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Friday, May 31
Instructional Applications & Insights
Fri, May 31, 1:30 PM - 3:05 PM
Grand Ballroom I

Apply “STEAMS” Methodology on Managing Europe Travel (305121)

*Charles Chen, Applied Materials 
Mason Chen, Stanford OHS 

Keywords: Science, Technology, Engineering, Artificial Intelligence, Math, Statistics

This paper adopts STEAMS (Science, Technology, Engineering, Artificial Intelligence, Math, Statistics) methodology. The objectives of this paper are to introduce the benefits of integrating all 6 “STEAMS” elements, especially living in the Big Data World. Managing Europe Travel case study was demonstrated to present this novel “STEAMS” concept as compared to current “STEM” or” STEAM” approach. This paper was addressing travel cost & time while visiting five major cities in Europe. The main objective was to build a robust route which can meet both time & expense requirements. The input variables used were the intra-city time & expense while the response variables were the total time & expense. There are three core visions of this “STEAMS” methodology: (1) replace “Art” with “Artificial Intelligence”, (2) separate “Statistics” from “Math”, and (3) integrate all six “STEAMS” elements. Adding the “Artificial Intelligence” Black-Box element can trigger and enhance the effectiveness of “Scientific” Research and “Math” algorithms. Separating the “Statistics” element from “Math” can conduct more effective risk management and draw practical conclusions. “Engineering” DOE can validate the “Artificial Intelligence” algorithm. The “STEAMS” approach can enhance the cross-linking and becoming a natural critical thinking way for most scientists and engineers striving in the modern Big Data era. It’s critical and urgent for educators and teachers to migrate from their traditional STEM approach to the new “STEAMS” approach to educate our next generations in their early school learning and career development.