Abstract
This paper investigated high school students’ STEM capability in a robotic arm educational competition. The learning design of the competition based on the pedagogy of copy and redesign, and social creativity framework. Students learned the process of building up robotic arms by copying instructors’ examples, discussing possible ways of redesigning the robotic arms. The students need to present their creativity by using robotic arms as boundary objects in a collaboration. After a one-day workshop and another one-day competition, the observation results showed that students were capable of exhibiting unique creativity to solve the problem during the competition, such as refining the robotic arms to grab something which it had not been able to reach, or adding materials on the robots to create a better user experience. Students also applied scientific and mathematical knowledge to improve the robots, performed integrated STEM ability. Furthermore, students’ meta-cognitive strategies of taking notes and collaboration were evidenced. It indicated that the copy and redesign, and social creativity framework can facilitate students’ creative performance of STEM capability. Moreover, as the study adopted students’ attitudes towards STEM survey, the results showed that students’ attitudes towards STEM had no significance after the curriculum design. The possible reasons included that short-term learning process might have minor influence on students’ STEM attitudes. Other possible reasons might be the ceiling effect, and small number of samples. Future study was suggested to evaluate the learning design into a long-term curriculum, adopt semi-structured interview to investigate more delicate relationship between the learning design and students’ performance, and conduct STEM ability test to understand students’ performance.
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Chu, L., Ting, YL., Tai, Y. (2020). Building STEM Capability in a Robotic Arm Educational Competition. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Human and Technology Ecosystems. HCII 2020. Lecture Notes in Computer Science(), vol 12206. Springer, Cham. https://doi.org/10.1007/978-3-030-50506-6_28
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