Article written by Natasha Shea, P-Tech & Robolliance Expert
Every day we hear about “jobs that don’t exist yet.” We also know that as industry leaders we’re in the throes of developing innovative technologies that are key to security industry success. Just as the engineers who designed the robot needed to think differently, so will the end-users and operators of the technology. To get ahead of the learning curve and accelerate both development and implementation of robotics in the future, education programs are preparing students today.
At Hudson Valley P-TECH, we teach high school courses, and offer students college and career training through a degree program and industry mentoring as they prepare for the workplace of the 21st century. As educators we are responsible for training students for jobs that don’t yet exist. In order to do this, we turn to industry professionals to help us identify skills—academic and professional—that could translate to almost any job market in the STEM field of study. In conversations with industry professional in STEM related careers, I am finding that providing opportunities for students to emulate actual challenges in the workplace will better prepare students for these types of expectations later on.
How does a school do that? Project based learning, a pillar of Hudson Valley P-TECH, requires students to work collaboratively. This translates into thinking out loud, innovating, and communicating on any number of STEM projects. Teams of students work together to problem solve, create efficiencies, and suggest viable innovative approaches using research methods. Units of study focus not only on the content areas of math, science, social studies and English, but also on STEM and industry specific skills.
I wanted to create an environment at Hudson Valley P-TECH that allows students to experiment, build, and refine in a “makerspace” environment. For example, students are able to experiment with robotics equipment, bringing coding and math concepts learned in the classroom to real life. At its simplest form, students learn that precision in coding and math functions determines whether or not you are able to successfully move a robot.
On a larger scale, students learn the value of planning, revising, persistence, research, and collaboration to get the job done. This trial and error leads to mastery, with students teaching other students about what they did to make their project work.