Bridging the Gaps in Career Readiness
Working with Watt AI is preparing students for their careers in more ways than one. Clemson’s Center for Career and Professional Development is using AI technology to look at the differences between students’ perceptions of their own career readiness and what prospective employers are saying.
Clemson’s career center has identified nine core competencies that students need to develop to succeed in the workplace — communication, collaboration, leadership, adaptability, analytical skills, technology, integrity and ethics, self-awareness and brand.
“When you look at how an employer ranks those competencies and then when you look at how a student ranks those competencies, there’s a gap,” says Troy Nunamaker M ’00, M ’03, Ph.D.’20, chief solutions officer for the career center. “Students often think they perform higher in those competencies than employers think they do.”
The idea to use AI to identify and quantify this gap started with Nunamaker’s dissertation when he was earning his Ph.D. in higher education administration. He manually analyzed surveys from students who had completed internships and their internship employers to look for differences in each group’s responses to core competency questions. He wanted to dig deeper but had neither the time nor the personnel to comb through more surveys, so he turned to Watt AI for help. Now, he can analyze thousands of surveys per semester.
The first year of the project was focused on leadership, looking at the ways student interns responded about their own leadership skills versus the way their employers did. The AI was taught to look for certain words that described leadership as either transactional — focused on rewards and consequences — or transformational leadership through encouragement and empowerment. The AI found that students tended to describe their own leadership as strictly in one style or another, whereas employers tended to want more of a blended approach.
Nunamaker says he hopes the results will allow the career center to better coach students on the job application process, as well as understand how these core competencies are taught and how that can be improved. The project has been recognized with an award from the Cooperative Education and Internship Association for distinguished excellence in the field.
For Daniel Smith ’20, his work on the project helped him land his job as a software engineer for NCR Corporation in Atlanta. He worked on the project as a student, implementing the AI model and labeling the data so it would know what keywords to search for.
“This project was where I learned the most about AI and machine learning. I learned the fundamentals in the classroom, but this was where I got my hands dirty in AI,” Smith says.
Smith connected with NCR at a hack-a-thon event at Georgia Tech, which he entered using the same kind of machine-learning tool that he used in his Creative Inquiry project. He didn’t win, but he caught the attention of an NCR recruiter, which led to a job interview and an eventual job offer.