The education sector is experiencing significant changes as artificial intelligence (AI) tools become more widespread and advanced. The era of paying for essay-writing services or homework solutions is fading. Tools like ChatGPT and Copilot, which are free and adaptable, can address nearly any student inquiry. This shift in teaching methods has been explored previously. Uysalel highlights how AI-driven interactions can boost student engagement, pointing to a transition towards more dynamic learning settings (Uysalel 2024). Barakat stresses the importance of deliberately integrating AI tools in the engineering curriculum, advocating for students to use these systems while critically assessing their outputs (Barakat 2024). Jim\u00e9nez Romanillos and Andersson examine Bloom\u2019s Taxonomy within AI’s role in design education, illustrating AI’s potential to alter cognitive expectations for assignments (Jim\u00e9nez Romanillos and Andersson 2024).<\/p>\n
Teachers across various fields are questioning how to create assignments that support learning with AI’s constant presence. This question lacks a universal answer, as educators differ in opinions on AI’s role in education based on their discipline or teaching philosophy. Two electrical engineering professors at a graduate university were interviewed to understand their perspectives on AI in STEM courses. Both professors taught classes in the electrical and computer engineering undergraduate program, and it was known that they held different views on AI’s role in their courses. These interviews aim to demonstrate that even within the same disciplines, educators can have varied approaches to course and assignment design concerning AI. Note that Professor A’s responses were transcribed from an in-person interview, while Professor B’s answers came via email due to scheduling issues.<\/p>\n
Professor A teaches three junior and senior-level electrical and computer engineering courses: Microprocessor Systems, Computer Organization, and Embedded Systems Design, all of which involve considerable programming. Assignments in Microprocessor Systems and Embedded Systems require students to submit code, which is then tested for functionality. In Computer Organization, assignments include lab work for processor design and traditional homework problems on Canvas. Professor B teaches mainly electrical and computer engineering courses, focusing recently on digital logic, and has also taught an Intro to AI course. Students engage in hands-on projects using Verilog, run simulations, and write brief reports aligned with ABET outcomes.<\/p>\n
Professor A noticed students using AI tools, like ChatGPT, about a year ago (Fall 2024) when a student used it during a final exam, confirming AI’s role in completing assignments. Professor B, an early adopter, quickly recognized student use, noting that some writing and code explanations seemed overly polished or generic. Professor A views AI in education as both an opportunity and a challenge, advocating for students to first learn core principles before utilizing AI, much like ensuring a child understands math before using a calculator. Professor B sees AI as a significant opportunity if used intentionally, emphasizing the need for structure to ensure students engage in critical thinking.<\/p>\n
To counter AI use in assignments, Professor A uses Respondus Lockdown Browser during exams, although not fond of its glitches, after students were caught using AI in exams, resulting in academic dishonesty failures. Professor B integrates AI into assignments, allowing students to use ChatGPT for code explanation or refactoring, followed by critiquing its errors. Reflecting on assignment changes during COVID, Professor A recalls a drop in learning, emphasizing that AI used as a substitute for learning hampers students\u2019 development as competent engineers. Professor B focused on engagement during COVID and now concentrates on authenticity, designing assignments that reveal students\u2019 thought processes.<\/p>\n
The department and institution provide guidance on AI use in assignments, with Professor A noting the Provost’s office\u2019s suggested syllabus language and school-wide faculty retreat discussions. While no formal department discussions occurred, campus-wide guidance suffices, though more tools and clarity would aid, especially for code evaluation. Professor B\u2019s university encourages setting personal course policies to responsibly acknowledge AI. Professor A has discussed AI with a colleague, disagreeing on its early integration, while Professor B collaborates to rethink assignments and automate grading with AI, maintaining instructor oversight.<\/p>\n
Professor A stresses balance, highlighting the need for foundational skills to ensure AI enhances rather than limits learning. Open to change, he believes students must first grasp core principles. Professor B accepts AI\u2019s permanence, focusing on helping students learn alongside it. The academic landscape will continue to transform, and educators may need to adapt if the optimal way to prepare students evolves.<\/p>\n