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Crowdsourcing-Based Learning: the Effective Smart Pedagogy for STEM Education

机译:基于众包的学习:茎教育的有效智能教育学

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Multiple innovative teaching and learning strategies, that strongly support the advanced technology-based education, emerged in recent years. However, there are no published data analytics and validated outcomes regarding how good those innovative teaching approaches support the main concepts of Smart Pedagogy. This paper presents the outcomes of the ongoing research, design and development project at the InterLabs Research Institute, Bradley University (Peoria, IL, USA) aimed to identify, analyze, test, implement and recommend various components of Smart Pedagogy for STEM education. Those components may include but are not limited to 1) learning- by-doing, active learning or experiential learning, 2) games-based learning and gamification of learning, 3) collaborative learning, 4) analytics-based learning, 5) flipped classroom, 6) crowdsourcing-based learning, 7) badging-based learning, and 8) productive failure-based learning. The obtained research outcomes about application of crowdsourcing-based learning in several STEM undergraduate and graduate courses are presented in this paper. Project outcomes undoubtedly demonstrate students' keen interest in active use of crowdsourcing-based learning in Sciences courses, in particular, and in highly technological Smart Pedagogy in STEM education, in general.
机译:近年来出现了多种创新教学和学习策略,强烈支持先进的技术教育。但是,没有公布的数据分析和有关这些创新教学方法如何支持智能教育学的主要概念的良好数据分析和验证结果。本文介绍了旨在识别,分析,检验,实施和推荐智能教育的各个组成部分核心教育部的持续研究,设计和开发项目的持续研究,设计和开发项目的结果。这些组件可能包括但不限于1)学习,积极学习或经验学习,2)基于游戏的学习和游戏,3)协同学习,4)基于分析的学习,5)翻转教室,6)基于众包的学习,7)基于徽章的学习和8)生产失败的学习。本文提出了关于在几个茎本科和研究生课程中应用众包的研究的研究结果。一般而言,项目结果无疑展示了学生对积极使用基于众群的学习,特别是在茎教育中的高技术智能教育学中的积极利用。

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