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This project focuses on developing three technical courses for lower-division electrical engineering education to bridge the gap between Career and Technical Education (CTE) programs in high schools, engineering programs at community colleges, and lower-division electrical engineering courses at four-year universities. The primary goal of the project is to create a seamless academic transition by providing electrical engineering students with the necessary foundational knowledge in analog and digital systems, as well as hands-on experience with laboratory measurement tools. The courses utilize industry-relevant technologies such as LabView, MATLAB, PLC programming, and ready-to-use microcontroller boards to facilitate experiential learning at lower division courses. Early exposure to these tools and systems equips students with practical skills that not only prepare them for further academic pursuits but also align them with workforce demands in industries that increasingly rely on automation, data acquisition, and real-time system controls. The success of this project is attributed to its emphasis on design and project-based learning, which fosters critical thinking and problem-solving skills essential for real-world applications. By integrating design principles early in students' educational experiences, they are better prepared to tackle complex engineering problems as they progress through their academic careers. The use of project-based learning allows students to apply theoretical knowledge to tangible, real-world projects, improving their engagement and deepening their understanding of electrical engineering concepts. Practical tools like MATLAB and microcontroller boards in entry-level courses not only motivates students to pursue engineering but also increases retention rates in STEM fields, a key metric for academic success. This project is also advocating for early exposure to hands-on technical skills as a way to better prepare students for the workforce. By focusing on skill development in both CTE programs and early college courses, students are equipped with a stronger foundation for electrical engineering careers and are more likely to succeed in upper-division coursework and beyond. The seamless integration of high school, community college, and university programs ensures that students acquire both the theoretical and practical skills necessary to be successful in an increasingly technology-driven economy. Moreover, the project's use of industry-standard tools, coupled with its focus on bridging academic gaps, provides a sustainable model for developing a skilled and versatile workforce, addressing the growing need for engineers proficient in both design and system implementation.
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This content will become publicly available on June 22, 2026
Work-in-Progress: Uncovering AI Adoption Trends Among University Engineering Students for Learning and Career Preparedness
Work-in-Progress: Uncovering AI Adoption Trends Among University Engineering Students for Learning and Career Preparedness-progress study explores self-reported data on AI use by university engineering students. The purpose of this study is to investigate how students are utilizing AI technologies and to understand their views on the role of AI in their future. The primary research question formulated was: How does the adoption of AI technologies for learning vary across demographic groups among university engineering students? Advances in technology and the emergence of AI tools have attracted attention from academia, research, and industry. The rapid growth of deep learning technologies has changed the landscape in the work environment, and universities may need to adapt to keep pace. Dynamic changes in the workplace have accelerated as these AI technologies are being leveraged to complete tasks at a high-speed rate. Research indicates that the workforce is increasingly demanding higher skill levels, including specialized AI skills. Formal education in AI basics could be crucial for future career readiness. Over 150 engineering students reported their demographics, including age, race, gender, year in school, and if they identify as having any form of disability. Currently, the survey remains open. The final study will incorporate more responses, and additional data will come from semi-structured interviews. This research explores the ways in which undergraduate and graduate students at a major R1 land-grant university in the western United States interact with AI tools. Students reported on using AI technologies, like ChatGPT, to aid in their learning. Preliminary findings suggest that freshman students are less likely to have used AI technologies than those later in their college careers. Encouragingly, students closest to entering the workforce are the ones with the most exposure to these technologies. Interestingly, students who identify as having any form of a disability or condition that impacts their learning (e.g., learning disability, neurodiversity, physical disability, etc.) initially reported lower usage of AI technologies compared to their classmates. The lower use by freshmen and increasing exposure to generative AI throughout students’ university experience is noteworthy. Students were also asked for their views on the formal integration of AI technologies into the College of Engineering courses. It could be valuable for universities to explore adding formal training to help equip students for the workforce. We anticipate that this study will highlight how exposure to AI technologies may prove essential for engineering students in preparing for a rapidly evolving workplace, as AI has the potential to enhance real-world problem-solving skills and help students become more equipped for workplace demands.
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- Award ID(s):
- 2346881
- PAR ID:
- 10631161
- Publisher / Repository:
- ASEE Conferences
- Date Published:
- Subject(s) / Keyword(s):
- GAI, Generative Artificial Intelligence, Engineering, Learning, AI Adoption
- Format(s):
- Medium: X
- Location:
- Montreal, Quebec, Canada
- Sponsoring Org:
- National Science Foundation
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