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KALAMAZOO, Mich.—"AI is unlikely to replace you any time soon, but those people who know AI will.” This is an adage used by Dr. Kuanchin (KC) Chen, �鶹��ý professor of computer information systems and a 30-year veteran of researching and teaching artificial intelligence.

Being on the leading edge of effectively using AI in a variety of contexts is the goal of Chen and his colleagues as they embark on a pilot project for teaching business �鶹��ýs how to use AI to successfully research job �鶹��ý and prepare for interviews.

While Chen was searching for ways to bring AI to the Haworth College of Business in broader ways, he came across �鶹��ýs who needed to improve their interview skills.

“We have many talented �鶹��ýs,” he says. “However, many of them still follow the traditional way to sharpen their interview skills, testing out their interview technique with the first few companies until their skills mature. This process is slow and not effective. We see �鶹��ýs repeat a very time-intensive process to improve their interview skills.”

AI has a lot of potential in career readiness, according to Chen, who heads the Center for Business Analytics, and his collaborators from the college’s Communication Center and Zhang Career Center agree.

“Text summarization, feature exaction, natural language processing, and even topic modeling are among useful AI techniques,” he says. “I contacted the director at the Communication Center, Beth Ernst, regarding potential ideas, and she enthusiastically referred me to Tim Buchanan and Marie Moreno, experts in communication and generative AI from the center.”

The team then approached Geralyn Heystek, director of the Zhang Career Center, and her team to exchange thoughts, learn about the current practice in career development circles, and brainstorm possible directions for the project. The collaboration took off from there—with an AI-like speed that firmly places WMU Haworth at the forefront of educational institutions using the technology to get �鶹��ýs interview-ready. The expertise contributed by the three centers is indispensable to the success of the project, because the combination of communication skills, career strategies, technology savviness and research guidance provide the foundation for its success.

“AI will be used to effectively prepare �鶹��ýs for interviews. Instead of playing catch-up, we decided to lean into it and become a resource for the entire campus community on how to do it well,” say Chen.

�鶹��ý the project

The AI interview training pilot serves three goals. First, it empowers �鶹��ýs to craft comprehensive responses to interview questions with generative AI. Second, �鶹��ýs receive assistance from the college’s Center for Business Analytics, Communication Center and Zhang Career Center with developing well-rounded responses to potential interview questions. Third, rooted in the behavior literature, the pilot assesses how self-efficacy in job interviews and the use of AI for that purpose are cultivated through the �鶹��ýs' experience, resource availability, and intended job roles. The project has highly practical applications for �鶹��ýs but also builds theoretical contributions that advance the understanding of symbiotic relationships with AI.

Students participating in the pilot will work with Buchanan on the following:

• Send job postings which they intend to apply to
• Reserve an appointment at the WMU Haworth Communication Center
• Receive preparatory training on generative AI, if the �鶹��ý is not familiar with it
• Analyze the job requirements with a Communication Center consultant and generative AI, identifying areas the �鶹��ý needs the most help with
• Create potential job interview questions, especially addressing the �鶹��ý’s weak areas, using generative AI
• Create preliminary responses to those questions with generative AI
• Analyze generative AI’s feedback with the human consultant
• Identify areas of improvement and areas of creative response, looking at content accuracy and presentation strategies
• Refine responses reviewed by both the human consultant and generative AI
• Respond to a survey in order to assess satisfaction, forms of self-efficacy and other psychological factors

The multi-phase project begins with helping �鶹��ýs deliver the right substance in interviews, with future phases addressing questions regarding how to enhance problem-solving, data analytics and other skills �鶹��ýs can demonstrate. Ultimately the project should help participants extend their AI expertise in the interview contexts to other similar problems in a work setting.

“We are interested in assessments directly after the training and after the �鶹��ýs have a chance to apply what they have learned at real job interviews,” says Chen. “The method is rooted in theories that focus on assessing current interview skills with AI, the ability to carry those skills into the future, and the competence to apply AI skills at the anticipated position. This granularity of skill assessment is useful for lifelong learning, especially when technology evolves nearly every day. The team thanks Dean Satish Deshpande for the support and the freedom to embark on new AI initiatives at the college.”

Many business �鶹��ýs who are now applying for jobs faced challenges while beginning their college careers during the pandemic, adds Moreno.

“These soon-to-be graduates have more anxiety about interviewing than previous groups of �鶹��ýs,” says Moreno “This project is a response to those increased �鶹��ý concerns and also imparts value-added skills that �鶹��ýs can take with them into the workplace.”

Once the process has been piloted at WMU Haworth, the team plans to roll the training out to all �鶹��ýs at Western.

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