Collaborative Research: Multimodal Affective Pedagogical Agents for Different Types of Learners

协作研究：针对不同类型学习者的多模式情感教学代理

基本信息

批准号：
1821894
负责人：
Nicoletta Adamo-Villani
金额：
$ 49.88万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2023-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1821894&HistoricalAwards=false
关键词：
Collaborative Research Multimodal Affective Pedagogical

项目摘要

While most research on embodied pedagogical agents (adaptive virtual agents that guide and mentor learners) explores cognitive features, this project investigates the role of agent affect/emotion. This project examines how the agent's affective state (e.g., seeming interested or concerned) impacts different types of students (e.g., differing by knowledge level, gender, underrepresented group status, interest in STEM fields, and personality profile) when learning from online statistics lessons. The project integrates several areas of research: a) computer graphics research on life-like and believable representation of emotion in embodied agents, b) advanced methods and techniques from artificial intelligence and computer vision for real-time recognition of emotions, c) cognitive psychology research on learning from affective agents, and d) education research on the efficacy of affective agents for improving student learning of STEM concepts. Through experimental research the project will advance the state of the art in agent design and implementation by integrating findings on effective emotion regulation with algorithms that support life-like expression of emotions in embodied agents. To investigate the multimodal design features of affective pedagogical agents, the project has two main objectives: (1) research and develop novel algorithms for emotion recognition and for life-like emotion representation in embodied animated agents, and (2) develop an empirically grounded research base to guide the design of affective pedagogical agents for different types of learners. In one series of experiments the project will determine evidence-based design principles to guide the development of agents that demonstrate emotion/affect, including which kinds of affective states are most effective for which kinds of learners. In a second series of experiments, the project will implement a web-camera system to detect the emotional state of the learner (e.g., confused, interested, content, or bored), adapting the emotional state displayed by the agent in response. Of interest is whether students learn the statistics lesson better when the pedagogical agent is sensitive to the learner's emotional state than when it is not. In addition to its scientific merit, the project will develop and make available a toolkit of affective animated pedagogical agents that adapt to learner characteristics to be used by learners of all ages, for education and training in a variety of subject matters and settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

虽然大多数关于具体教学代理（指导和辅导学习者的自适应虚拟代理）的研究都探索认知特征，但该项目研究代理情感/情感的作用。该项目研究在学习在线统计课程时，代理人的情感状态（例如，看起来感兴趣或关心）如何影响不同类型的学生（例如，因知识水平、性别、代表性不足的群体状态、对 STEM 领域的兴趣和个性特征而不同）。该项目整合了多个研究领域：a）对具体主体中逼真且可信的情感表示的计算机图形学研究，b）来自人工智能和计算机视觉的先进方法和技术，用于实时识别情感，c）认知心理学关于情感因素学习的研究，以及 d) 关于情感因素对于改善学生 STEM 概念学习的功效的教育研究。通过实验研究，该项目将通过将有效情绪调节的发现与支持具体代理逼真的情感表达的算法相结合，推进代理设计和实施的最先进水平。为了研究情感教学代理的多模态设计特征，该项目有两个主要目标：（1）研究和开发用于情感识别和具体动画代理中逼真的情感表示的新颖算法，以及（2）开展基于经验的研究指导针对不同类型学习者设计情感教学媒介的基础。在一系列实验中，该项目将确定基于证据的设计原则，以指导展示情感/情感的代理的开发，包括哪种情感状态对哪种类型的学习者最有效。在第二系列实验中，该项目将实现一个网络摄像头系统来检测学习者的情绪状态（例如，困惑、感兴趣、内容或无聊），从而调整代理所显示的情绪状态作为响应。有趣的是，当教学人员对学习者的情绪状态敏感时，学生是否能比不敏感时更好地学习统计课程。除了其科学价值外，该项目还将开发并提供一个情感动画教学代理工具包，该工具包适应学习者的特点，供所有年龄段的学习者使用，用于各种主题和环境的教育和培训。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。