摘要
智能教育机器人正处于发展初级阶段,面临着教学性不足、反馈性差、感知力欠缺等诸多问题。本研究基于人工智能领域的多项关键支撑技术,采用经典心理学的自我决定理论作为理论基础,设计并实现了“智慧学伴”智能教育机器人的系统架构。本研究首先基于知识图谱技术构建了教育认知地图,基于机器学习技术构建了学习者模型,基于自然语言处理技术构建了问答与对话系统,利用情感计算技术估计学习者的学习情绪和专注度等关键状态信息。在此基础上,本研究针对家庭教育与环境的特点,设计了五类典型的智能机器人应用模式,以帮助学习者完成不同阶段的学习目标,并满足其自主感、胜任感及归属感等核心需求。本研究将有助于人工智能技术与教育机器人领域的融合与发展。
The fast development of educational robots still stays in its initial stage,and currently,it faces many challenges,typically including lack of teaching,feedback,and sensing capabilities.Driven by the latest artificial intelligence(AI)technologies and the self-determination theory from the classic psychological domain,we design and implement an intelligent educational robot,called“smart learning partner.”Specifically,we adopt knowledge graph to design the educational cognitive map,machine learning to model the learner,natural language processing to construct question-answering and conversational agents,and affective computing to estimate learners'emotion and engagement status.Furthermore,we define five typical application scenarios for the robot to help learners in the family environment,and meanwhile satisfy learners'needs of autonomy,competence,and relatedness.The outcome of this study would benefit the interdisciplinary research involving both AI and educational robot domains.
作者
卢宇
薛天琪
陈鹏鹤
余胜泉
LU Yu;XUE Tianqi;CHEN Penghe;YU Shengquan(Advanced Innovation Center for Future Education,Beijing Normal University,Beijing 100875,China;School of Educational Technology,Faculty of Education,Beijing Normal University,Beijing100875,China)
出处
《开放教育研究》
CSSCI
北大核心
2020年第2期83-91,共9页
Open Education Research
基金
教育部人文社会科学研究青年基金项目(17YJCZH116)
国家自然科学基金青年科学基金项目(61702039,61807003)。
关键词
教育机器人
知识图谱
学习者建模
机器学习
自然语言处理
情感计算
educational robot
knowledge graph
student model
machine learning
natural language processing
affective computing