英文摘要
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This study explores fifth grade gifted students' and experts' mental models and modeling process, in the development of conceptual understanding and design of "loop" and "switch" programs in NXT-G. The students' performance could be seen as a starting point, and experts' performance could be seen as the role model. Suggestions for gifted students learning mobile robotics were proposed by comparing these two target groups. This study adopted the case study research method. Six fifth grade gifted students and two experts were purposely selected. Participants' experiences in completing the "Programming Concepts Test" were collected through the think aloud method and screen video capture. Additional evidence was gathered from the "Test of Understanding in Programming Concepts" and interviews. The results showed: 1. The "loop" and "step" models were adopted by the gifted students when they understood the "loop" program, while "single-switch," "multi-switch" and "odd" models were adopted in students' understanding of the "switch" program; however, "variable loop" and "nested loops" models were adopted by the experts when they performed the "loop" program, while the "multi-switch" model was adopted in experts' performance of the "switch" program. 2. The gifted students relied on class experience to select a model, and needed to verify their model via implementing the program. If they could not achieve the goal, they usually used trial and error to modify arguments or rejected their original model rather than revising it. However, the experts had abundant problem solving resources and experiences to form strategies. They usually verified their selected model via thought experiments and solved problems rapidly. We suggest adopting experts' strategy models (e.g., variable loop, nested loops) as templates to enhance students' basic understanding of programming and their experience of using programming models. Moreover, "prediction-implementation-sharing" could be used to encourage students' thinking experimentations and to compare different models' scopes and limitations.
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