Towards integrating semantics of multi-media resources and processes in e-Learning

Huang, Weihong; Eze, Emmanuel; Webster, David E.

doi:10.1007/s00530-005-0009-6

Cited by 10 publications

(6 citation statements)

References 25 publications

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“…Some researchers have proposed agent‐based e‐learning systems (e.g. Huang et al , 2006a, b); however, the agent‐based systems currently being proposed do not support all aspects of e‐learning.…”

Section: Learning Support Systems and Agentsmentioning

confidence: 99%

“…Abasolo and Gomez, 2000; Cazalens et al , 2000; Gregg and Walczak, 2007; Rhodes and Maes, 2000; Tan et al , 2002; Walczak, 2003). However, resource location agents need to allow semantic searches of online content to facilitate discovery of appropriate materials based on the conceptual meaning of the subject material (Huang et al , 2006a, b; Shafrir and Etkind, 2006). The main processes that are involved in semantic information retrieval include (Korfbage, 1997):a querying process, where the user specifies the types of information to be located using natural language or terms connected by Boolean operators;an indexing process, where a document representation is created based on semantic web metadata and word usage; andan evaluation process, were a matching between the user query and the document representation is performed using concept parsing algorithms (a generic semantic procedure that identifies the lexical labels and building blocks of concepts) (Shafrir and Etkind, 2006) or ontology mappings (Gašević and Hatala, 2006).…”

Section: E‐learning Agentsmentioning

confidence: 99%

“…improved learning outcomes) (Heinström, 2000; Leidner and Jarvenpaa, 1995; Bovy, 1981; Wilson, 2000). Personalization agents can be used to create a personalized learning model and pathway tailored to individual learner knowledge and personality traits (Huang et al , 2006a, b).…”

Section: E‐learning Agentsmentioning

confidence: 99%

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E‐learning agents

Gregg

2007

The Learning Organization

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Purpose-The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e-learning resources and to foster collaboration in e-learning environments. Design/methodology/approach-This paper proposes an e-learning environment that can be used to provide customized learning. It utilizes a set of interacting agents that can personalize instruction based on an individual's prior knowledge as well as their cognitive and learning needs. The e-learning agents monitor the e-learning environment and improve learning and collaboration based on learners' prior knowledge, social characteristics and learning style. Findings-E-learning agents should allow the discovery of new learning objects more easily, allow learners to customize materials presented to improve learning outcomes, and improve collaboration in the e-learning environment. Originality/value-Little prior research has been done on the use of agents in e-learning environments. This paper proposes a set of e-learning agents that, if implemented in online education or training environments, should provide tangible benefits to organizations.

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Section: Learning Support Systems and Agentsmentioning

confidence: 99%

Section: E‐learning Agentsmentioning

confidence: 99%

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E‐learning agents

Gregg

2007

The Learning Organization

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“…The quantity of online multimedia learning resources increases rapidly to fulfill the basic requirements of learning [ 11 ]. Along with the big data, machine learning technologies have been applied in learning system [ 12 ] [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Digital case-based learning system in school

Gu¹,

Guo²

2017

PLoS ONE

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With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

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“…Context has been identified from the literature to play a crucial role in human knowledge representation, reasoning, and perception [3]. Therefore, multimedia, information retrieval systems need the ability to represent, utilize and reason about context to help improve semantic organization and management of multimedia resources.…”

Section: Introductionmentioning

confidence: 99%

Distributed Multimedia Metadata Tracking and Management: An Ontology-Based Approach with Use of RSS

Belis

Doulamis

2009

2009 16th International Conference on Systems, Signals and Image Processing

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In this paper we present a multimedia metadata management system that uses ontologies for efficient multimedia traceability and management. The use of digital devices to produce image and video content even by novices is expected to significantly increase the amount of multimedia data. This raises the need of adoption of an effective ontology-based model for intelligent multimedia metadata management. The problem assumes greater significance due to different file formats and the necessity of integrating largely distributed and diverse information system implementations. Provided that efficient searching and retrieval systems are based on how annotated data are organized and managed, in our study we use the RSS 2.0 (Really Simple Syndication) format, for enhancing the ontology with multimedia information.

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Towards integrating semantics of multi-media resources and processes in e-Learning

Cited by 10 publications

References 25 publications

E‐learning agents

E‐learning agents

Digital case-based learning system in school

Distributed Multimedia Metadata Tracking and Management: An Ontology-Based Approach with Use of RSS

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