The aDORe federation architecture: digital repositories at scale

Sompel, Herbert Van de; Ryan, Chris; Hochstenbach, Patrick

doi:10.1007/s00799-008-0048-7

Cited by 19 publications

(11 citation statements)

References 26 publications

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“…LORs are currently being used in various e-learning environments and belong mainly to educational institutions [2,3]. Also, federations of LORs provide educational applications to search, retrieve and access specific LO contents available in any LOR [4]. Recommender Systems aim to provide users with search results close to their needs, making predictions of their preferences [5].…”

Section: Motivationmentioning

confidence: 99%

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Argumentation-Based Hybrid Recommender System for Recommending Learning Objects

Rodríguez

Heras

Palanca

et al. 2016

Multi-Agent Systems and Agreement Technologies

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Abstract. Recommender Systems aim to provide users with search results close to their needs, making predictions of their preferences. In virtual learning environments, Educational Recommender Systems deliver learning objects according to the student's characteristics, preferences and learning needs. A learning object is an educational content unit, which once found and retrieved may assist students in their learning process. In previous work, authors have designed and evaluated several recommendation techniques for delivering the most appropriate learning object for each specific student. Also, they have combined these techniques by using hybridization methods, improving the performance of isolated techniques. However, traditional hybidization methods fail when the learning objects delivered by each recommendation technique are very different from those selected by the other techniques (there is no agreement about the best learning object to recommend). In this paper, we present a hybrid recommendation method based on argumentation theory that combines content-based, collaborative and knowledge-based recommendation techniques and provides the students with those objects for which the system is able to generate more arguments to justify their suitability. This method has been tested by using a database with real data about students and learning objects, getting promising results. MotivationAccording to the IEEE, a learning object (LO) can be defined as a digital entity involving educational design characteristics. Each LO can be used, reused or referenced during computer-supported learning processes, aiming at generating knowledge and competences based on student's needs [1]. LOs have functional requirements such as accessibility, reuse, and interoperability. The concept of LO requires understanding of how people learn, since this issue directly affects the LO design in each of its three dimensions: pedagogical, didactic, and technological [2]. In addition, LOs have metadata that describe and identify the educational resources involved and facilitate their searching and retrieval. Learning ObjectsCorresponding author.Repositories (LORs), composed of thousands of LOs, can be defined as specialized digital libraries storing several types of heterogeneous resources. LORs are currently being used in various e-learning environments and belong mainly to educational institutions [2,3]. Also, federations of LORs provide educational applications to search, retrieve and access specific LO contents available in any LOR [4]. Recommender Systems aim to provide users with search results close to their needs, making predictions of their preferences [5]. In virtual learning environments, Educational Recommender Systems (ERS) deliver LOs according to the student's characteristics, preferences and learning needs. In order to improve recommendations, ERS must perform feedback processes and implement mechanisms that enable them to obtain a large amount of information about users and how they use the LOs. ERS can be classified into s...

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Section: Motivationmentioning

confidence: 99%

“…Then, the integration module performs the hybridization process to provide the student with the most relevant and appropriate LOs. This is done by selecting LOs that have been proposed by 2 4 Several hybridization methods, as proposed in [6], were tested, and the cascade approach achieved the best recommendation results [8]. or 3 of the recommendation modules.…”

mentioning

confidence: 99%

Argumentation-Based Hybrid Recommender System for Recommending Learning Objects

Rodríguez

Heras

Palanca

et al. 2016

Multi-Agent Systems and Agreement Technologies

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“…Federation of LORs serve to provide educational applications of uniform administration in order to search, retrieve and access specific LO contents available in whatever of LOR groups [10].…”

Section: Learning Objects Repositories and Federationsmentioning

confidence: 99%

Adaptive and Personalized Educational Ubiquitous Multi-Agent System Using Context-Awareness Services and Mobile Devices

Salazar

Ovalle

Duque

2015

Lecture Notes in Computer Science

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Abstract. In the last decade, some useful contributions have occurred to elearning system development such as adaptation, ubiquity, personalization, as well as context-awareness services. The aim of this paper is to present the advantages brought by the integration of ubiquitous computing along with distributed artificial intelligence techniques in order to build an adaptive and personalized context-aware learning system by using mobile devices. Based on this model we propose a multi-agent context-aware u-learning system that offers several functionalities such as context-aware learning planning, personalized course evaluation, selection of learning objects according to student profile, search of learning objects in repository federations, search of thematic learning assistants, and access of current context-aware collaborative learning activities involved. In addition, several context-awareness services are incorporated within the adaptive e-learning system that can be used from mobile devices. In order to validate the model a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of using this kind of approaches in virtual learning environments which constitutes an attempt to improve learning processes.

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“…However, in the digital contents world there are many studies [9] and proposals [10][11][12] on this topic. But none of them have been applied to a software artifact repository.…”

Section: Software Repository Standardsmentioning

confidence: 99%