586 research outputs found
The use of animated agents in e‐learning environments: an exploratory, interpretive case study
There is increasing interest in the use of animated agents in e‐learning environments. However, empirical investigations of their use in online education are limited. Our aim is to provide an empirically based framework for the development and evaluation of animated agents in e‐learning environments. Findings suggest a number of challenges, including the multiple dialogue models that animated agents will need to accommodate, the diverse range of roles that pedagogical animated agents can usefully support, the dichotomous relationship that emerges between these roles and that of the lecturer, and student perception of the degree of autonomy that can be afforded to animated agents
The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning
In this paper, we address the problem of creating believable agents (virtual
characters) in video games. We consider only one meaning of believability,
``giving the feeling of being controlled by a player'', and outline the problem
of its evaluation. We present several models for agents in games which can
produce believable behaviours, both from industry and research. For high level
of believability, learning and especially imitation learning seems to be the
way to go. We make a quick overview of different approaches to make video
games' agents learn from players. To conclude we propose a two-step method to
develop new models for believable agents. First we must find the criteria for
believability for our application and define an evaluation method. Then the
model and the learning algorithm can be designed
Adaptive Augmented Reality Serious Game to Foster Problem Solving Skills
This paper describes the design of an adaptive intelligent augmented reality serious game which aims to foster problem solving skills in young learners. Studies show that our students lack computational thinking skills in high school, which raises the need to establish new methods to develop these skills in our younger learners. We believe that problem solving skills are the fundamental skills of computational thinking and are critical for STEM, in addition to a broad range of other fields. Therefore we decided to focus on those meta-cognitive skills acquired to foster problem solving, such as strategic knowledge. The game described in this paper provides a unique adaptive learning environment that aims to develop learners’ meta-cognitive skills by utilizing augmented reality technology, believable pedagogical agents and intelligent tutoring modules. It offers a great user experience and entertainment which we hope will encourage learners to invest more time in the learning process. This paper describes the architecture and design of the game from the viewpoint of educational pedagogies and frameworks for serious game design
Orientações de design para Agentes Pedagógicos Animados
A área de agentes animados pedagógicos está
relacionada ao desenvolvimento de aplicações que visam
melhorar o processo de interação humano-computador
(por humanos queremos dizer estudantes e professores)
utilizando software de agentes representados por caracte-
res ou figuras humanas. A fim de ajudar os pesquisado-
res a projetar agentes pedagógicos que possam melhorar
a usabilidade do agente humano, este trabalho vai discutir
as diretrizes básicas para o design de Agentes Animados
Pedagógicos, com base nos conceitos fornecidos pela In-
formática na Educação, Inteligência Artificial e Interação
Humano-Computador
Intelligent Agents: A Physics Education Opportunity in Latin-America
Intelligent Agents are being applied in a wide range of processes and
everyday applications. Their development is not new, in recent years they have
had an increased attention and design in learning and as mentoring tools. In
this paper we discuss the definition of what an intelligent agent is; how they
are applied; how thy look like; recent implementations of agents; agents as
support in learning process; their state in Latin-American countries and future
developments and trends that will permit a better communication between people
and agents.Comment: 6 page
Inferring Peer-Related Emotions in a Collaborative Learning Game
Este artigo apresenta um modelo afetivo para inferir emoções do aluno em um jogo de aprendizagem colaborativa. O modelo é focado na representação e reconhecimento de emoções vinculadas a uma dinâmica de colaboração (tais como orgulho, vergonha, admiração e reprovação). O modelo emprega uma abordagem cognitiva em que as emoções do aluno são representadas e inferidas pela representação da avaliação cognitiva que o aluno faz sobre a “louvabilidade” das interações colaborativas durante o jogo, de acordo com suas expectativas de padrões comportamentais. O modelo afetivo do aluno se apóia em Redes Bayesianas, através das quais são mapeadas dependências causais entre traços da personalidade, objetivos, padrões comportamentais, interações e emoções do aluno. Um jogo colaborativo que suporta mecanismos simples de interação foi implementado como protótipo de teste. Ao fazer uso deste jogo, alunos podem construir soluções compartilhadas de uma classe de problemas lógicos. As variáveis afetivas e cognitivas do modelo e suas relações probabilísticas são detalhadas e a captura de evidências da interação a partir do jogo protótipo é discutida
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