Deeper modeling via affective meta-tutoring

通过情感元辅导进行更深入的建模

• 批准号: 0910221
• 负责人: Kurt VanLehn
• 金额: $ 94.79万
• 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: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0910221&HistoricalAwards=false
• 关键词: Deeper; modeling; via; affective; meta

The studies address through investigation of students in Arizona High School summer programs how students learn, understand and manipulate scientific models of the carbon cycle and the water cycle. The investigators of this project have identified problems that on-line tutors have with creating conditions for students to regulate their own behavior. Instead of taking advantage of the available learning opportunities, some students ask for hints until the tutor gives them the correct answer. The investigators hypothesize that lasting benefits require changing students beliefs about shallow compared with deep modeling practices and breaking their modeling habits and instilling new ones. They intend to add affective learning companions to the on-line tutors. The modules use the teachable agent metaphor called Betty's Brain. The study analysis will be conducted in high school summer schools in Arizona for students that are mostly Native Americans. The students are self-selected for attending the summer school. Data collection will include student logs, verbal protocols and affect sensor data from the summer school participants (approximately 30 students). Three studies will be conducted: 1. to develop a meta tutoring tool, 2. to develop an affective learning agent with verbal and physical gestures, and 3. a measure of whether the new tool results in increases in learning. The analysis will involve causal inference and data mining of student records of their activities. The third phase of the learning will compare students who use one agent with the teachable agent; a second group will compare two agents, the teachable agent and the meta-tutor; and a third group will compare three agents. The outcome of the study is a developed and tested tool to increase student learning and statistical analysis of records maintained by the investigators of student activities with the teachable agent. The study should help indicate whether computer tutors are more effective if they have integrated features that mimic human performance.

这些研究通过对亚利桑那州高中暑期项目的学生进行调查，探讨了学生如何学习、理解和操纵碳循环和水循环的科学模型。该项目的研究人员发现了在线导师在为学生规范自己行为创造条件方面存在的问题。有些学生没有利用现有的学习机会，而是寻求提示，直到导师给他们正确的答案。研究人员假设，要获得持久的好处，就需要改变学生对浅层建模实践与深度建模实践的看法，并打破他们的建模习惯并灌输新的建模习惯。 他们打算在在线导师的基础上增加情感学习伙伴。 这些模块使用称为“贝蒂大脑”的可教学代理隐喻。该研究分析将在亚利桑那州的高中暑期学校进行，学生主要是美国原住民。 学生自行选择参加暑期学校。 数据收集将包括学生日志、口头协议以及来自暑期学校参与者（约 30 名学生）的影响传感器数据。 将进行三项研究：1. 开发元辅导工具，2. 开发具有言语和身体手势的情感学习代理，以及 3. 衡量新工具是否会提高学习效果。 分析将涉及学生活动记录的因果推理和数据挖掘。 学习的第三阶段将比较使用一种代理的学生与可教代理的学生；第二组将比较两个智能体，可教智能体和元导师；第三组将比较三个代理。 该研究的结果是一个开发和测试的工具，可以提高学生的学习能力，并对调查人员与可教代理一起维护的学生活动记录进行统计分析。 这项研究应该有助于表明，如果计算机辅导员具有模仿人类表现的综合功能，它们是否会更有效。