Collaborative Research: Using Data Mining and Observation to derive an enhanced theory of SRL in Science learning environments

协作研究：利用数据挖掘和观察得出科学学习环境中 SRL 的增强理论

• 批准号: 1561676
• 负责人: Gautam Biswas
• 金额: $ 62.96万
• 依托单位: Vanderbilt University
• 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 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1561676&HistoricalAwards=false
• 关键词: Collaborative; Research; Using; Data; Mining

This project aims to enhance theory and measurement of students' self-regulated learning (SRL) processes during science learning. SRL refers to learning that is guided by metacognition (thinking about one's thinking), strategic action (planning, monitoring, and evaluating personal progress against a standard), and motivation to learn. The project will accomplish this by developing a technology-based framework which leverages human expert judgment and machine learning methods to identify key moments during SRL and analyze these moments in depth. The project uses an existing science learning environment, Betty's Brain, that combines learning-by-modeling with critical thinking and problem solving skills to teach complex science topics. The environment is designed to have the student teach Betty science topics using concept maps (the critical elements of the science) and reading materials provided by the environment. A critical component of this project is to determine when a student using the system needs help. Using SRL as a basis, the additions to Betty's brain will identify key points in the SRL processes of metacognition, strategic action, and motivation. Some of these points can be determined automatically in recognizing key points while others require human intervention to recognize key points and then to determine what actions should be taken to enable the student. This information will be recorded and the experiences then are used to update the automatic identification of key points.The project's main intellectual merit is in integrating the power of data mining to rapidly sift through large amounts of data to find key inflection or change points in student reasoning and strategies, with the power of human beings to deeply understand other humans' SRL processes. This measurement framework, with the accompanying detectors of inflection points in students' SRL in online learning, has the potential to transform science learning and teaching in K-12 settings by providing insights into how SRL unfolds during learning through the interactions between affect, engagement, cognition and metacognition. Those insights will be used to extend an existing theory of SRL, increasing its richness, specificity, and predictive power. Self-regulated learning is important to student success, both in K-12 education and during life-long learning afterwards. Better understanding of SRL processes will support the development of computer-based science learning environments, such as Betty's Brain, with the capability to better support students' learning of SRL skills and strategies in science classrooms. By studying these issues within the diverse population of urban students who currently use Betty's Brain, success of the project will increase the relevance of SRL to the full diversity of America's learners. The project's software will be available through the portal www.teachableagents.org.

本项目旨在加强对学生在科学学习过程中自我调节学习过程的理论和测量。SRL是指在元认知(思考一个人的思维)、战略行动(对照标准规划、监测和评估个人进步)和学习动机的指导下进行的学习。该项目将通过开发一个基于技术的框架来实现这一点，该框架利用人类的专家判断和机器学习方法来识别SRL期间的关键时刻，并深入分析这些时刻。该项目使用了现有的科学学习环境--贝蒂的大脑，该环境将建模学习与批判性思维和解决问题的技能相结合，教授复杂的科学主题。该环境旨在让学生使用概念图(科学的关键要素)和环境提供的阅读材料来教授Betty科学主题。这个项目的一个关键组成部分是确定使用该系统的学生何时需要帮助。使用SRL作为基础，Betty大脑中的新成员将识别SRL过程中元认知、战略行动和动机的关键点。其中一些点可以在识别关键点时自动确定，而另一些点则需要人工干预来识别关键点，然后确定应该采取什么行动来使学生能够。这些信息将被记录下来，然后这些经验将被用于更新关键点的自动识别。该项目的主要智力优势是将数据挖掘的能力与人类深入理解其他人的SRL过程的能力相结合，数据挖掘的能力可以快速筛选大量数据，以找到学生推理和策略中的关键转折点或变化点。这一测量框架与在线学习中学生SRL拐点的相应检测器一起，通过提供关于SRL在学习过程中如何通过情感、参与、认知和元认知之间的交互作用展开的洞察，有可能改变K-12环境下的科学学习和教学。这些见解将被用来扩展现有的SRL理论，增加其丰富性、特异性和预测能力。自我调节学习对学生的成功非常重要，无论是在K-12教育中，还是在以后的终身学习中。更好地理解SRL过程将支持基于计算机的科学学习环境的发展，例如Betty的大脑，能够更好地支持学生在科学课堂上学习SRL技能和策略。通过在目前使用贝蒂大脑的不同城市学生群体中研究这些问题，该项目的成功将增加SRL与美国学习者的全面多样性的相关性。该项目的软件将通过门户网站www.teachableagents.org获得。