2024 ASEE Annual Conference & Exposition

The Future of Learning: Harnessing Generative AI for Enhanced Engineering Technology Education

Presented at Panel: AI and Engineering Technology Education: What, Why, How?

Engineering Technology education stands at the precipice of a profound transformation driven by the integration of Generative Artificial Intelligence (Generative AI). Incorporating generative AI into engineering technology education can enhance the learning experience, foster creativity, and prepare students for the increasingly AI-driven field of engineering. It allows students to focus on problem-solving, innovation, and the application of engineering principles, while AI handles routine tasks and provides valuable insights and guidance. However, it's crucial to strike a balance and ensure that students also develop a deep understanding of the fundamental concepts and skills that underlie the technology they are using. This abstract provides an overview of a study that explores the transformative potential and application of Generative AI in engineering technology education.
Generative AI refers to a category of AI models and algorithms that have the ability to generate new content that is similar to, or in some cases indistinguishable from, content created by humans. These AI systems are designed to generate data, such as text, images, audio, and more, based on patterns and knowledge they've learned from large datasets during their training.
Integrating Generative AI into engineering education can be a valuable way to prepare students for the future and equip them with skills relevant to emerging technologies. This study explores how Generative AI can revolutionize the traditional pedagogical approach by enabling the development of interactive lab experiences, simulations, and practical exercises to integrate and create a greater understanding of AI capabilities. These innovations create authentic learning environments, equipping students with hands-on experience and honing their problem-solving skills.
This study also scrutinizes the ethical implications and challenges tied to the incorporation of Generative AI in education. It emphasizes the need for unbiased AI algorithms and responsible usage while calling for comprehensive training and support for instructors in harnessing this innovative technology.
In conclusion, this study intends to demonstrate that harnessing Generative AI in engineering technology education has the potential to revolutionize the way students learn in addition to preparing students to leverage these technologies for innovative engineering solutions and equip them with valuable skills that are increasingly in demand in various engineering domains.

Authors
  1. Mr. Jody Lee Alberd Austin Peay State University [biography]
  2. Mahesh Kumar Pallikonda Austin Peay State University [biography]
  3. Prof. Ravi C. Manimaran Austin Peay State University [biography]
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