Exploring the future of engineering education: Perspectives from a workshop on artificial intelligence and the future of stem and societies

Conrad Tucker, Kathy Schmidt Jackson, John Jongho Park

Research output: Contribution to journalConference articlepeer-review

Abstract

The objective of this NSF funded workshop was to explore ways that artificial intelligence (AI) is transforming the jobs landscape and in turn, the knowledge portfolio and skills that educators should be imparting on their students prior to graduation. To best address these issues, engineering researchers, policy advocates, and industry leaders were convened to discuss the future of STEM and societies in the age of AI. From an engineering education domain, workshop participants were made aware of fundamental breakthroughs in AI that have resulted in their wide-scale adoption in society, and how these breakthroughs may impact the types of jobs that engineers of the future will do. Pre- and post-survey data were acquired from the participants in order to quantify the differences, if any, in terminology such as AI, and STEM. Beyond semantic differences in terminology, data pertaining to the solutions proposed by different groups were also collected. I.e., from an academic point of view, what changes are needed in industry and government, in order to facilitate the changing nature of education? From a government perspective, what should be the national funding priorities in order to ensure that the U.S. remains highly competitive on the global landscape and leverages the power of AI to innovate and retrain its workforce? From an industry perspective, how should degree programs evolve to meet the needs of the real world? Findings from this workshop can serve as a guide to researchers and decision makers in academia, government and industry on how AI will transform both STEM education and the workforce.

Original languageEnglish (US)
Article number691
JournalASEE Annual Conference and Exposition, Conference Proceedings
Volume2020-June
StatePublished - Jun 22 2020
Event2020 ASEE Virtual Annual Conference, ASEE 2020 - Virtual, Online
Duration: Jun 22 2020Jun 26 2020

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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