Shortly after graduating from Rhode Island School of Design (RISD), I received an alumni email from RISD about its former President John Maeda’s initiative to integrate arts into STEM (science, technology, engineering, and mathematics) education, calling it STEAM. As a designer in love with math and science, this email touched me on an emotional level.
(For New York Times coverage on John Maeda and RISD’s initiative, see here.)
Supporters of STEAM argue that creativity and problem-solving skills are intricately tied to success in STEM education. Although I do agree with this point of view, this argument can be somewhat arbitrary. For one, we don’t fully understand what creativity means, and even if we did, we know it is not necessarily equivalent to learning how to draw. With a number of years working in both fields, I would like to share my personal opinion on how learning art might benefit one’s practice in data science.
I always loved both science and the arts, but I constantly had to choose between the two. It was as difficult a question as choosing between mom and dad (quite literally because my mom was a designer, and my dad an engineer). In my childhood, I spent many hours building a line-tracer robot and teaching myself to code, while also filling up books with character sketches. If someone asked me what I wanted to be when I grew up, I always struggled to choose either an artist or a scientist.
#psychology #art #education #stem #data-science #data analysis
Developing spatial ability to enhance performance in STEM. I always loved both science and the arts, but I constantly had to choose between the two.