Planning Grant: Engineering Tools for Education Research (EnTER)

提出建议的团队设想建立一个工程研究中心，该中心将改变学习和教学，专注于STEM教育中的主动学习。目前了解在这种环境中发生了什么的努力仅限于在使用紧凑、简单的数据形式(如成绩或调查)的研究和使用学生作业的视频和书面记录的研究之间进行选择。紧凑的数据提供了洞察力，但从课堂环境中删除了，而详细的记录审查规模较小，因为分析这些丰富的定性数据需要劳动密集型方法。与这两种策略相关的妥协严重限制了在发展对课堂环境的科学理解并利用这些信息影响现实世界课堂方面的进展。要从根本上改变教育环境促进学习的方式，需要多管齐下，将拥有认知科学和学习科学、生物传感、数据分析和计算机系统专业知识的研究人员聚集在一起。由此产生的工程系统将解决有关学生如何在个人、团队和课堂社区中学习最好的基础研究问题。这些知识随后可以转化为实用工具，为教师提供课堂内洞察力，了解学生在大规模积极学习环境中的思考和参与。这笔ERC计划拨款将促进团队和中心结构的发展，美国国家科学院和工程院认为，这是在下个世纪推进个性化学习所必需的。通过这些工具开发的知识将以包容和伦理敏感的方式导致课程、教育学和支持学习和教学的工程系统的设计的进步。具有多个并发对话和活动的主动学习环境是学习的挑战；然而，了解它们的动态对学习科学的进步至关重要。我们的工程团队将发明新的传感器，嵌入低功耗的可穿戴计算平台，其数据将由下一代机器学习算法处理。ERC计划赠款将通过研讨会和数据黑客松将不同学科的研究人员聚集在一起，以了解研究问题并展示潜在的技术。这些工具化的学习环境将使研究人员能够迅速地制定和评估假设，其规模远远超过今天所能达到的水平。ERC规划团队将直接与一系列利益相关者接触，他们对下一代劳动力的教育感兴趣。这些利益相关者包括学生、教育工作者、研究人员、管理人员、行业和认证机构，他们将参与围绕拟建中心建立生态系统。鉴于这项工作的性质，隐私和对人类受试者的道德待遇将是该项目所有方面的核心。黑客马拉松和研讨会活动将通过展示这些技术在教育研究中的潜力，影响塔夫茨大学以外的更广泛的研究社区。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The proposing team envisions an Engineering Research Center that will transform learning and instruction with a focus on active learning in STEM education. Current efforts to understand what takes place in such environments are limited to choosing between studies using compact, simple forms of data (such as grades or surveys), and studies employing video and written records of students' work. Compact data provide insight but are removed from the classroom setting, while detailed record reviews are small-scale because of the labor-intensive methods required to analyze these rich, qualitative data. The compromises associated with both strategies have severely limited progress in developing a scientific understanding of the classroom environment and using this information to impact real-world classrooms. Radically altering the way educational environments foster learning requires a multi-pronged approach bringing together researchers with expertise in cognitive and learning sciences, bio-sensing, data analytics and computer systems. The resulting engineered system will address fundamental research questions concerning how students learn best as individuals, in teams, and in classroom communities. This knowledge can subsequently be translated into practical tools to provide instructors with in-classroom insight into students' thinking and engagement in active learning environments at scale. This ERC planning grant will facilitate the development of a team and Center structure that the National Academies of Science and Engineering believe is necessary to Advance Personalized Learning in the next century. Knowledge developed through these tools will, in an inclusive and ethically sensitive manner, lead to advances in curriculum, pedagogy, and the design of engineered systems in support of learning and instruction.Active learning environments with multiple concurrent conversations and activities are a challenge to study; however, understanding their dynamics is central to the advancement of learning science. Our engineering team will invent new sensors, embedded in low-power wearable computing platforms, whose data will be processed by next-generation machine learning algorithms. The ERC planning grant will bring together researchers in convergent disciplines through workshops and data hackathons to understand the research problems and demonstrate potential technologies. These instrumented learning environments will allow researchers to formulate and evaluate the hypotheses rapidly and at a scale well beyond that which can be achieved today. The ERC planning team will directly engage a range of stakeholders with an interest in the education of the next generation workforce. These stakeholders include students, educators, researchers, administrators, industry and accreditation agencies that will be engaged to build an ecosystem around the proposed center. Given the nature of the effort, privacy and ethical treatment of human subjects will be central to all aspects of the project. The hackathons and workshop activities will impact the broader research community beyond Tufts University by showing the potential of these technologies for educational research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.