Embracing Computational Thinking as an Impetus for Artificial Intelligence in Integrated STEM Disciplines through Engineering and Technology Education 

Abstract


 The scope and versatile nature of engineering and technology education as a discipline provide a platform for the integration of computational thinking (CT) into STEM education, accomplishing the goal of bringing not only computer science principles into the K-12 education but also the fundamentals of machine learning (ML) and artificial intelligence (AI) into the curriculum. Today, it is commonplace to say that artificial intelligence and machine learning technologies impact the workplace and continue to revolutionize as well as create new demands for solving daily world challenges. This article discusses the integration of computational thinking practices of decomposition, pattern recognition, algorithmic thinking, and abstraction as key to problem-solving practices that may enhance the development of AI and ML capabilities in high school students. The intent of this article is to contribute to ongoing discussions among educators, employers, parents, and all those concerned with how best to prepare a citizenry that is digitally revolutionized. Implications are offered for the assessment of CT integrated within STEM, curriculum, pedagogy, and professional development for STEM teachers.

A Bibliometric Review Leveraging the use of Computational Thinking for educational sustainability in STEM subjects: A Framework for Teaching and Learning in the 21st Century.

“…Furthermore, there is a need to underscore how the STEM design challenges undertaken with students can effectively harness CT for problem-solving. Additionally, STEM teacher educators should explore avenues to integrate CT and create learning experiences that foster the understanding of AI and ML fundamentals within teacher preparation and education coursework (Asunda et al, 2023). This entails offering pre-service teachers opportunities to cultivate competencies and knowledge in CT, encompassing AI and ML, equipping them to effectively guide their future students.…”

“…Rather than mere pro ciency in a speci c array of knowledge concerning a singular device or programming language, it embodies a cognitive methodology. Although computational thinking (CT) is frequently conjoined with computers and coding, it is imperative to acknowledge its potential impartation even in the absence of tangible computational devices (Asunda, Faezipour, Tolemy & Do Engel, 2023). Teaching using CT approach helps scaffold learners to understand the problem at hand, by effectively breaking it down into more manageable steps, thereby enhancing their comprehension and mastery of the subject (Lee, Wu, Lin, Wang & Huang, 2024; Mumcu, Uslu, & Yıldız, 2023).…”