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.

该项目进行了跨学科研究，以提高对体现学习的理解，因为它适用于当前基于技术的学习环境（例如，桌面模拟，交互式白板和3D交互式环境）的STEM主题。该项目以广泛的研究为基础，包括有关PI的先前工作，涉及体现学习和统计学习。 PI将体现的学习描述为吸引学习者的神经肌肉系统，因为他们在视觉，听觉和动力学上与周围的世界互动以构建新的知识结构。统计学习被描述为通常无意学习的能力，哪些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，这是许多STEM学科中掌握复杂主题的核心，包括物理和数学。该项目有两个中心研究问题：学生知识的增益如何受到具体学习程度的影响，以及在多大程度上，不同技术的学习环境限制或支持STEM主题的体现学习或支持体现的学习？为了研究这些问题，PIS使用两个物理主题在五个阶段进行了三个系列实验。 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示例性的模型和原则，以帮助课程和技术设计师创建学习方案，以考虑给定的学习环境提供的体现水平。