Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)

Detalhes bibliográficos
Autor(a) principal: Tozadore, Daniel Carnieto
Data de Publicação: 2020
Tipo de documento: Tese
Idioma: eng
Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
Texto Completo: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-31082020-093935/
Resumo: Artificial Intelligence (AI) has taken an important role in peoples routine. Mainly because it enables the automation of repetitive tasks and the customization of services for each user. Both of these resources are made possible by the knowledge that is created from data generated by past experiences. Especially in the educational field, AI can help teachers to optimize their working time in recurring actions of planning, executing and evaluating their activities. For students, AI can enhance the learning experience through interactive devices that, at first, increase students interest and motivation for being a novelty and then try to continue producing these effects in long-term interactions through techniques of adaptation and customization. However, one of the biggest problems is the lack of naturalness to use these techniques as allies. Based on the needs of teachers and students presented in literature, this project sought a way to meet these needs in a unique approach, proposing a computational architecture that communicates in an intuitive way with teachers through a graphical interface and with students through a social robot. The result is a Cognitive Adaptive System for Teaching and Learning (R-CASTLE). This system aims to enable AI algorithms as tools to assist teachers in planning, executing and evaluating their educational activities without having previously presented technical knowledge of these algorithms. At the same time, R-CASTLE offers the students a technological and challenging way to carry out practical exercises, at a level of difficulty corresponding to that presented by each of them. AI algorithms allow the robot to use visual and verbal communication to collect indicative values in students responses and body expressions to assess their attention, communication and learning skills. Further, it allows also to use this data in adapting and customizing the system in order to maintain students engaged for longer period of time in the activities. The graphical interface also provides easy ways to manipulate data generated from past activities to be modified and optimized for future activities. Although it is difficult to statistically evaluate the efficiency of this project as a whole due to the large amount of specialized data for this type of solution, studies with analyzes of isolated modules and initial tests of the complete system have pointed out optimistic indications about the potential of this tool to collaborate in a practical and intuitive way with students and teachers of elementary schools and also for those interested in using R-CASTLE in other tasks of Human-Robot Interaction.
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spelling Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)Sistema Cognitivo Adaptativo para Robótica Social Educacional (R- CASTLE)Adaptive systemsArtificial intelligence for educationHuman-robot interactionInteligência artificial para educaçãoInteração humano-robôRobótica socialSistemas adaptativosSocial roboticsArtificial Intelligence (AI) has taken an important role in peoples routine. Mainly because it enables the automation of repetitive tasks and the customization of services for each user. Both of these resources are made possible by the knowledge that is created from data generated by past experiences. Especially in the educational field, AI can help teachers to optimize their working time in recurring actions of planning, executing and evaluating their activities. For students, AI can enhance the learning experience through interactive devices that, at first, increase students interest and motivation for being a novelty and then try to continue producing these effects in long-term interactions through techniques of adaptation and customization. However, one of the biggest problems is the lack of naturalness to use these techniques as allies. Based on the needs of teachers and students presented in literature, this project sought a way to meet these needs in a unique approach, proposing a computational architecture that communicates in an intuitive way with teachers through a graphical interface and with students through a social robot. The result is a Cognitive Adaptive System for Teaching and Learning (R-CASTLE). This system aims to enable AI algorithms as tools to assist teachers in planning, executing and evaluating their educational activities without having previously presented technical knowledge of these algorithms. At the same time, R-CASTLE offers the students a technological and challenging way to carry out practical exercises, at a level of difficulty corresponding to that presented by each of them. AI algorithms allow the robot to use visual and verbal communication to collect indicative values in students responses and body expressions to assess their attention, communication and learning skills. Further, it allows also to use this data in adapting and customizing the system in order to maintain students engaged for longer period of time in the activities. The graphical interface also provides easy ways to manipulate data generated from past activities to be modified and optimized for future activities. Although it is difficult to statistically evaluate the efficiency of this project as a whole due to the large amount of specialized data for this type of solution, studies with analyzes of isolated modules and initial tests of the complete system have pointed out optimistic indications about the potential of this tool to collaborate in a practical and intuitive way with students and teachers of elementary schools and also for those interested in using R-CASTLE in other tasks of Human-Robot Interaction.A Inteligência Artificial (IA) tem assumido um papel importante na rotina das pessoas. Principalmente porque viabiliza a automação de tarefas repetitivas e a customização de serviços para cada usuário. Ambos recursos são possibilitados pelo conhecimento que se cria a partir de dados gerados por experiências passadas. Especialmente na área da educação, a IA pode ajudar os professores a otimizar seu tempo de trabalho em ações recorrentes de planejamento, execução e avaliação das atividades. Já para os alunos, a IA pode potencializar a experiência de aprendizado por meio de dispositivos interativos que, a princípio, aumentam o interesse e a motivação dos alunos por serem uma novidade e que tentam continuar