Abstract
Existing computational thinking (CT) research focuses on programming in K-12 education; however, there are challenges in introducing it into the formal disciplines. Therefore, we propose the introduction of non-programming plugged learning in mathematics to develop students’ CT. The research and teaching teams collaborated to develop an instructional design for primary school students. The participants were 112 third- and fourth-grade students (aged 9–10) who took part in three rounds of experiments. In this paper, we present an iterative problem-solving process in design-based implementation research, focusing on the implementation issues that lead to the design principles in the mathematics classroom. The computational tasks, environment, tools, and practices were iteratively improved over three rounds to incorporate CT effectively into mathematics. Results from the CT questionnaire demonstrated that the new program could significantly improve students’ CT abilities and compound thinking. The results of the post-test revealed that CT, including the sub-dimensions of decomposition, algorithmic thinking, and problem-solving improved threefold compared to the pre-test between the three rounds, indicating that strengthened CT design enhanced CT perceptions. Similarly, the students’ and teacher’ interviews confirmed their positive experiences with CT. Based on empirical research, we summarize design characteristics from computational tasks, computational environment and tools, and computational practices and propose design principles. We demonstrate the potential of non-programming plugged learning for developing primary school students’ CT in mathematics.
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Acknowledgements
The authors would like to thank Ling Xie who conducted instructional design and implementation, the mathematics teacher team for their participation in classroom observation and seminars in a primary school attached to Huazhong University of science and technology, Wuhan, China, and thank Xing Li, Dandan Wang, and Niu Li for their assistance with experiments.
Funding
This study was funded by a grant (Grant Number: 71874066) from the National Natural Science Foundation of China and a grant (Grant Number: 21YJC880026) from the Philosophy and Social Sciences Planning Project of the Ministry of Education, China.
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Appendices
Appendix 1
Appendix 2
Transfer exercises
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1.
Use 20 fence sections, each measuring 1 m to enclose a rectangular field for planting potatoes. How do you enclose the largest area? Answer: The area of the square is the largest; side length: 20÷4=5(m); area: 5×5=25(m2).
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2.
Use 12 fence sections, each measuring 1 m to enclose a rectangular bale of straw with two adjacent sides against the wall. How do you enclose the largest area?
Answer: The area of the square is the largest; length + width = 12(m); length=6(m); width=6(m); area: 6×6=36 (m2)
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3.
Use 16 fence sections, each measuring 1 m to enclose a rectangular chicken coop with one side against the wall. How do you enclose the largest area?
Answer:
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(1)
Long side against the wall: length+2×width=16
Length (m)
Width (m)
Area (square meters)
14
1
14
12
2
24
10
3
30
8
4
32
6
5
30
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(2)
Short side against the wall: width+2×length=16
Length (m)
Width (m)
Area (square meters)
7
2
14
6
4
24
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Wang, J., Zhang, Y., Hung, CY. et al. Exploring the characteristics of an optimal design of non-programming plugged learning for developing primary school students’ computational thinking in mathematics. Education Tech Research Dev 70, 849–880 (2022). https://doi.org/10.1007/s11423-022-10093-0
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DOI: https://doi.org/10.1007/s11423-022-10093-0