Embodied STEM Learning Across Technology- Based Learning Environments

跨基于技术的学习环境的具体 STEM 学习

• 批准号: 1020367
• 负责人: Arthur Glenberg
• 金额: $ 252.15万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1020367&HistoricalAwards=false
• 关键词: Embodied; STEM; Learning; Across; Technology

This project conducts interdisciplinary research to advance understanding of embodied learning as it applies to STEM topics across a range of current technology-based learning environments (e.g., desktop simulations, interactive whiteboards, and 3D interactive environments). The project builds on extensive research, including prior work of the PIs, regarding both embodied learning and statistical learning. The PIs describe embodied learning as engaging the neuromuscular systems of learners as they interact with the world around them visually, aurally, and kinesthetically in order to construct new knowledge structures. Statistical learning is described as the ability to learn, often without intent, which sequences of stimuli are consistent with a set of rules. An example of statistical learning is pattern recognition, which is central to mastery of complex topics in many STEM disciplines including physics and mathematics.The project has two central research questions: How are student knowledge gains impacted by the degree of embodied learning and to what extent do the affordances of different technology-based learning environments constrain or support embodied learning for STEM topics? To investigate these questions, the PIs are conducting three series of experiments in five phases using two physics topics. The first four phases are developmental and the final phase implements and assesses the two modules in schools (20 plus teachers, 700 plus K-12 students) in Arizona and New York (15 total sites, 10 plus public schools, minimum one Title I school).The aim of this project is to meld these two research trajectories to yield two key outcomes: 1) basic research regarding embodiment and statistical learning that can be applied to create powerful STEM learning experiences, and 2) the realization of exemplary models and principles to aid curriculum and technology designers in creating learning scenarios that take into account the level of embodiment that a given learning environment affords.

该项目进行跨学科研究，以促进对体现学习的理解，因为它适用于当前一系列基于技术的学习环境中的STEM主题（例如，桌面模拟、交互式白板和3D交互式环境）。该项目建立在广泛的研究基础上，包括PI之前的工作，关于体现学习和统计学习。 PI将具身学习描述为参与学习者的神经肌肉系统，因为他们与周围的世界进行视觉，听觉和动觉互动，以构建新的知识结构。统计学习被描述为学习的能力，通常没有意图，刺激序列与一组规则一致。 统计学习的一个例子是模式识别，这是掌握许多STEM学科（包括物理和数学）复杂主题的核心。该项目有两个中心研究问题：学生的知识增益如何受到体现学习程度的影响，以及不同技术学习环境的可供性在多大程度上限制或支持STEM主题的体现学习？为了研究这些问题，PI正在使用两个物理主题进行五个阶段的三个系列实验。前四个阶段是发展性的，最后一个阶段是在学校实施和评估这两个模块（20多名教师，700多名K-12学生）在亚利桑那州和纽约（共15个站点，10多所公立学校，至少一所标题I学校）。该项目的目的是融合这两个研究轨迹，以产生两个关键成果：1）关于具体化和统计学习的基础研究，可以应用于创建强大的STEM学习体验，和2）实现示例性模型和原则，以帮助课程和技术设计者创建学习场景，这些场景考虑到给定学习环境提供。