OBAA-LEME: A Learning Object Metadata Content Editor supported by Application Profiles and Educational Metadata Ontologies

Behr, André; Primo, Tiago Thompsen; Vicari, Rosa María

doi:10.5753/cbie.wcbie.2014.455

Cited by 2 publications

(1 citation statement)

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“…Besides the works described above, many others were published in Brazil during this period with promising results regarding this new unifying moment between ontologies and the adaptive educational systems. Some examples are: Challenges in Creating Adaptive Instructional Materials and their Use in Popular E-Learning Environments (Publio et al, 2013), Challenge of the Use of Gamification in Intelligent Tutoring Systems Based on Semantic Web (Andrade et al, 2013), OBAA-LEME: A Learning Object Metadata Content Editor Supported by Application Profiles and Educational Metadata Ontologies (Behr et al, 2014), Systematic Review of the Use of the Semantic Web for Virtual Learning Environments (Pereira & Siqueira, 2014), Semantic Description of Learning Experience Based on xAPI Specification (Rabelo et al, 2015), Comparative Analysis of Association Approaches between Felder-Silverman Learning Styles and IEEE LOM Standard Metadata (Aguiar et al, 2015), Training Monitoring in e-learning Made Possible by the Integration between Learning Management Systems and Personal Learning Environment (Melo Filho et al, 2014) and A Reference Ontology for Pedagogical Architectures (Silveira et al, 2021).…”

Section: Distance Learning In the 20th Centurymentioning

confidence: 99%

Semantic Web and Distance Learning: Euphoria, Frustration and Restart

Castello Branco Neto

2024

RBIE

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In the nineties, two different trends on distance learning research arose. The first one aimed to create systems able to adapt themselves to students’ characteristics, based on instructional and learning theories, while the second aimed to facilitate the creation and management of distance courses, by reusing material. Technologies available so far had hindered the creation of systems able to conjoin the benefits achieved by both groups because adaptive systems were limited to a specific knowledge domain, and almost everything had to be recreated to be used in a different subject. On the other hand, systems able to deal with different subjects could not automatically adapt their content to students’ needs. The emergence of the Semantic Web, as well as Learning Objects, led researchers to develop projects based on them to solve that problem. At last, adaptive and reusable courses based on learning theories could be developed. Learning Object Metadata and other standards for e-learning, as well as ontologies about different knowledge domains, students’ characteristics and learning theories were the tools that researchers were missing to solve such problems. Although much research and publications have been done in that period, few practical results were noticed, frustrating not only the students, but also the teachers and other education-related workers, as they realized that the level of system autonomy they had aimed for had not been reached. This paper describes the euphoria caused by the Semantic Web, problems related to the engineering of ontologies that led to a frustration period, as well as the current period, in which research was resumed with less ambitious objectives. Thus, some considerations about the future of the Semantic Web Based Learning are presented.

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