The Use of Multi-Agents' Systems in e-Learning Platforms

Orzechowski, Tomasz

doi:10.1109/sibcon.2007.371299

Cited by 11 publications

(6 citation statements)

References 6 publications

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“…Agent Based Search System (ABSS) relies on harvester agents to improve the quality of search query results [15]. The system is capable of not only harvesting heterogeneous remote learning object repositories, but also tracking changes in them.…”

Section: Related Workmentioning

confidence: 99%

HAPA: Harvester and Pedagogical Agents in E-learning Environments

Ivanović¹,

Mitrović²,

Budimac³

et al. 2015

INT J COMPUT COMMUN

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In the field of e-learning and tutoring systems two categories of software agents are of the special interest: harvester and pedagogical agents. This paper proposes a novel e-learning system that successfully combines both of these agent categories and introduces two distinct sub-types of pedagogical agents helpful and misleading. Whereas helpful agents provide the correct guidance for the given problem, misleading agents try to guide the learning process in the wrong direction by offering false hints and inadequate solutions. The rationale behind this approach is to motivate students not to trust the agent's instructions blindly, but to employ critical thinking. Consequently, students will be put in a "softly stressed" environment in order to prepare them for real working environments in their future work in companies. Nevertheless students themselves will decide on the correct solution to the problem in question.

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Section: Related Workmentioning

confidence: 99%

HAPA: Harvester and Pedagogical Agents in E-learning Environments

Ivanović¹,

Mitrović²,

Budimac³

et al. 2015

INT J COMPUT COMMUN

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“…The basic function is storing, managing and finding the data. Metadata and users accounts databases are key databases [37].…”

Section: Multi Agent Architecture For Intelligent E-learningmentioning

confidence: 99%

“…When the user is working agent its alive otherwise it becomes dead. Personal agent requests for search and find result [37].…”

Section: Multi Agent Architecture For Intelligent E-learningmentioning

confidence: 99%

Intelligent Agent Based Architectures for E-Learning System: Survey

Arif¹,

Hussain²

2015

IJUNESST

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“…The use of MAS in e-learning is not a new concept. Agents were proposed in many phases of learning, such as formative assessment [20], personal tutors [12,3], skill management [10], learning paths [7], personalised content search [19], communities for group collaboration [27,23], affective facilitation [5], and many more. Various applications in e-learning [15] and frameworks with MAS were also proposed [22,8,4].…”

Section: Institutionmentioning

confidence: 99%

Cloud e-Learning: A New Challenge for Multi-Agent Systems

Pireva

Kefalas²,

Dranidis³

et al. 2014

Advances in Intelligent Systems and Computing

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The developments of pedagogical models in e-learning together with the advances of learning technologies and cloud computing give us confidence to believe that the traditional e-learning will evolve into a process which will put the learner in the center of educational provision. In this paper, we propose Cloud e-Learning, a new approach to e-learning that will be open and learner-centered, it will allow personalisation, it will enhance self-motivation and collaboration. The learners should be able to choose what to learn, what sources to use, with and by whom, how and in what pace, what services and tools to use, how to be assessed, whether to get credits towards a degree etc. In such a dynamic and complex environment, the need for Multi-Agents Systems is necessary. Actors in Cloud e-Learning would need automated facilitation in all services involved. We outline few indicative scenaria for Cloud E-Learning and we explain how smart agents can act on behalf of the learners, teachers and institution in order to maximise the benefit of the proposed concept.

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The Use of Multi-Agents' Systems in e-Learning Platforms

Cited by 11 publications

References 6 publications

HAPA: Harvester and Pedagogical Agents in E-learning Environments

HAPA: Harvester and Pedagogical Agents in E-learning Environments

Intelligent Agent Based Architectures for E-Learning System: Survey

Cloud e-Learning: A New Challenge for Multi-Agent Systems

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