ON-SMMILE: Ontology Network-based Student Model for MultIple Learning Environments

Yago, Hector; Clemente, Julia; Rodríguez, Daniel; Córdoba, Pedro Fernández de

doi:10.1016/j.datak.2018.02.002

Cited by 32 publications

(31 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The model consists of 14 steps that are: 1. Construction of the virtual course, for which it is of the utmost importance to take into account the national and international standards for the construction of virtual courses such as IMS, LOM in order to incorporate the construction of the course the latest tools and insights of instructional design (Yago, Clemente, Rodriguez, & Fernandez-de-Cordoba, 2018), (Pástor, Jimenez, Gomez, & Isotani, 2018). 2.…”

Section: Theoretical Foundation Of the Operational Indicators Of The mentioning

confidence: 99%

Operational Indicators of the Learning Management System in Virtual Spaces Supported by ICT

Capacho¹,

Jimeno²,

Salazar³

2019

Turkish Online Journal of Distance Education

View full text Add to dashboard Cite

The paper presents the conceptual framework and operational indicators of the Learning Management System in virtual spaces supported by ICT. The framework of the management system has three layers that are operational, management-operative, and management-decision. The conceptual foundation of the system is related to the Science of Education, the Science of Computing and the Science of Administration, and takes into account the representative model of the teaching-learning process of the student in virtual spaces supported by ICT. The dimensions, characteristics, variables, and indicators of the management system are assembled on the model in question. The indicators presented in the article correspond to 153 indicators of the operational layer. These were evaluated internationally with a confidence level of more than 90%. The operative indicators are contained in the dimensions of identification, academic, pedagogical-didactic, formative, of assessment of the virtual learning, and technological of the system of management of the virtual learning. The importance of the indicators presented ensures the success of the operational phase of the management system. Therefore, once the operation of the system is guaranteed, the success of the management-operative and management-decision layers of the system is assured. The correct fulfillment of the layers above guarantees the achievement of both the student's learning in the virtual course and the institution that offers virtual teaching through virtual learning platforms supported by ICT.

show abstract

Section: Theoretical Foundation Of the Operational Indicators Of The mentioning

confidence: 99%

Operational Indicators of the Learning Management System in Virtual Spaces Supported by ICT

Capacho¹,

Jimeno²,

Salazar³

2019

Turkish Online Journal of Distance Education

View full text Add to dashboard Cite

show abstract

“…In the work [17], there is considered the problem of creation of the large-scale ontologies and their practical use. The article [18] presents the ontological student's network model for learning environments. This model is developed as a set of ontological resources that have been expanded, standardized, interconnected and adapted for the use in various learning environments.…”

Section: Cognitive Smart-technology Of Distance Learning Of Experion mentioning

confidence: 99%

Cognitive Smart-Technology of Distance Learning of Experion PKS Distributed Control System for Oil and Gas Industry Using Ontological Approach

