Microgenetic Learning Analytics

微观遗传学习分析

• 批准号: 1252350
• 负责人: Florence Sullivan
• 金额: $ 30.09万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1252350&HistoricalAwards=false
• 关键词: Microgenetic; Learning; Analytics

Research activities that will be undertaken in this project are:(1) the development of theoretically-based, microgenetic learning analytic protocols aimed at understanding middle school student learning in a robotics setting as well as the development of theoretically-based, sentiment analysis protocols aimed at understanding the salience of stereotype threat for underrepresented students studying in a robotics context; (2) pilot testing these protocols on an existing data set; (3) refining and improving the protocols based on the results of the pilot test; and (4) conducting original research on the development of computational thinking in underrepresented middle school students studying in a robotics context, including examining the salience of stereotype threat on student activity. Microgenetic analysis refers to the study of learning changes where:1. Observations span the period of rapidly changing competency2. Within the this period the density of observations is high relative to the rate of change3. Observations are analyzed intensivelyThis proposal combines microgenetic analysis with computer science based learning analytics. The computer science based learning analytics take computer captured data and analyzes and mines that data for understanding of student learning. It is frequently used in intelligent tutoring systems and Massive Open Online Courses. In such cases, every keystroke is captured and the learning analytics is about making sense of those captured keystrokes.The goal of this FIRE proposal is to increase the diversity of individuals who enter the field of computing by engaging in research on the development of computational thinking in underrepresented middle school students as they interact in a robotics environment. This research will include an examination of the salience of stereotype threat in an all girl robotics study setting. The PIs will achieve this project goal through the creation of a new research method that combines microgenetic analysis techniques derived from the field of developmental psychology with learning analytic techniques, derived from the field of computer science. The PIs term this new method Microgenetic Learning Analytics.

该项目将开展的研究活动是：（1）开发基于理论的微观学习分析协议，旨在了解中学生在机器人环境中的学习，以及开发基于理论的情感分析协议，旨在了解在机器人环境中学习的代表性不足的学生的刻板印象威胁的显着性;（2）在现有数据集上对这些协议进行试点测试;（3）根据试点测试的结果改进和改进协议;以及（4）对在机器人背景下学习的代表性不足的中学生的计算思维的发展进行原创性研究，包括检查刻板印象威胁对学生活动的显着性。微观发生分析是指学习变化的研究，其中：1。观察跨越能力迅速变化的时期2。在这段时间内，观测密度相对于变化率是高的3。该提案将微观遗传分析与基于计算机科学的学习分析相结合。基于计算机科学的学习分析采用计算机捕获的数据，并分析和挖掘这些数据，以了解学生的学习。它经常用于智能教学系统和大规模开放式在线课程。在这种情况下，每个学习者都被捕获，学习分析是关于理解这些捕获的学习者的。这个FIRE提案的目标是通过参与研究在机器人环境中互动时，代表性不足的中学生的计算思维发展来增加进入计算领域的个人的多样性。这项研究将包括在所有女孩机器人研究设置的刻板印象威胁的显着性检查。PI将通过创建一种新的研究方法来实现这一项目目标，该方法将来自发展心理学领域的微观分析技术与来自计算机科学领域的学习分析技术相结合。PI将这种新方法称为微观遗传学习分析。