Collaborating with Undergraduate Programs

What Do Undergraduates Really Know?

If you are reading this, you probably completed an undergraduate degree in something, at some point (this was longer ago for some than it was for others). Looking back, you likely recall at least three things about your undergraduate experience: you did not really get into your “major” until your junior (3rd) year, you did not know as much as you think you did (the hubris of youth), and students who took the time to get an internship or engage in a co-op were more likely to get a good job.

These three points are interconnected.

Let’s start by addressing why you likely took classes in the first two years in subjects that you may or may not have sought out.

Almost 95% of all U.S. colleges and universities use an academic calendar with two primary 15-week semesters - Fall and Spring - with an 8-week summer semester¹. Most undergraduate programs have a stated requirement of approximately 120-130 credit hours of study to earn a bachelor’s degree² which equates to approximately 40 courses (most undergraduate courses are 3 credit hours). Credit hour requirements for a few common majors can be found in Figure 3-1.

The average number of credit hours actually earned by undergraduate students is closer to 135- In fact, only about 40% of students enrolled in a four-year college program graduate in four years³ (make a note of this for when your child starts college). There are several reasons for the extra time/credit hours, including changing school, changing major, failed classes, and, of course the catchall category of “life events”.

Figure 3.1 Average required credit hours for selected undergraduate major in the United States (2018).

Across all undergraduate degrees offered through universities and colleges in the United States, there are roughly three categories of courses: general education, major required courses, and electives. See Figure 3-2.

So, what exactly happens in each of those three sections and, as an analytics professional trying to engage with a university, why should you care?

Tlie bulk of most undergraduate degrees in the United States stems from a strong emphasis on liberal arts foundations. Historically, the goal of the liberal arts education was to provide a general framework of knowledge, exposure to a breadth of subjects to promote critical thinking, and to be a bridge to higher level curricu- lums in applied fields of study. However, the number of strictly “liberal arts” colleges in the United States has declined precipitously with an associated rise in more technical colleges'¹. Despite this drop in entire curriculums being liberal arts based,

Figure 3.2 Typical distribution of undergraduate credit hours in the United States.

most bachelor’s degree programs have some number of credits required in general education which are typically split among humanities, social sciences, mathematics, writing, the arts, history, and physical, environmental, chemical, and/or biological sciences. While the total number of credits vary by institution, it is usually about one third of all required credit hours (see Figure 3-1)- Beyond that, students have requirements for their majors, which often reflect some notion of required competency needed as directed by the field’s accrediting body. For example, a nurse would need so many instructional hours and clinical hours across directed subjects and still need to pass a competency exam to gain a practice license at the level of Registered Nurse (RN). Similarly, an engineering student in an accredited program must take two or three semesters of general education, followed by two semesters of mathematics and science and at least three semesters of instruction in engineering courses — and then pass two competency exams to apply for licensure as a practicing engineer. Other fields have similar requirements (e.g., education, accounting). After general education and major course work, any remaining credit hours are “electives” - courses open to student choice.

It is worth noting that there is no standardized curriculum - or governing body - for data science.

The key message here is that whether a student is studying nursing, engineering, or data science, the material is still relatively “high level” and theoretical. General education courses are effectively introductory survey courses. This means that higher level learning opportunities are limited at the bachelor’s level - by design. What is emphasized is the critical thinking involved and hopefully holistic view of how subjects, theories, and phenomena intersect into higher level models of inquiry. In other words, at the undergraduate level, students are really “learning how to learn”.

In the last year of study, undergraduate students increasingly participate in some type of internship or capstone experience (when they make us the benevolent dictators of education, we would require that all students graduating from an accredited university in the 21st century would have an internship or capstone experience... but we digress...). Capstone courses and internships have been identified as “high- impact” educational practices - those practices having the greatest contribution to a successful undergraduate experience (i.e., degree completion, employment in field of choice). The American Association of Colleges and Universities identified High- Impact Educational Practices’ as:

■ Common Intellectual Experiences

■ Learning Communities

■ Writing-Intensive Courses

■ Collaborative Assignments and Projects

■ Undergraduate Research

■ Diversity/Global Learning

■ Service Learning

■ Community-Based Learning

■ Capstone Courses

■ Internships

These practices - which again are increasingly integrated into undergraduate programs across the United States - are high impact because they require students to do (at least) four things:

■ High-impact practices demand that students devote considerable time and effort to purposeful tasks and require regular decisions that deepen their involvement as well as their commitment to their academic program and to their college.

■ They help students build substantive relationships by requiring them to interact with faculty and peers about complex, integrated matters over extended periods of time. As professors with almost 50 collective years of teaching experience (Bob is older), it continues to amaze us how few students actually interact with faculty outside the classroom. We don’t bite — at least not hard.

■ They challenge students to work with students from other disciplines and other backgrounds and contribute to new ways of thinking about and responding to novel circumstances as they work on intellectual and practical tasks, inside and outside the classroom, on and off campus. From your own experience, consider how many times - particularly in the later years of your program — you worked with students who were majoring in a discipline different from your own. Historically, students were rarely provided the opportunity to collaborate with students or faculty outside of their discipline. However, today most work is done in collaborative teams comprised of people with different skills and typically different types of formalized training. This is particularly true and relevant for data science, where almost all work is done in teams of specialists.

■ They help students apply and test what they are learning in new situations. High-impact practices provide opportunities for students to see how what they are learning works in different settings and create contexts to integrate, synthesize, and apply knowledge.

Long-standing, well-established undergraduate programs of study have had to retro-actively integrate high-impact practices into their curricula. However, the first generation of undergraduate programs in data science have been able to integrate these high-impact practices into their curricula from the beginning. As an analytics manager looking for opportunities to work with an undergraduate population, understand that capstone courses, internships, and applied project opportunities are the “ultimate” examples of high impact educational experiences.

While an applied data project is an effective way for you and your organization to evaluate and recruit students for positions, note that these types of engagements make an important contribution to the students’ educational experience. In addition, faculty within these undergraduate programs are likely regularly on the lookout for corporate partners to help develop and structure these projects — so you are also helping to “lighten the load” for a lecturer or assistant professor who may be scrambling to meet their course requirements.