3.7	74	11.8	3.2	131	6.7	1.8
Weighted average		14.3	3.6		11.3	3.3		7.7	1.8