Multi-Agent Systems: A Survey.

This paper explores the possibility of implementing a constructivist learning environment using chatbot technology as a basis of enabling students acquire global economy and technological information age skills and competencies (21 st century skills) within the context of a developing country. The suggested approach is to integrate chatbot technology into the prevailing teaching-learning environment taking into consideration enabling and constraining factors. Social constructivism provides the basis for concretization of this approach, where social interaction plays a fundamental role in the development of cognition, with mediation using cultural tools and scaffolding contributing to the process of learning.

Chatbot technology: A possible means of unlocking student potential to learn how to learn

Feedback is an essential component of scaffolding for learning. Feedback provides insights into the assistance of learners in terms of achieving learning goals and improving self-regulated skills. In online courses, feedback becomes even more critical since instructors and students are separated geographically and physically. In this context, feedback allows the instructor to customize learning content according to the students' needs. However, giving feedback is a challenging task for instructors, especially in contexts of large cohorts. As a result, several automatic feedback systems have been proposed to reduce the workload on the part of the instructor. Although these systems have started gaining research attention, there have been limited studies that systematically analyze the progress achieved so far as reported in the literature. Thus, this article presents a systematic literature review on automatic feedback generation in learning management systems. The main findings of this review are: (1) 65.07% of the studies demonstrate that automatic feedback increases student performance in activities; (2) 46.03% of the studies demonstrated that there is no evidence that automatic feedback eases instructors’ workload; (3) 82.53% of the studies showed that there is no evidence that manual feedback is more efficient than automatic feedback; and (4) the main method used for automatic feedback provision is the comparison with a desired answer in some subject (such as logic circuits or programming).

Automatic feedback in online learning environments: A systematic literature review

As the development of online learning is growing, a large amount of log data on student activity is available and accumulated in Learning Management Systems (LMS) This massive volume of data can be analysed in order to discover hidden information about students' learning behaviours and, in particular, to identify at-risk students and to advise instructors to provide additional assistance and interventions to help those who are at risk, to increase retention rates As a result, Learning Analytics (LA) has emerged, which aims to measure, analyse and report students' learning behaviours using data analytics techniques In this regard, this paper aims to provide an overview of how at-risk students are identified or predicted by analysing their learning behaviours in online learning, including the types of data and tools or analytics methods used The findings indicate that most of the data analytics techniques have successfully identified and predicted at-risk students and various types of data are determined as attributes in predicting at-risk students Finally, further research should be conducted to identify and predict at-risk students, since there are diverse students in online learning who have different demands, and interventions should be developed to tackle the problems faced by at-risk students in order to enhance their learning performances

Identifying at-risk students in online learning by analysing learning behaviour: A systematic review

Online discussion forums are asynchronous communication tools that are widely used in Learning Management Systems. However, instructors and students face various difficulties, and instructors lack a guide on what strategies they can use to achieve a more participatory forum environment. This work aims to identify benefits and difficulties of using online discussion forums from the instructors’ point of view, and to provide a list of strategies and improvements that can mitigate the challenges and lead to a more participatory forum. We used coding procedures to analyze data collected through semi-structured interviews. The results of our exploratory analysis are relevant to the distance learning community and can inform instructors, developers, and researchers to help them improve the quality of mediation and use of forums.

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What to expect, and how to improve online discussion forums: the instructors’ perspective

The large number of messages posted on the forum, a key element in Distance Education Courses based on Virtual Learning Environment, which does not receive adequate feedback from the tutor in sufficient time is a typical problem faced by students in these environments. The tutors, in turn, feel a lack of tools to monitor activities carried out by the student. This article proposes an approach for solving these problems based on the concept of perception, using the multiagent system paradigm. The system is composed by intelligent agents, which act in a Moodle discussion forum using an AIML knowledge base. Agents solve questions about matters discussed at the forum, and they use perception to recommend the implementation of activities that the student has not done. The results from simulations based on real courses already completed show that there is a decrease in the workload of tutors. Students are reminded the deadline for the tasks automatically. It was necessary to create hundreds of AIML rules to get answers to good level. The partial results indicate that the approach of combining AIML and MAS is promising to improve the feedback from tutors and motivate students to conclude their work on time.

