Academic integrity breaches and plagiarism existed long before the rise of generative artificial intelligence (AI). Students had already turned to paid online tutoring platforms like Chegg and CourseHero to obtain assistance with homework assignments, take-home exams, and course projects. However, the emergence of large language models like ChatGPT offers a novel approach to address these online tutoring services. It provides students with an opportunity to seek legitimate help while reshaping how we construct assignment questions and projects. Consider a real-world scenario where problems often lack the information and consistent methodologies taught in courses, making it insufficient to offer technological solutions. This study focuses on the digital signal processing course within electrical and robotics engineering programs. This course predominantly involves assignments that require coding and can easily be prone to plagiarism through generative AI platforms. For instance, tasks like designing a low-pass filter with specified desired frequency and signal parameters can be tackled using textbook-based methods that generative AI can readily employ to generate solutions. In reality, however, these desired parameters are often unknown, necessitating the application of rigorous system identification techniques to determine the appropriate filter design.
The author proposes introducing open-ended problems and projects in these courses. This approach aims to foster critical thinking among students and prepare them for the demands of the industrial and research sectors. This shift in the curriculum can serve as a progressive step in addressing academic integrity issues and revitalizing engineering technology education. In essence, the utilization of generative AI models like ChatGPT can serve as a force for positive change in the educational landscape. It enables students to receive genuine support while pushing educational institutions to adapt by emphasizing critical thinking and problem-solving skills. This transformation represents a significant stride in the ongoing effort to maintain academic integrity and meet the evolving needs of the engineering and technology sectors.
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