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EXP: Augmenting a Teachable Robot with Adaptive Cognitive and Social Support

EXP：通过自适应认知和社交支持增强可教机器人

基本信息

批准号：
1735909
负责人：
Winslow Burleson
金额：
$ 74.98万
依托单位：
New York University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2020-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735909&HistoricalAwards=false
关键词：
EXP Augmenting Teachable Robot Adaptive

项目摘要

This proposal investigates robotic teachable agents, a type of cyberlearning technology that provides cognitive and affective feedback to support students' learning. The Tangible Activities for Geometry system (TAG) is a robotic teachable agent platform for middle school mathematics and computational thinking. Students physically engage within a projected coordinate space with an interactive teachable robot named Quinn. Students teach Quinn how to solve challenges involving plotting points on a graph, translating points, rotating points, and plotting lines by giving procedural and conditional instructions to Quinn. There appear to be at least two primary advantages to using a robotic learning platform to investigate how to design teachable agents. First, a physical presence, provided by a robotic agent, strengthens users' perceptions of having a social partner that is more than a virtual agent. Second, students receive cognitive benefits from learning through embodied, physical interactions. This research investigates the unique affordances of a teachable robot for supporting students' cognitive and social interactions within a learning environment as it enhances our understanding of how cyberlearning can support STEM learning (mathematics and computational thinking). The study will be conducted in a school system having high percentages of underrepresented minorities who will learn to design features of the robots, exposing them to STEM careers and increasing the likelihood of acceptance and scalability. The investigative team will also disseminate findings and Do-It-Yourself (DIY) instructions for integrating cyberlearning environments and pedagogical approaches.This proposal advances an empirical investigation that uses a teachable robot learning environment built with prior NSF support, integrated within the NYU Holodeck, a state-of-the-art immersive collaborative cyberlearning research environment, to improve understanding of how adaptive cognitive and social support can facilitate embodied interactions with teachable agents. This project investigates the teachable agent phenomenon within the context of the Tangible Activities for Geometry system (TAG), a robotic teachable agent platform for middle school mathematics and computational thinking. The project has three phases. First, the research team will explore two factors related to cognitive support: (1) how the teachable agent can give adaptive feedback representative of a learner (questions, self-explanations) rather than a tutor (hints, instructional explanations), and (2) how cognitive prompts can leverage the physical properties of the environment. Second, the team will explore two factors related to social support: (a) how a teachable agent can make adaptive attributions to effort or ability for its success or failure to motivate students, and (b) how the robot can use its embodied presence (physical or tactile) to contribute social information to enhance student learning. Third, to assess the efficacy of the interventions, the project incorporates a study comparing cognitive and social support to a condition with only cognitive support, only social support, and with no support. The project will make substantial contributions toward better understanding how to design and effectively incorporate support, provided by a teachable robot, to adaptively provide cognitive and social support to improve student outcomes. The robot framework will be tested in schools, including high percentages of underrepresented minorities, developing new ways of using technology to learn mathematics and computational thinking.

该提案研究机器人可教学代理，这是一种网络学习技术，提供认知和情感反馈来支持学生的学习。几何活动系统（TAG）是一个面向中学数学和计算思维的机器人教学代理平台。学生们在投影坐标空间内与一个名为Quinn的交互式可教学机器人进行物理接触。学生教奎因如何解决涉及绘制点的图形，翻译点，旋转点，并通过给奎因程序和条件指令绘制线的挑战。使用机器人学习平台来研究如何设计可教代理似乎至少有两个主要优势。首先，由机器人代理提供的物理存在，加强了用户对拥有比虚拟代理更多的社交伙伴的感知。第二，学生通过具体的身体互动从学习中获得认知益处。这项研究调查了可教机器人在学习环境中支持学生认知和社交互动的独特功能，因为它增强了我们对网络学习如何支持STEM学习（数学和计算思维）的理解。该研究将在一个拥有高比例代表性不足的少数民族的学校系统中进行，他们将学习设计机器人的功能，使他们接触STEM职业，并增加接受和可扩展性的可能性。调查小组还将传播研究结果和DIY（DIY）指导，以整合网络学习环境和教学方法。该提案提出了一项实证调查，使用在NSF支持下构建的可教机器人学习环境，集成在纽约大学Holodeck中，这是一个最先进的沉浸式协作网络学习研究环境，提高对适应性认知和社会支持如何促进与可教代理的具体互动的理解。本项目研究了可教代理现象的背景下的TDERIGHT活动几何系统（TAG），机器人可教代理平台，中学数学和计算思维。该项目分三个阶段。首先，研究小组将探讨与认知支持相关的两个因素：（1）可教代理如何提供代表学习者（问题，自我解释）而不是导师（提示，指导性解释）的自适应反馈，以及（2）认知提示如何利用环境的物理特性。第二，研究小组将探讨与社会支持相关的两个因素：（a）可教代理如何对其成功或失败的努力或能力进行自适应归因以激励学生，以及（B）机器人如何使用其具体存在（物理或触觉）来贡献社会信息以增强学生的学习。第三，为了评估干预措施的有效性，该项目纳入了一项研究，将认知和社会支持与只有认知支持、只有社会支持和没有支持的情况进行比较。该项目将为更好地理解如何设计和有效地整合可教机器人提供的支持做出重大贡献，以自适应地提供认知和社会支持，以提高学生的成绩。机器人框架将在学校进行测试，包括高比例的代表性不足的少数民族，开发利用技术学习数学和计算思维的新方法。