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Utterback enjoys filling the ‘toolbox’ for students

Barry McNamara
MONMOUTH, Ill. – Computer scientists are rarely described as being “multilingual,” but first-year mathematics and computer science professor Robert Utterback said that Monmouth College students in his discipline learn “at least three” programming languages during the first half of their undergraduate careers. They finish knowing as many as six.

“Our goal is to teach them the underlying fundamentals of programming languages,” said Utterback.

He said that all Monmouth students typically learn Java and C++ before branching out in various directions, depending on the classes they take.

“If they know the underlying fundamentals, they should be able to pick up Y, knowing what they do about X,” he said.

That type of instruction is part of what Utterback calls “making sure the students get a useful toolbox full of tools.”

“I want them to be able to apply those tools to real-life situations,” he said. “It’s important that they know when to use each of those tools at the right time – when is each language or programming paradigm the best one to use.”

Growing up in St. Clair, Mo., Utterback borrowed “tools” from both his parents. Utterback would “mess around” with computers on his visits to a computer store his father ran, eventually getting involved with them at home, as well. His mother taught elementary school. So from an early age, teaching computer science was Utterback’s goal, although he also enjoyed mathematics and contemplated that teaching path, as well.

Monmouth is Utterback’s first full-time position since he earned a doctorate from Washington University in St. Louis. He earned an undergraduate degree from Truman State University in Kirksville, Mo., where he met his wife, Audrey.

As Utterback’s interest in computer science grew, he became particularly interested in parallel computing, which involves a computer doing multiple tasks “at exactly the same time.” Put another way, many calculations or the execution of processes are carried out concurrently. Large problems can often be divided into smaller ones, which can then be solved at the same time. An example is scientists working on climate simulations.

“It’s really hard to program those computers and get good performance,” said Utterback. “If you do the parallel computing right, you can run the simulations a lot faster.”

Utterback said he’s happy to start his career at Monmouth, where “the focus is really on teaching.”

“It’s a nice place,” he said. “My hometown was small – around 4,000 people – so I’m used to smaller towns, and I also like working at a smaller college. Also, my wife grew up in Galesburg, so it’s really convenient that we were able to move so close to her family.”