【作者】 王倩倩；

【导师】 陈维维； 周应华；

【作者基本信息】 扬州大学 ， 教育硕士（专业学位）， 2022， 硕士

【摘要】 随着信息与智能时代到来,创新人才的培养成为社会发展的需求。机器人教育和机器人竞赛成为培养创新人才的有效途径,很多国家日益开展对机器人的学习和研究。目前我国很多学生通过参加机器人社团、机器人竞赛加入到机器人的学习,但是机器人教育在逐步开展的同时,也出现了诸如缺乏科学的理论体系、教学方式单一以及学生只重视竞赛的结果和荣誉等问题。因此,如何更好地使学生掌握机器人竞赛所需基本知识,发散学生创新思维进而能够提升学生创造力和问题解决能力,使机器人教育能够在中小学有效开展,是我们需要研究的关键问题。本研究以机器人竞赛活动所需的基本知识为教学主线,将设计型学习这一新兴学习范式融入到机器人常规课堂中,构建教学活动框架并开展区别于竞赛集训的教学活动进行实践探索。首先总结了国内外设计型学习和机器人教育领域的研究成果和现状,并阐释和分析本文的理论基础;其次对机器人竞赛活动的现状、需求、以及具体活动概述进行分析,为教学活动设计提供支撑;再次通过教学活动前期分析明确教学目标、内容和学习者特征,以设计型学习经典模型为参考,构建适用于机器人竞赛教学的活动框架,该框架以学生活动为主体,设计了探究学习、迭代设计和反思优化三个主要阶段。最后在南京市K小学以乐高EV3为载体开展教学设计、教学实施、教学评价以及反思与修正四个环节的教学实践,实践过程中以活动评价表、课堂观察和访谈等方式检验教学实施的效果并对初始框架进行修正完善,最终形成基于设计型学习的小学机器人竞赛教学活动框架。基于以上工作,通过创造力量表测试、作品评价数据和课后访谈进行分析,取得一些研究成果:在机器人教育常规课堂中,机器人竞赛教学活动框架的设计与实践是行之有效的;基于设计型学习的小学机器人竞赛教学活动可以有效地培养并提高学生的创造力和问题解决能力,提高对机器人的学习兴趣和积极性,在学习知识的同时提高综合素质。更多还原

【Abstract】 With the advent of the era of information and intelligence,the cultivation of innovative talents has become the demand of social development.Robotics education and robotics competitions have become an effective way to cultivate innovative talents,and many countries are increasingly carrying out learning and research on robots.At present,many students in China have joined the learning of robots by participating in robot clubs and robot competitions,but while robot education is gradually being carried out,there are also problems such as the lack of scientific theoretical system,single teaching methods,and students only pay attention to the results and honors of competitions.Therefore,how to better enable students to grasp the basic knowledge required for robot competitions,divergent students’ innovative thinking and thus enhance students’ creativity and problem-solving ability,so that robot education can be effectively carried out in primary and secondary schools,is the key issue we need to study.This study takes the basic knowledge required for robot competition activities as the main teaching line,integrates the emerging learning paradigm of design learning into the regular classroom of robots,constructs the teaching activity framework and carries out teaching activities that are different from competition training for practical exploration.First of all,the research results and current situation in the field of design-based learning and robot education at home and abroad are summarized,and the theoretical basis of this paper is explained and analyzed;secondly,the current situation,needs,and specific activities of robot competition activities are analyzed to provide support for the design of teaching activities;again,the teaching objectives,content and learner characteristics are clarified through the pre-analysis of teaching activities,and the activity framework suitable for robot competition teaching is constructed with the design learning classic model as a reference,which takes student activities as the main body and designs inquiry learning.Iterative design and reflection on optimization have three main stages.Finally,in Nanjing K Primary School,Lego EV3 was used as the carrier to carry out the teaching practice of teaching design,teaching implementation,teaching evaluation and reflection and correction,and in the process of practice,the effect of teaching implementation was tested by means of activity evaluation forms,classroom observations and interviews,and the initial framework was revised and improved,and finally the teaching activity framework of the primary school robot competition based on design-based learning was formed.Based on the above work,through the creation of strength table tests,work evaluation data and after-class interviews,some research results have been obtained:in the regular classroom of robot education,the design and practice of the robot competition teaching activity framework is effective;the design-based learning of primary school robot competition teaching activities can effectively cultivate and improve students’ creativity and problem-solving ability,improve the learning interest and enthusiasm of robots,and improve the comprehensive quality while learning knowledge.更多还原