How Universities Are Preparing Generation Z for a Data-Driven Workforce

From video game designers to structural engineers, learn how interpreting data and drawing insights will be a fundamental skill for tomorrow's workforce.

By Anne Miller, Contributor

Local politicians point to the $3.98 billion project to replace New York’s iconic Tappan Zee Bridge as a marvel of modern engineering—3.1 miles long, supported by 4,900 miles of steel strands—but the real technological advancement might be the hundreds of sensors throughout the project that will measure things like traffic conditions and weather.

When John Kolb, vice president for information services and technology and chief information officer at Rensselaer Polytechnic Institute (RPI) in Troy, New York, sees the bridge, he sees the future of the undergraduates he works with.

“You’re getting all this data from the bridge,” he said. “What are you going to do with it? If you don’t have any dexterity to sift through all that data, you’re just…collecting data.”

Like the new bridge, the world is increasingly a cacophony of data. It’s easy to drown in it unless you know how to sort, shuffle, and interpret the data into something meaningful—and useful. That’s where the students come in.

Rethinking the University Mindset

In the fall of 2018, every RPI undergraduate will have to meet a data dexterity requirement by taking two data-intensive classes in order to graduate. In some cases, these are new classes. The university is also tweaking other existing courses to include data aspects to meet the intensive part of the requirement.

According to the university’s administrators, it’s the first American college to implement such requirements in higher education.

“We chose the term ‘data dexterity’ because we really want our students to be quite competent—experts in working with the data—and we think that cuts across all disciplines,” Kolb said.

These data organization and IoT-minded skills are becoming more in demand in the workforce, and recent surveys show that graduates adept at working with micro-data points will have an advantage in the modern workforce.

According to a PwC and Business-Higher Education Forum joint report released in 2017, nearly a quarter of educators say all graduates will have data science and analytics skills by 2021. Meanwhile, 69 percent of employers surveyed said they favor candidates with data skills over those without.

“In 2015, there were more job postings asking for [data science and analytics] DSA skills than the total number of postings combined that asked for registered nurses and truck drivers, two of the largest hiring occupations in the U.S.,” the report found.

In other words, data skills are in high demand.

Navigating the Data-Driven Campus

Despite the push toward more data-centric classes in universities, institutes of higher learning still struggle with what and how to teach, as well as how much and to whom.

Frameworks are starting to emerge, so universities and high schools can get on the same page, but that’s still not enough to meet the anticipated 2.7 million jobs that will involve data science in 2020, the PwC survey notes. The desire is not just for more numbers folks, but for versatile brains that can apply data to across disciplines.

“We want them to not only have the tech and analytics skills, but also the social skills,” Kolb said, of his school’s program. “So, you’ve seen something in the data that’s interesting – how do you tease that out, how do you collaborate as a team to move something forward?”

It’s not just employers or professors who desire to nurture these skills. The students themselves—the first wave of truly digital native high school graduates—are also pushing for access to this type of learning.

“We want [students] to not only have the tech and analytics skills, but also the social skills.”

— John Kolb, Chief Information Officer, Rensselaer Polytechnic Institute

At the University of California Berkeley, a flood of students entering basic data classes forced the school to reconsider what type of courses the renowned university should offer—and how data analysis might be taught.

In 2015, the school debuted a pilot program with 150 students, and four classes, for freshmen in data science. That pilot has grown to include more than 2,500 students. In February of this year, the university said its Foundations of Data class is the fastest growing in university history, limited only by space and the number of teachers available. The students represent 70 different majors.

“Our students have seen in their lives how data is transforming the world,” said Cathryn Carson, the faculty lead for the school’s Data Science Education Program. She added, “in the San Francisco Bay area, especially, there’s no question that computing and data science can open doors.”

Berkeley’s data class isn’t a requirement. But the school purposefully decided not to require any prerequisites for students who want to take it, to encourage cross-discipline participation.

“We see data science becoming a fundamental part of many students’ college experience,” Carson said. “With so many jobs in the future likely to call on skills of analyzing and interpreting data, data science provides strong habits of thought, great flexibility, and preparation for many careers.

Carson and Kolb might run departments on opposite sides of the country, but philosophically, they seem to agree that the future of work, and of higher education, involves understanding data usage—no matter what the profession.

“I don’t think there are very many areas of research where there’s not an abundance of data right now,” Kolb said. “If you don’t have some capabilities in this area, I think you’re not going to be very successful.”

For Kolb, while it is important to help students develop data-driven skills that will apply to physical projects, such as the information generated from the Tappen Zee Bridge project, they also need to cultivate data skills in the softer sciences. Take video game design, for example, which RPI offers as a major. Students might need to manipulate files to create realistic terrain, Kolb said.

“With so many jobs in the future likely to call on skills of analyzing and interpreting data, data science provides strong habits of thought, great flexibility, and preparation for many careers.

—Cathryn Carson, Data Science Education Program, University of Berkeley

A New Norm

Today’s college student has grown up on Facebook and other social channels, generating massive amounts of data. It’s Kolb’s hope that in addition to being purveyors of data, Generation Z will also be the ones to interpret and find applications for it.

“We hope those students are going to be leaders in their fields, leaders for whatever enterprises they work for. Whether it’s professional or personal, the ability to make this a normal course of dealing with the world is really important,” Kolb said.

“There’s a lot of information out there to sort through,” he summed up, “and we want our students to be leaders in doing that.”