A Balanced Pedagogical Approach toward AI Readiness Education for STEM Learners

Abstract

Artificial intelligence (AI) is increasingly being applied to disciplines beyond computer science (CS). Engineers, statisticians, business analysts, biologists, physicists, physicians, and pharmacists, are among the many non-CS professionals who leverage the power of AI algorithms and systems for solving their domain-specific problems. Although AI has been found useful for solving a wide range of previously unsolvable problems, there are important limitations associated with contemporary AI. It is therefore important to inform current and future AI users regarding both strengths and weaknesses of AI in its current form, as well as what AI will be like in the foreseeable future. In this paper, the authors describe a pedagogical approach toward educating AI users from a range of STEM disciplines so that they can best exploit what AI has to offer. Specifically, a balanced approach is taken to ensure that learners gain knowledge and skills in what AI can or cannot do for them. A growing suite of experiential learning modules, which complement existing educational resources, serve as a vehicle for getting STEM learners ready for a future workplace characterized by significant use of AI technologies. These learning modules promote active learning and can be applied in a traditional classroom setting, self-directed online study, or a mix of the two modes. The paper ends with a presentation of encouraging results of actual use of the experiential learning modules in a mixed mode setting across multiple quantitative disciplines. All project artifacts, including the developed experiential learning modules, recommended uses, and best practices, are freely available on the project website. Interested educators and researchers are welcome to use the available resources and/or contribute to the on-going research.