ISSN: 2226-6348
Open access
The 4th Industrial Revolution is sweeping the world, incorporating technology into communities. High-tech tools and resources are being developed as part of the digital revolution. In the realm of education, there has been a larger emphasis on coding instruction in order to develop a sufficient number of young people to fill fifty percent of computing-related STEM (science, technology, engineering, and mathematics) job openings. Our children and grandchildren must think critically in order to solve the world's ill-structured, unexpected, and intricate issues. Computational thinking, when combined with critical thinking, can produce automatic or semi-automated problem-solving solutions. As a result, computational thinking is becoming increasingly important in science, mathematics, and nearly every other topic. This is demonstrated by Malaysia's recent implementation of computer coding into the school curriculum in order to build 21st century competencies in students. Computational thinking (CT) is one of the conceptual underpinnings required to solve problems successfully and efficiently by combining facts and ideas. In order to solve problems and offer solutions that can be applied in a variety of contexts, computational thinking—i.e., algorithmically, with or without the use of computers—is crucial in computing and information science. It is critical to foster a diversity of abilities and competences among students as to successfully navigate the complexity challenge in the real world. As a result, building a learning environment can be a daunting task for many instructors who lack the tools and research-based expertise to redesign their teaching methods. This conceptual framework has two objectives: (1) developing deep learning and connected computational thinking through a mathematical curriculum instructional model which is capable of improving students' problem-solving skills; and (2) implementing the designed model to assist teachers in education who encountered difficulties when using problem-based curriculum materials. A computational mathematics problem-based learning (CM-PBL) teaching technique is developed to achieve these goals. Students can use the CM-PBL learning framework to simulate and build their own computational models as to aid their self-learning and comprehension of mathematical concepts. It demonstrates that how students can use coding to improve their soft engineering skills.
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In-Text Citation: (Ting et al., 2023)
To Cite this Article: Ting, K. S., Talib, O., Ayub, A. F. M., Zolkepli, M., Yee, C. C., & Hoong, T. C. (2023). Word Problems as a Vehicle for Teaching Computational Thinking. International Journal of Academic Research in Progressive Education and Development, 12(1), 1493–1509.
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