Helping Faculty Prepare Students for the Workforce

By Kathleen Kavanagh, Joe Skufca, Ben Galluzzo, and Karen Bliss

Motivated by national initiatives to improve the role of science, technology, engineering, and mathematics (STEM) educators in workforce preparation from K-12 through college, the SIAM Education Committee is focusing on methods to help teachers and faculty better equip their students. A session organized by the committee at the 2020 Joint Mathematics Meetings, which took place this January in Denver, Colo., reflected this focus area. The speakers included Karen Bliss of Virginia Military Institute (VMI) and Ben Galluzzo and Joe Skufca, both of Clarkson University. An industry panel following the talks generated discussion on employer requirements when hiring mathematicians.

In addition to a solid foundation of core mathematics, statistics, and problem-solving abilities, industrial positions also require skills like data literacy, computing, mathematical modeling, interdisciplinary team collaboration, and effective communication. Integrating these skills into new or existing curricula raises challenges for faculty members who may not be experienced in certain areas. For example, while machine learning courses have not historically been part of most undergraduate- or graduate-level coursework, academic departments are now recognizing that a machine learning background increases their students’ marketability.

Computing lies at the heart of every future path across all global cultures, including complex societal problems, manufacturing and financial innovation, and even consumer trends. To ensure that high school students are prepared for this future, instructors must be creative and resourceful. To that end, Galluzzo described a National Science Foundation venture that centers on computational literacy using math modeling and R programming in high school courses. The Computing with R for Mathematical Modeling (CodeR4Math) project leverages inherent connections between computational thinking, mathematical modeling practices, and a multitude of representational tools. This combination creates a synergistic solution that allows students to simultaneously develop competencies in both domains. The project is currently generating a collection of facilitated math modeling activities that provide students with “just in time” coding help.

Bliss detailed the evolution of a differential equations (DEs) course as part of the transition from a mathematics major to an applied mathematics major  at VMI. At the outset, she and her colleagues met with faculty from departments served by the DEs course—like engineering, physics, and chemistry—to determine what they wanted students to gain from the course. This discussion allowed them to pare down the existing pencil-and-paper solution techniques and redirect the course’s focus to modeling, specifically the employment of DE utilization to answer questions in different disciplines. Students in Bliss’s class explore population models, models of disease spread, and the use of blast attenuating seats (represented by a spring-mass system) in military vehicles to decrease traumatic brain injury. By emphasizing the translation of mathematical models to real-world scenarios, utilizing appropriate technology to obtain solutions, and communicating results via succinct reports, students learn to work in interdisciplinary teams and leverage their math skills to solve important problems.

Skufca overviewed Clarkson’s efforts to address emerging workforce needs, as framed in the context of a small, resource-challenged university. Clarkson developed a professional master’s degree in data analytics, which is available as an interdisciplinary program across all of the university’s departments. Three years after establishing the master’s program, Clarkson’s Department of Mathematics began offering an undergraduate degree in data science. The flexibility associated with a small university helped achieve both initiatives, which were inspired by industry need.

Skufca then explained how careful curriculum mapping—combined with strong cooperation across disciplines—allowed Clarkson to build these programs without adding many supplementary resources. The directors of both new programs first look to industry to identify relevant skills, then turn to internal academic expertise to determine the fundamental pedagogy that supports, enables, and broadens that specific skillset. A unique component of the data science curriculum is a three-credit “math” course (taught by a mathematics professor) on the ethics of data science and applied mathematics; this is especially pertinent as the interplay of math, industry, and government requires awareness of professional mathematics’ impact on society.

Genetha Gray of Salesforce, Carol Woodward of Lawrence Livermore National Laboratory, Pat Quillen of MathWorks, and Aaron Luttman of Pacific Northwest National Laboratory comprised the industry panel that followed the initial presentations. Each panelist began by recounting employers’ requirements for hiring mathematicians. Recommended skills included deep knowledge in a specific subject, a background in some realm of science, programming experience with expertise in a compiling language, familiarity with numerical methods, and problem-solving abilities. However, a common theme among all panelists was strong communication proficiency — the ability to explain ideas at a high level to experts while also communicating effectively with non-experts.

The audience was interested in types of required writing skills, and inquired about methods that they could use to train students accordingly. Quillen noted that helping students learn succinctness—in an email or storytelling, for example—is crucial. Woodward emphasized the importance of efficiently translating logical arguments into writing while keeping one’s audience in mind. One attendee sought advice on building connections with industry associates, identifying and contacting the right partners, and maximizing the likelihood of response. Gray suggested reaching out to public relations personnel since they are often able to best connect individuals with suitable internal contacts. Most importantly, she recommended underscoring the benefits for companies in forming relationships with academia.

Finally, Luttman urged attendees to utilize SIAM resources, and encouraged faculty to take advantage of programs like PIC Math and the Visiting Lecturer Program to help students establish early industry partnerships.

Kathleen Kavanagh is a professor of mathematics at Clarkson University and the Vice President for Education at SIAM. Joe Skufca is a professor of mathematics and chair of the Department of Mathematics at Clarkson. Benjamin Galluzzo is an associate professor of mathematics at Clarkson. Karen Bliss is an associate professor in the Department of Applied Mathematics at Virginia Military Institute.