Samigulina¹,

Technologies²,

Samigulina³

et al. 2020

Series of geology and technical sciences

View full text Add to dashboard Cite

NAS RK is pleased to announce that News of NAS RK. Series of geology and technical sciences scientific journal has been accepted for indexing in the Emerging Sources Citation Index, a new edition of Web of Science. Content in this index is under consideration by Clarivate Analytics to be accepted in the Science Citation Index Expanded, the Social Sciences Citation Index, and the Arts & Humanities Citation Index. The quality and depth of content Web of Science offers to researchers, authors, publishers, and institutions sets it apart from other research databases. The inclusion of News of NAS RK. Series of geology and technical sciences in the Emerging Sources Citation Index demonstrates our dedication to providing the most relevant and influential content of geology and engineering sciences to our community. Қазақстан Республикасы Ұлттық ғылым академиясы "ҚР ҰҒА Хабарлары. Геология жəне техникалық ғылымдар сериясы" ғылыми журналының Web of Science-тің жаңаланған нұсқасы Emerging Sources Citation Index-те индекстелуге қабылданғанын хабарлайды. Бұл индекстелу барысында Clarivate Analytics компаниясы журналды одан əрі the Science Citation Index Expanded, the Social Sciences Citation Index жəне the Arts & Humanities Citation Index-ке қабылдау мəселесін қарастыруда. Webof Science зерттеушілер, авторлар, баспашылар мен мекемелерге контент тереңдігі мен сапасын ұсынады. ҚР ҰҒА Хабарлары. Геология жəне техникалық ғылымдар сериясы Emerging Sources Citation Index-ке енуі біздің қоғамдастық үшін ең өзекті жəне беделді геология жəне техникалық ғылымдар бойынша контентке адалдығымызды білдіреді. НАН РК сообщает, что научный журнал «Известия НАН РК. Серия геологии и технических наук» был принят для индексирования в Emerging Sources Citation Index, обновленной версии Web of Science. Содержание в этом индексировании находится в стадии рассмотрения компанией Clarivate Analytics для дальнейшего принятия журнала в the Science Citation Index Expanded, the Social Sciences Citation Index и the Arts & Humanities Citation Index. Web of Science предлагает качество и глубину контента для исследователей, авторов, издателей и учреждений. Включение Известия НАН РК. Серия геологии и технических наук в Emerging Sources Citation Index демонстрирует нашу приверженность к наиболее актуальному и влиятельному контенту по геологии и техническим наукам для нашего сообщества.

show abstract

“…Unlike classroom teaching, e-Learning courses have specific characteristics such as the transactional distance between actors (educators and students) and the use of learning platforms, called as Learning Management System (LMS) or Massive Open Online Courses (MOOC). This transactional distance presents challenges in the teaching process such as: i) the lack of information about the students' real academic progress, ii) the attempt to predict the result of the students' academic performance, iii) the difficulty in making pedagogical decisions due to the low support of Information Systems, iv) the difficulty in keeping the student engaged, and v) high dropout rates (Yago et al, 2018;Villagra-Arnedo et al, 2017;Iglesias-Prada et al, 2015). Thus, researchers are making an effort to minimize such challenges using computational resources applied to the educational context.…”

Section: Introductionmentioning

confidence: 99%

“…However, the tools of supervising students available in learning platforms are not easy to use and do not enable the consistent assessment of student learning progress. According to Yago et al (2018), educators try to use the tools available on the learning Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Academic Performance Based on Learning Analytics and Ontology: A Systematic Review

Costa¹,

Sanches²,

Amorim³

et al. 2020

Informatics in Education

View full text Add to dashboard Cite

This paper presents a systematic literature review of the coordinated use of Learning Analytics and Computational Ontologies to support educators in the process of academic performance evaluation of students. The aim is to provide a general overview for researchers about the current state of this relationship between Learning Analytics and Ontologies, and how they have been applied in a coordinated way. We selected 31 of a total of 1230 studies related to the research questions. The retrieved studies were analyzed from two perspectives: first, we analyzed the approaches where researchers used Learning Analytics and Ontologies in a coordinated way to describe some Taxonomy of Educational Objectives; In the second perspective, we seek to identify which models or methods have been used as an analytical tool for educational data. The results of this review suggest that: 1) few studies consider that student interactions in the Learning Management System can represent students' learning experiences; 2) most studies use ontologies in the context of learning object assessment to enable learning sequencing; 3) we did not identify methods of evaluation of academic performance guided by Taxonomies of Educational Objectives; and 4) no studies were identified that report the coordinated use of Learning Analytics and Computational Ontologies, in the context of academic performance monitoring. Thus, we identify future directions of research such as the proposal of a new model of evaluation of academic performance.

show abstract

ON-SMMILE: Ontology Network-based Student Model for MultIple Learning Environments

Cited by 32 publications

References 17 publications

Operational Indicators of the Learning Management System in Virtual Spaces Supported by ICT

Operational Indicators of the Learning Management System in Virtual Spaces Supported by ICT

Cognitive Smart-Technology of Distance Learning of Experion PKS Distributed Control System for Oil and Gas Industry Using Ontological Approach

Monitoring Academic Performance Based on Learning Analytics and Ontology: A Systematic Review

Contact Info

Product

Resources

About