produzindo esses efeitos a longo prazo por meio de técnicas de adaptação e customização. Entretanto, um dos maiores problemas é a falta de naturalidade para usar essas técnicas como aliadas. Baseado nas necessidades de professores e alunos apresentadas na literatura, este projeto buscou uma forma de atender tais necessidades em uma única abordagem, propondo uma arquitetura computacional que se comunique de uma maneira intuitiva com os professores por meio de uma interface gráfica e com os alunos por meio de um robô social. O resultado é um Sistema Cognitivo Adaptativo para Robótica Social Educacional (Robotic - Cognitive Adaptive System for Teaching an Learning - R-CASTLE). Este sistema tem como objetivo viabilizar algoritmos de IA como ferramentas de auxílio para os professores no planejamento, execução e avaliação de suas atividades educacionais sem que apresentem previamente conhecimentos técnicos desses algoritmos. Ao mesmo tempo, o R-CASTLE oferece para os alunos uma maneira tecnológica e desafiadora de realizar exercícios práticos, em um nível de dificuldade correspondente ao apresentado por cada um deles. Os algoritmos de IA permitem que o robô usar comunicação visual e verbal para coletar valores indicativos nas respostas e expressões corporais dos alunos para avaliar suas habilidades de Atenção, Comunicação e Aprendizagem. Além disso, permitem também usar esses dados na adaptação e customização do sistema a fim de manter os alunos engajados por mais tempo nas atividades. A interface gráfica também proporciona maneiras fáceis de manipular os dados gerados em atividades passadas para serem modificados e otimizados em atividades futuras. Embora seja difícil avaliar estatisticamente a eficiência deste projeto como um todo devido à grande quantidade de dados especializados para esse tipo de solução, estudos com análises dos módulos isolados e testes iniciais do sistema completo têm apontado bons indicativos sobre o potencial dessa ferramenta para colaborar de forma prática e intuitiva com alunos e professores do ensino fundamental e também para possíveis interessados em usar o R-CASTLE em outras tarefas de Interação Humano-Robô.Biblioteca Digitais de Teses e Dissertações da USPRomero, Roseli Aparecida FrancelinTozadore, Daniel Carnieto2020-05-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/55/55134/tde-31082020-093935/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2020-08-31T15:47:02Zoai:teses.usp.br:tde-31082020-093935Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212020-08-31T15:47:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
Sistema Cognitivo Adaptativo para Robótica Social Educacional (R- CASTLE)
title Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
spellingShingle Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
Tozadore, Daniel Carnieto
Adaptive systems
Artificial intelligence for education
Human-robot interaction
Inteligência artificial para educação
Interação humano-robô
Robótica social
Sistemas adaptativos
Social robotics
title_short Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
title_full Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
title_fullStr Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
title_full_unstemmed Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
title_sort Robotic - Cognitive Adaptive System for Teaching and Learning (R-CASTLE)
author Tozadore, Daniel Carnieto
author_facet Tozadore, Daniel Carnieto
author_role author
dc.contributor.none.fl_str_mv Romero, Roseli Aparecida Francelin
dc.contributor.author.fl_str_mv Tozadore, Daniel Carnieto
dc.subject.por.fl_str_mv Adaptive systems
Artificial intelligence for education
Human-robot interaction
Inteligência artificial para educação
Interação humano-robô
Robótica social
Sistemas adaptativos
Social robotics
topic Adaptive systems
Artificial intelligence for education
Human-robot interaction
Inteligência artificial para educação
Interação humano-robô
Robótica social
Sistemas adaptativos
Social robotics
description Artificial Intelligence (AI) has taken an important role in peoples routine. Mainly because it enables the automation of repetitive tasks and the customization of services for each user. Both of these resources are made possible by the knowledge that is created from data generated by past experiences. Especially in the educational field, AI can help teachers to optimize their working time in recurring actions of planning, executing and evaluating their activities. For students, AI can enhance the learning experience through interactive devices that, at first, increase students interest and motivation for being a novelty and then try to continue producing these effects in long-term interactions through techniques of adaptation and customization. However, one of the biggest problems is the lack of naturalness to use these techniques as allies. Based on the needs of teachers and students presented in literature, this project sought a way to meet these needs in a unique approach, proposing a computational architecture that communicates in an intuitive way with teachers through a graphical interface and with students through a social robot. The result is a Cognitive Adaptive System for Teaching and Learning (R-CASTLE). This system aims to enable AI algorithms as tools to assist teachers in planning, executing and evaluating their educational activities without having previously presented technical knowledge of these algorithms. At the same time, R-CASTLE offers the students a technological and challenging way to carry out practical exercises, at a level of difficulty corresponding to that presented by each of them. AI algorithms allow the robot to use visual and verbal communication to collect indicative values in students responses and body expressions to assess their attention, communication and learning skills. Further, it allows also to use this data in adapting and customizing the system in order to maintain students engaged for longer period of time in the activities. The graphical interface also provides easy ways to manipulate data generated from past activities to be modified and optimized for future activities. Although it is difficult to statistically evaluate the efficiency of this project as a whole due to the large amount of specialized data for this type of solution, studies with analyzes of isolated modules and initial tests of the complete system have pointed out optimistic indications about the potential of this tool to collaborate in a practical and intuitive way with students and teachers of elementary schools and also for those interested in using R-CASTLE in other tasks of Human-Robot Interaction.
publishDate 2020
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