Abstract
Computational thinking sits at the core of every engineering and computing related discipline. It has increasingly emerged as its own subject in all levels of education. It is a powerful cornerstone for cognitive development, creative problem solving, algorithmic thinking and designs, and programming. How to effectively teach computational thinking skills poses real challenges and creates opportunities. Targeting entering computer science and engineering undergraduates, we resourcefully integrate elements from artificial intelligence (AI) into introductory computing courses. In addition to comprehension of the essence of computational thinking, practical exercises in AI enable inspirations of collaborative problem solving beyond abstraction, logical reasoning, critical and analytical thinking. Problems in machine intelligence systems intrinsically connect students to algorithmic oriented computing and essential mathematical foundations. Beyond knowledge representation, AI fosters a gentle introduction to data structures and algorithms. Focused on engaging mental tool, a computer is never a necessity. Neither coding nor programming is ever required. Instead, students enjoy constructivist classrooms designed to always be active, flexible, and highly dynamic. Learning to learn and reflecting on cognitive experiences, they rigorously construct knowledge from collectively solving exciting puzzles, competing in strategic games, and participating in intellectual discussions.
Highlights
Introduction and related worksTeaching and learning computational thinking or CT, were originally realized over three and a half decades ago [1]
The aim was to draw out constructionism in every child and to leverage cognitive development, intellectual and mental abilities to acquire, transform, and consolidate knowledge
Approaching CT from a different perspective, we present pedagogical benefits and designs of an integration of classical and contemporary elements from AI – artificial intelligence into an introductory course for CS and engineering undergraduates
Summary
Teaching and learning computational thinking or CT, were originally realized over three and a half decades ago [1]. Designing a course on computational thinking often reflects on computer science and programming. It provides free indoor and outdoor learning activities to engage learners of all ages to computational thinking Those who prefer undertaking it with block programming environment are familiar with Scratch [13], which allows creators to create interactive arts, animations, stories, and games. We propose a comprehensive module on CT comprising a series of carefully selected AI puzzles and games that have been deliberately organized by the levels of CT skills required to solve the problems and coherence, continuity, and cohesion of the underlying fundamentals in data structures and algorithms. College classroom discussions are preferable to lectures when the learning objectives involve developing thinking skills and applying knowledge to new circumstances [15].
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