The influence of SRA programming on algorithmic thinking and self-efficacy using Lego robotics in two types of instruction
The influence of SRA programming on algorithmic thinking and self-efficacy using Lego robotics in two types of instruction
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DOI：
10.1007/s10798-019-09559-9
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发表时间：
2019-12-24
影响因子：
2.1
通讯作者：
Specht, Marcus
中科院分区：
文献类型：
--
作者：
Fanchamps, Nardie L. J. A.;Slangen, Lou;Specht, Marcus
本研究探讨发展的算法思维的一部分，计算思维技能和自我效能的小学生使用可编程机器人在不同的指令变量。计算思维是在21世纪世纪技能的背景下定义的，它描述了以计算机可以处理的方式（重新）制定问题的过程。编程机器人提供了特定的启示，因为它可以用于开发遵循感知-理性-行为（SRA）循环的程序。文献提供的证据表明，编程机器人有潜力提高算法思维作为计算思维的一个组成部分。具体而言，有迹象表明，使用SRA编程的学生在开放的脚手架学习环境中比通过直接教学更好地学习算法技能，并实现更高水平的自我效能。为了确定所使用的指令变量的影响，实验研究设计中，小学生解决基于算法的数学问题（网格图）的初步测量和他们的自我效能通过问卷调查确定。作为一种干预措施，学生们学习使用“乐高NXT”机器人和“头脑风暴”软件以两种不同的教学方式解决编程问题。后测量包括乐高挑战，解决数学问题（网格图），和重复的自我效能问卷。这项研究表明，我们对算法思维的测量增加取决于SRA的使用量（尽管不显著）。使用SRA循环的编程可被视为测量效应的原因。机器人干预期间使用的指令变体似乎只发挥了很小的作用。
This study investigates the development of algorithmic thinking as a part of computational thinking skills and self-efficacy of primary school pupils using programmable robots in different instruction variants. Computational thinking is defined in the context of twenty-first century skills and describes processes involved in (re)formulating a problem in a way that a computer can process it. Programming robots offers specific affordances as it can be used to develop programs following a Sense-Reason-Act (SRA) cycle. The literature provides evidence that programming robots has the potential to enhance algorithmic thinking as a component of computational thinking. Specifically there are indications that pupils who use SRA-programming learn algorithmic skills better and achieve a higher level of self-efficacy in an open, scaffold learning environment than through direct instruction. In order to determine the influence of the instruction variant used, an experimental research design was made in which pupils solved algorithm-based mathematical problems (grid diagrams) in a preliminary measurement and their self-efficacy determined via a questionnaire. As an intervention, pupils learn to solve programming issues in pairs using "Lego NXT" robots and "Mindstorms" software in two instruction variants. The post-measurement consists of a Lego challenge, solving mathematical problems (grid diagrams), and a repeated self-efficacy questionnaire. This research shows an increase of our measures on algorithmic thinking dependent on the amount of SRA usage (though not significant). Programming using the SRA-cycle can be considered as the cause of the measured effect. The instruction variant used during the robotic intervention seems to play only a marginal role.