Improving cooperation in Virtual Learning Environments using multi-agent systems and AIML

With the widespread use of Virtual Learning Environments (VLE) in various educational institutions, usually in education courses distance, the task of monitoring the activities of students per guardians and mediators to achieve levels of quality have been a increasing work. To follow up the students in these new technologies require new thinking and attitudes of educators in these environments and new solutions by the designers of this class of systems. This paper describes architectures based on Multiagent Systems, focused on the concept of perception, designed to assist students and tutors on completion and monitoring of activities in distance education courses Resumo. Com a disseminacao do uso de Ambientes Virtuais de Aprendizagem (AVA) por diversas instituicoes de ensino, notadamente em cursos de Educacao a Distância, a tarefa de acompanhamento das atividades dos alunos por tutores e mediadores para atingir niveis de qualidade tem sido um trabalho cada vez maior. Realizar o acompanhamento dos alunos nessas novas tecnologias, requerer novas reflexoes e posturas de educadores nestes ambientes e novas solucoes por parte dos projetistas desta classe de sistemas. Este Artigo descreve arquiteturas baseadas em Sistemas Multiagente, focadas no conceito de percepcao, criadas para auxiliar alunos e tutores na conclusao e acompanhamento de atividades em cursos de Educacao a Distância.

Sistema Multiagente para Apoiar a Percepção e o Acompanhamento de Atividades em Ambientes Virtuais de Aprendizagem

With the spread of information technologies and communication, the creation and use of intelligent systems have contributed to the social and digital inclusion and promoting citizenship of people. Children with hearing loss need to be inserted in early learning in signs in Brazilian Sign Language(LIBRAS). This paper describes ELRA application that uses Augmented Reality in the teaching-learning of LIBRAS. The application is under development and explores 3D objects to help children, mediated by technology.

ELRA - Teaching Brazilian Sign Language Using Augmented Reality

A ampliacao do acesso a Internet e a difusao de kits roboticos de menor custo tem possibilitado a Robotica Educacional, aplicacoes a distância usando o conceito de Telerobotica. Este artigo descreve um Ambiente Telerobotico Educacional baseado em Sistemas Multiagente que foi desenvolvido utilizando a metodologia MaSE. Suas funcionalidades foram testadas com resultados promissores. O sistema possibilita a selecao de cenarios associados a desafios distintos, de acordo com os niveis de habilidade do usuario. A abordagem apresenta avancos sobre os sistemas teleroboticos encontrados na literatura, pois permite flexiblidade na ativacao de cenarios variados e uma interacao usuario-sistema utilizando agentes.

Arcabouço de um Ambiente Telerobótico Educacional Baseado em Sistemas Multiagente

A common problem in Virtual Learning Environments is the difficult task to monitor students activities and the lack of feedback from the tutor. Use of new technologies to perform the tracking of students in virtual environments can bring great results, facilitating the work students and teachers This paper presents TUCUMA, an 3D Intelligent Virtual Agent integrated into an Environment Virtual Learning Moodle. It works as a distance learning course tutor, monitoring students activities, removing doubts of the students through dialog. The avatar is composed of MultiAgent System responsible for producing gestures and monitoring students activities.

Márcio Aurélio dos Santos Alencar

Papers

Improving cooperation in Virtual Learning Environments using multi-agent systems and AIML

Sistema Multiagente para Apoiar a Percepção e o Acompanhamento de Atividades em Ambientes Virtuais de Aprendizagem

ELRA - Teaching Brazilian Sign Language Using Augmented Reality

Arcabouço de um Ambiente Telerobótico Educacional Baseado em Sistemas Multiagente

TUtor Collaborator Using Multi-Agent System