By Geoffrey Draper, and Aaron M. Curtis, Brigham Young University–Hawaii
Data Visualization as
a Proving Ground for
We present a course that introduces undergraduate students to the concepts of graduate school, using data
visualization as the topic of study. Students read seminal
papers in the field of data visualization and implement
many of its core algorithms. By the end of the course,
students who may not have otherwise considered graduate
studies as an option can make an informed decision about
whether to attend graduate school or join the workforce
The benefits of a diverse faculty are well recognized [ 18].
However, achieving this diversity requires a robust pipeline of
non-traditional students and underrepresented ethnic groups
[ 22] both attending graduate school and pursuing careers in
academia. Undergraduate research is one vehicle for motivating
students towards academic careers. Unfortunately, the number
of undergraduate research positions is often limited both by
funding and by faculty time constraints.
To address this concern, we present an undergraduate course
that gives students an exposure to many of the basic concepts of
graduate school, without necessarily requiring the faculty time
commitment of one-on-one mentored research. Our course is
patterned after the idea of a seminar or colloquium course typically taken during a student’s first year of graduate studies. The
topic of the course is data visualization, since that is a research
area with which we are familiar—although in principle any advanced topic would suffice. Enrollment is limited to juniors and
seniors majoring in Computer Science. In this course, we introduce students to many of the concepts and activities they will
encounter in graduate school—such as reading academic papers,
implementing previous work, proposing new projects, making
presentations, and writing research reports. We tell our students
that by the end of the course, they will say one of three things.
( 1) I want to attend graduate school and study data
visualization. I am already familiar with the key papers,
people, and techniques in the field, and am ready to hit the
( 2) I want to attend graduate school, but do not want to study
data visualization. I enjoyed the experience of reading
academic papers and making presentations to my peers;
however, my research interests lie elsewhere.
( 3) I now know that I do not want to attend graduate school. I
just want to find a job and start making money!
Although we’d be thrilled if every student echoed sentiment
#1, but one of these results is, to us, a successful outcome of
the course. The students will have gained important research
and critical thinking skills, which are of value in both industry and academia. Those who do go into graduate school will
“know what they’re getting into,” and those who decide against
graduate school will have made an informed decision, based on
their own interests and career goals. It is far better for them to
find out they don’t like research before starting graduate school,
rather than halfway through!
Topic-based seminars [ 1, 19] and undergraduate courses in
data visualization [ 3, 13] are not new. However, to our knowledge, ours is the only one that combines the two: using data
visualization to introduce undergraduates to the rigors of grad-uate-level study.
This course began in 2013 as an attempt to boost awareness of
graduate studies among our juniors and seniors, many of whom