EXP: Inq-Blotter - A Real Time Alerting Tool to Transform Teachers' Assessment of Science Inquiry Practices

EXP：Inq-Blotter - 一种实时警报工具，可改变教师对科学探究实践的评估

• 批准号: 1629045
• 负责人: Janice Gobert
• 金额: $ 55万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1629045&HistoricalAwards=false
• 关键词: EXP; Inq; Blotter; Real; Time

The Cyberlearning and Future Learning Technologies Program funds efforts that support envisioning the future of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects design and build new kinds of learning technologies in order to explore their viability, to understand the challenges to using them effectively, and to study their potential for fostering learning. This EXP project addresses the need for real-time diagnostic tools for teachers that can assess students' needs, i.e. provide formative assessment, in order to improve science instruction. The project will extend, pilot, implement, and study Inq-Blotter, a scalable, web-based alerting system that enables teachers' formative assessment of middle school students' Physical Science scientific practices, aligned to the newly released national framework Next Generation Science Standards. The Inq-Blotter alerting system will be used in conjunction with Inq-ITS (Inquiry Intelligent Tutoring System), in which students "show what they know" by conducting inquiry with simulations. Students form questions, design and conduct experiments, interpret data, warrant their claims with data, and communicate their findings. As students work, they are assessed in real-time by the algorithms of Inq-ITS. To complete the formative assessment loop, the Inq-Blotter alerting tool sends real time alerts to teachers' laptops and smartphones on students' inquiry skills so that the teachers know who needs the most help and on which skills. Discourse between teachers and students will be analyzed to better understand how this alerting system can support teachers' real-time instruction of inquiry and how it can foster students to learn inquiry practices in real-time and transfer them to subsequent activities, thereby contributing to practical knowledge about how science inquiry is taught and learned.Unique to Inq-ITS is its ability to automatically assess inquiry using algorithms based on knowledge-engineering and data mining, making reliable alerting possible. By adding logging and timestamping to Inq-Blotter of every interaction a teacher has with its interface, the PIs will introduce the ability to capture and analyze teacher-student interactions on an extremely fine-grained scale, in turn allowing for maximum leverage of the algorithmic assessment capability of Inq-ITS. This combination of measuring students' inquiry practices in real-time at scale with a technological tool that facilitates real-time, targeted instruction could revolutionize how teachers interact with students during inquiry-based science instruction. The project will advance the state of the art of using a technology-based approach to close the formative assessment loop for the ill-defined domain of science inquiry. This research will also evince the broader principles surrounding this technological genre so as to guide the design of human-computer interfaces of other alerting tools for teachers and inform how learning-analytics techniques can best be utilized in such tools.

网络学习和未来学习技术计划为支持设想学习技术的未来并推进我们对人们如何在技术丰富的环境中学习的了解的努力提供资金。网络学习探索（EXP）项目设计和建立新的学习技术，以探索其可行性，了解有效使用它们的挑战，并研究其促进学习的潜力。该EXP项目解决了教师对实时诊断工具的需求，这些工具可以评估学生的需求，即提供形成性评估，以改善科学教学。该项目将扩展，试点，实施和研究Inq-Blotter，这是一个可扩展的，基于网络的警报系统，使教师能够对中学生的物理科学科学实践进行形成性评估，与新发布的国家框架下一代科学标准保持一致。Inq-Blotter警报系统将与Inq-ITS（探究智能辅导系统）结合使用，学生通过模拟进行探究来“展示他们所知道的”。学生提出问题、设计和进行实验、解释数据、用数据证明他们的主张并传达他们的发现。当学生工作时，他们通过Inq-ITS的算法进行实时评估。为了完成形成性评估循环，Inq-Blotter警报工具向教师的笔记本电脑和智能手机发送关于学生探究技能的真实的时间警报，以便教师知道谁最需要帮助以及需要哪些技能。将分析教师和学生之间的话语，以更好地了解该警报系统如何支持教师的实时探究指导，以及如何促进学生实时学习探究实践并将其转移到后续活动中，从而有助于关于如何教授和学习科学探究的实践知识。ITS是它使用基于知识工程和数据挖掘的算法自动评估查询的能力，使可靠的警报成为可能。通过为Inq-Blotter添加教师与其界面的每次交互的日志和时间戳，PI将引入在极细粒度范围内捕获和分析师生交互的能力，从而最大限度地利用Inq-ITS的算法评估能力。这种将实时测量学生的探究实践与促进实时、有针对性的教学的技术工具相结合的方法，可以彻底改变教师在探究式科学教学中与学生互动的方式。 该项目将推进使用基于技术的方法来关闭科学探究这一定义不清的领域的形成性评估循环的艺术水平。 这项研究还将表明围绕这一技术流派的更广泛的原则，以指导教师的其他警报工具的人机界面的设计，并告知如何学习分析技术可以最好地利用这些工具。