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Applying Computational Thinking and Formative Assessment to Enhance the Learning Performance of Students in Virtual Programming Language

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Innovative Technologies and Learning (ICITL 2023)

Abstract

Computational thinking (CT) is considered to be one of the core competencies of the 21st century, and many scholars have explored the feasibility of CT in different subjects. However, traditional programming languages have a certain degree of difficulty, and it is difficult for learners to learn and understand the structure and logic of syntax in this process. Visual programming language improves upon these conditions and constraints. Additionally, formative assessment (FA) has been shown to increase students’ motivation and interest in programming courses while improving their performance. Therefore, the application of CT core competencies and visual programming formative assessment system (VPFAS) is proposed by this study. Also, we explore whether it can enhance learning performance of students in virtual programming. A total of 52 students were recruited in this 10-week experiment. The result shows that the experimental group significantly enhance their learning performance in virtual programming by applying the CT core competence and the VPFAS. This means that the experimental group can not only solve the program’s problems through the CT core competencies but also improve their knowledge of the program’s concepts and objects through the VPFAS. Thus, this study confirms that applying CT and FA can enhance student learning performance in virtual programming.

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Acknowledgments

This research is sponsored in part by the National Science and Technology Council, Taiwan under Grand No. NSTC 110-2511-H-006-008-MY3 and NSTC 112-2811-H-006-003.

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Correspondence to Yueh-Min Huang .

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Cheng, YP., Cheng, SC., Yang, M., Lin, JM., Huang, YM. (2023). Applying Computational Thinking and Formative Assessment to Enhance the Learning Performance of Students in Virtual Programming Language. In: Huang, YM., Rocha, T. (eds) Innovative Technologies and Learning. ICITL 2023. Lecture Notes in Computer Science, vol 14099. Springer, Cham. https://doi.org/10.1007/978-3-031-40113-8_13

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  • DOI: https://doi.org/10.1007/978-3-031-40113-8_13

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  • Online ISBN: 978-3-031-40113-8

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