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Making Sense by Building Sense: Kindergarten Children’s Construction and Understanding of Adaptive Robot Behaviors

机译:通过建立感官来理解:幼儿园的孩子对自适应机器人行为的建构和理解

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This study explores young children’s ability to construct and explain adaptive behaviors of a behaving artifact, an autonomous mobile robot with sensors. A central component of the behavior construction environment is the RoboGan software that supports children’s construction of spatiotemporal events with an a-temporal rule structure. Six kindergarten children participated in the study, three girls and three boys. Activities and interviews were conducted individually along five sessions that included increasingly complex construction tasks. It was found that all of the children succeeded in constructing most such behaviors, debugging their constructions in a relatively small number of cycles. An adult’s assistance in noticing relevant features of the problem was necessary for the more complex tasks that involved four complementary rules. The spatial scaffolding afforded by the RoboGan interface was well used by the children, as they consistently used partial backtracking strategies to improve their constructions, and employed modular construction strategies in the more complex tasks. The children’s explanations following their construction usually capped at one rule, or two condition-action couples, one rule short of their final constructions. With respect to tasks that involved describing a demonstrated robot’s behavior, in describing their constructions, explanations tended to be more rule-based, complex and mechanistic. These results are discussed with respect to the importance of making such physical/computational environments available to young children, and support of young children’s learning about such intelligent systems and reasoning in developmentally-advanced forms.
机译:这项研究探索了幼儿构造和解释行为神器(带有传感器的自动移动机器人)的自适应行为的能力。行为构建环境的核心组件是RoboGan软件,该软件通过a-时态规则结构支持儿童时空事件的构建。六个幼儿园的孩子参加了这项研究,三个女孩和三个男孩。活动和采访是在五个环节中分别进行的,其中包括日益复杂的施工任务。结果发现,所有孩子都成功地构造了大多数这样的行为,并以相对较少的周期调试了他们的结构。对于涉及四个补充规则的更复杂的任务,成年人需要注意问题的相关特征。 RoboGan界面提供的空间脚手架很受孩子们使用,因为他们一直使用部分回溯策略来改善他们的结构,并在更复杂的任务中采用模块化的结构策略。孩子们在构造之后的解释通常以一条规则或两对条件行动夫妇为上限,其中一条规则比他们的最终构造少。对于涉及描述演示的机器人行为的任务,在描述其结构时,解释倾向于基于规则,复杂和机械化。讨论这些结果的方面是关于为幼儿提供此类物理/计算环境的重要性,以及支持幼儿学习此类智能系统和发展先进形式的推理。

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