Faculty: Dr. Shawn Bergman

Team Leads: Jamie Da Costa and Ella Drawbridge

Description: The Foundations of Career Understanding in Psychology Students (FOCUS) team creates practical, research‑driven solutions to support psychology students at App State. Our work focuses on helping students understand their employable skills, identify career pathways, and reduce the risk of underemployment after graduation. We do this by combining psychology, data analysis, and emerging technologies like Artificial Intelligence.

Project 1:

The FOCUS team is expanding an ongoing project that evaluates the knowledge, skills, and abilities (KSAs) students gain throughout the psychology major. Previously, psychology faculty rated the level of KSAs an average student should develop in each of their courses. These ratings were uploaded into Eugene, a career‑exploration website where students can select courses and view the KSAs they build and the jobs they may qualify for. Our current work incorporates AI‑generated KSA ratings. We compare these AI‑generated ratings to faculty ratings to determine accuracy and consistency. In the future, professors may be able to upload their syllabi directly to an AI tool that automatically identifies KSA levels - streamlining the process and reducing manual workload. This innovation may eventually allow us to expand Eugene’s reach to majors and minors outside psychology.

Project 2:

Feedback from the Student Satisfaction Survey revealed that some users found the Eugene website confusing. In response, the FOCUS team launched two initiatives:

Chatbot Implementation:  

We developed a student‑friendly chatbot designed to answer questions, reduce confusion, and guide users through Eugene’s tools. The chatbot is currently in its final testing phase and will soon be integrated into the Eugene platform.

Website Redesign:  

Based on student feedback, the Eugene website is undergoing a redesign to improve navigation, clarity, and overall user experience. This project is still in the early design stages, with updates planned for future development cycles.

Additional focus:

• The Marketing Committee works to increase awareness of the tools and resources available through FOCUS, including:

  • Eugene Website

  • Psychology Career Advising

  • Applying to Get a Job (PSY 4019)

Faculty: Dr. Jess Doll and Dr. Tim Huelsman

Team Lead: Brody Behm

Description: The Organizational Culture Insights Team explores how values, behaviors, and structures shape group dynamics in real-world organizations. This team focuses its research projects on employees' well-being, culture, and workplace experiences. We conduct research that brings insights into organizations and the people in them. We collaborate on meaningful research, gain hands-on experience, and contribute to a deeper understanding of workplace culture. Our team has presented 7 posters over the past two years at many different conferences, and we strive to publish meaningful work to further science.

Project 1: Social Stories in Business Case Studies

This project looks to examine the impact of social stories in management case studies on neurodivergent individuals. This research will measure engagement and learning as it relates to the impact of the integration of social stories in case studies.

Project 2: Career Websites: Job Seekers Intentions and Perceptions

The research aims to evaluate whether job seekers are visiting career websites to glean information and insights about an organization’s values. If they do, are the job seekers' perception realistic to the organizational values?

Faculty: Dr. Shawn Bergman and Dr. Timothy Ludwig

Team Lead: Ethan Fountain

On the Safety team, students work together using statistical tools to uncover meaning from data. We focus on identifying what commonly happens leading up to an incident, then report that information to keep employees safer. 

Previously, our research has been focused on Behavioral Observations which are on-scene reports Safety managers use to identify and reduce hazards. We wanted a way to assess the quality of those Observational Reports by analyzing the open text with AI.

Last year, our team used Python and ChatGPT to rate open-ended comments on 10 quality factors. Regression analysis found that three of these factors predicted incidents in the expected direction. This year, we plan to replicate our findings while deepening our understanding of what quality factors actually lead to more lives saved.