How to Assist Tutors to Rebuild Groups Within an ITS by Exploiting Traces. Case of a Closed Forum.

Salihoun, Mohammed; Guerouate, Fatima; Berbiche, Naoual; Sbihi, Mohamed

doi:10.3991/ijet.v12i03.6506

Cited by 9 publications

(11 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…• Formação de grupos -Neste tipo de estratégia, os usuários são alocados em grupos, designados para que seus integrantes sejam mais compatíveis e/ou complementares, facilitando as interações. Um mecanismo de formação automática de grupos em um sistema tutor inteligente, baseado no algoritmo de busca local 2-opt, foi abordado por Salihoun, Guerouate, Berbiche & Sbihi (2017), obtendo sucesso no incremento da participação no fórum. Maina et al (2017) desenvolveu uma solução de agrupamento com base no grau de colaboração, utilizando aprendizado de máquina e algoritmos kmédias e Expectation-maximization.…”

Section: Estratégias De Promoção Da Colaboraçãounclassified

Revisão Sistemática da Utilização de Fóruns Inteligentes para a Promoção da Colaboração na Aprendizagem Virtual

Mendes

Machiavelli

Gusmão

2019

RBIE

View full text Add to dashboard Cite

Os fóruns de discussão online são um tipo de atividade reconhecidamente importante para a promoção do intercâmbio de ideias e de construção de conhecimento colaborativo no contexto do ensino online. A ativa participação de seus integrantes torna-se, portanto, um requisito fundamental para que a aprendizagem se dê efetivamente, pois uma diversidade de conhecimentos interagindo sinergicamente resulta em uma rica base para quem a consulta, e, mais ainda, pode ser absorvida de maneira profunda por quem participa de sua construção. Na educação por meio virtual, também há que se considerar a importância que vêm ganhando as técnicas de Inteligência Artificial (IA), que possibilitam a extração de informações relevantes em ambientes que geram uma grande quantidade de dados, dificilmente tratados por técnicas da computação convencional. Assim, este trabalho visa investigar como a literatura tem reportado a utilização da IA para fomentar a participação em fóruns online, utilizados na aprendizagem virtual. Uma revisão sistemática foi feita e, apesar de inicialmente ter sido retornada uma grande quantidade de resultados, após uma análise mais detalhada, foram selecionados apenas 18 trabalhos de fato relacionados com o objetivo de pesquisa. Conclui-se, deste fato, que a IA ainda não está sendo amplamente usada na resolução do problema da participação em fóruns educacionais, o que sugere uma área de estudo potencialmente subutilizada, que, se bem explorada, pode fornecer uma contribuição importante para auxiliar na eficácia desta ferramenta.

show abstract

Section: Estratégias De Promoção Da Colaboraçãounclassified

Revisão Sistemática da Utilização de Fóruns Inteligentes para a Promoção da Colaboração na Aprendizagem Virtual

Mendes

Machiavelli

Gusmão

2019

RBIE

View full text Add to dashboard Cite

show abstract

“…In [4], authors gave an overview of proposed and implemented solutions showing that, in most cases, automatic grouping relies on probabilistic algorithms which employ a degree of randomness. In such approaches, the goal is not to find the best possible solution, but to find the approximation of the best solution [6], [7]. Examples are genetic algorithms [8] and those based on swarm intelligence [9].…”

Section: Grouping Algorithms In E-learning Systemsmentioning

confidence: 99%

“…Grouping algorithms are usually employed at the beginning of the e-tivity, but there are also approaches where they are used to rebuild groups during the e-tivity. For example, authors in [6] use the descent algorithm with the neighborhood of 2-opts to reconstruct the groups that are not homogeneous, according to the activity traces collected during the first part of the forum discussion.…”

Section: Grouping Algorithms In E-learning Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Implementation of Group Formation Algorithms in the ELARS Recommender System

Knez

Dlab

Hoić-Božić

2017

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

Abstract-Collaborative learning is recognized as an effective way of gaining knowledge in an online environment. Therefore, e-courses frequently include collaborative e-learning activities (e-tivities) that are performed in pairs or small groups of students. One of the challenges for teachers who organize e-tivities is the effective group forming. This paper presents algorithms that can be used to divide a set of students participating in an e-tivity to homogeneous or heterogeneous groups. The criterion for automatic group formation includes the following characteristics: the program of study, gender, learning styles preferences, Web 2.0 tools preferences, knowledge level and activity level. Designed algorithms were implemented in the educational recommender system ELARS and tested in the context of e-tivities.

show abstract

“…The constitution was done in an automatic manner according to our algorithm [33]. Each group will have an average following quantitative indicators that we have exploited.…”

Section: F the Reconstitution Of Groupsmentioning

confidence: 99%

A three-dimensional model that helps tutors to monitor groups during a collaborative online work

Salihoun¹,

Guerouate²,

Sbihi³

2017

IJET

View full text Add to dashboard Cite

Abstract-The E-Learning, model, based on learner's activity, can provide proof for competence assessment. Such models are the foundation for learning and teaching support, such as adaptation, assessment, competence analysis, recommendations and so on. This paper describes a method for analysing the learning processes that takes place in a computer-supported collaborative learning (CSCL) environment. Our approach is based on tracking the interactions between learners within groups and on a three-dimensional model that includes a participative, an interactive and an affective dimension. The exploitation of these traces can serve three main purposes: the evaluation of the quality of the process, the monitoring of student's performance in real time and the assessment of collaborative learning performances. In this study, the importance of a good climate of trust and affection in promoting teamwork is presented. In addition, a set of indicators is obtained by tracking course learner's behaviour within the learning environment. The findings of an empirical study of 14 work-based teams are discussed. The results can benefit to the tutor by providing him the opportunity to rebuild the working groups based on the stable and variable characteristics of learners.Keyword-E-learning, Traces, Indicators, Sociograms, Online collaborative work I. INTRODUCTION Usually, courses in online learning platforms are structured in various phases. In each phase, learners are required to engage in collaborative activities aimed at producing the work requested by their tutors. In order to do so, they will need to discuss, collaborate, negotiate meanings and finally reach an agreement in order to reify a shared product that is the expression of the group's achievements. However, tutors often struggle to track learners/groups progress or to detect learners/groups experiencing difficulties [1]. In order to have a deep understanding of the learning process, tutors are required to go beyond the surface level of interactions in order to understand the social and the cognitive processes involved. As computer conferencing systems usually record and maintain a history of the events occurring during the learning process, a wealth of information that can be analyzed is available.Several research studies over the last decades are leaning towards the track analysis in online learning environments. The main objective of this research is to guide tutors to interpret the learner's activities in elearning situations, by exploiting and analyzing the traces and providing knowledge on the activities, which we call learning indicators. These indicators help to understand and monitor learning in order to help tutors and offer them the opportunity to rebuild the working groups accusing difficulties based on the stable and variable characteristics of learners.Unfortunately, in our last study [1], some learners did not produce nothing due to an absence of a cohesion in the group. These include the problems of the affective dimension of learners, convergence proble...

show abstract

How to Assist Tutors to Rebuild Groups Within an ITS by Exploiting Traces. Case of a Closed Forum.

Cited by 9 publications

References 13 publications

Revisão Sistemática da Utilização de Fóruns Inteligentes para a Promoção da Colaboração na Aprendizagem Virtual

Revisão Sistemática da Utilização de Fóruns Inteligentes para a Promoção da Colaboração na Aprendizagem Virtual

Implementation of Group Formation Algorithms in the ELARS Recommender System

A three-dimensional model that helps tutors to monitor groups during a collaborative online work

Contact Info

Product

Resources

About