An ontology-based information retrieval mechanism for E-learning management system

2020 ◽  
Vol 26 (1) ◽  
Author(s):  
L.O. Omotosho ◽  
C.O. Akanbi ◽  
M.U. Ituen ◽  
I.K. Ogundoyin
Keyword(s):  
Description Logic ◽  
Early Stage ◽  
Consistency Checking ◽  
Ontological Engineering ◽  
Engineering Technique ◽  
Domain Expertise ◽  
E Learning ◽  
Retrieval Mechanism ◽  
The University

During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. The application of ontological engineering technique to e-learning, though still in its early stage, has become a phenomena tool in the integration and adaptation of a dynamic and flexible elearning environment, where tutors and learners are provided with the functionality of personalizing their learning process, this has not fully considered the generality of an entire field of study. This paper presents an ontology-based framework for classification of the entire courses of computer science at the university level. A model of an e-learning domain in the context of material classification that enables students retrieve information about a particular course in personalized ways was presented the method adopted elicited e-learning knowledge using documented materials, observation, consultation, prototyping among others. With domain expertise developed, the knowledge elicited was analyzed and formally represented using OWL-Description Logic. The design was implemented using Protégé 5.0 editor. The validation for accuracy and completeness was carried out with the domain and ontology experts using consistency checking reasoned, DL-Query. The results of the implementation show that elearning materials can be searched and retrieved easily and timely. The study also established and formalised an effective computational approach for representing information content of educational resources thereby helping to improve the flexibility of content representation in an e-learning system.Keywords: e-learning, Ontological Engineering, Ontology, Ontology Web Language (OWL), Knowledge Management, Description LogicVol. 26, No 1, June 2019

scholarly journals Centre of Agri-Knowledge – a Web-Based Integration of Information and Decision Support Systems for Agriculture

2006 ◽  
pp. 64-66
Author(s):  
Tamás Dövényi-Nagy
Keyword(s):  
Early Stage ◽  
Eastern Region ◽  
Web Based ◽  
Internet Technologies ◽  
Internet Portal ◽  
Internet Communities ◽  
Stage Of Development ◽  
Agricultural Sciences ◽  
E Learning ◽  
The University

The University Debrecen Centre of Agricultural Sciences acts as the centre and co-ordinator of agrarian higher education and consultation in the eastern region of Hungary. New internet technologies afford new chances to accomplish the institute’s mission to develop agriculture, environment and countryside in the area. As the main framework of integrated e-learning, e-business and research in the agrifood sector the development of an internet portal, the „Centre of Agri-knowledge” (CAK) has been started in the recent past.To support our students and education, to stay continuous in touch with our agricultural engineers we consider very important to build internet communities, where students, farmers, traders and researchers can share their knowledge and experience.In Europe same as in Hungary agriportals born and disappear continuously. Although CAK is still in its early stage of development, its comprehensiveness, professional backend and the experience of the Centre of Agricultural Sciences guarantee a new standard of online services in the Hungarian agrifood sector

scholarly journals Implementasi Teori Pembelajaran Blended Learning dalam Menyeimbangkan Kapabilitas Belajar pada Era Digital (Studi Kasus di Prodi PAI Universitas Alma Ata Yogyakarta)

2020 ◽  
Vol 7 (1) ◽  
pp. 33-51
Author(s):  
Abdul Rohman
Keyword(s):  
Blended Learning ◽  
Learning Theory ◽  
Cognitive Strategies ◽  
Verbal Information ◽  
Face To Face ◽  
Learning Patterns ◽  
Learning Capabilities ◽  
E Learning ◽  
The University

Blended learning learning pattern is a combination of conventional learning patterns and e-learning. The concept of blended learning applied at the University of Alma-ata uses the WEB system with a composition of blended learning patterns, 75% for conventional learning and 25% for e-learning. The implementation of the blended learning theory in balancing learning capabilities includes two classifications. Learning capabilities include five aspects, namely verbal information, cognitive strategies, intellectual skills, attitudes and motor skills. The five capabilities are divided into two classifications of blended learning theory, namely verbal information and cognitive strategies included in the classification of e-learning, this is because it places more emphasis on the knowledge aspect. Then the three other aspects fall into the classification of conventional learning, this is because the conventional learning process is carried out directly and face-to-face between educators and students, educators become a central figure in learning and play a role not only in conveying science but as explained by Alghazali, educators are al -mudaris, al-mualim, al-muaddib and al-walid.

NORMATIVE-METHODICAL SUPPORT OF THE EDUCATIONAL PROCESS AT UNIVERSITY IN TERMS OF E-LEARNING

2019 ◽  
pp. 56-63
Author(s):  
S. V. Kalmykova
Keyword(s):  
Online Courses ◽  
Practical Experience ◽  
Educational Process ◽  
Educational Resources ◽  
Project Work ◽  
Peter The Great ◽  
E Learning ◽  
The University ◽  
Academic Year

The article summarizes the experience of Peter the Great St. Petersburg Polytechnic University (SPbPU) in changing the regulatory and methodological support of the educational process in the context of e-learning. The models of involvement of mass open online courses (MOOCs) in the educational process of the university are considered. The author draws on practical experience and the results of an experiment implemented in 2016–2019 at Peter the Great St. Petersburg Polytechnic University, which allowed to include online courses in 100 % of the curriculum by the beginning of the 2018/2019 academic year. The analysis of the necessary local regulations, allowing to begin the active integration of online courses in the educational process. The necessity of classification of electronic educational resources within the university is substantiated. The possibility of using e-learning for the organization of project work is substantiated. A detailed description of the components of educational resources, which allowed to implement common requirements for their implementation in the educational process is given.

Hard and light gamification in education: Which one to choose?

2020 ◽  
Vol 1 (1) ◽  
pp. 20-27
Author(s):  
E. V. Karmanova ◽  
V. A. Shelemetyeva
Keyword(s):  
Computer Games ◽  
Educational Process ◽  
Course Development ◽  
Learning Technology ◽  
Training Course ◽  
Resource Requirements ◽  
E Learning ◽  
Characteristic Features ◽  
Game Elements

The article is devoted to the implementation of gamification methods in the educational process. The characteristic features of light and hard gamification are presented. The appropriateness of using gamification when applying e-learning technology is considered. Classification of courses based on hard gamification taking into account the technological features of development is proposed: courses-presentations, courses — computer games, VR/AR courses. The article also illustrates the use of various game elements of easy gamification using the example of the module “Level up! — Gamification” of the Moodle LMS. The capabilities of this module can be used in an electronic course by any teacher who has the skills of working with the Moodle.The authors present the analysis of the development of a training course in sales techniques using hard and light gamification technologies, where the course development was assessed for its complexity, manufacturability, and resource requirements. The results of the analysis showed that the development of courses using hard gamification requires much more financial and time-consuming than the development of courses using light gamification.The article evaluates the results of the educational intensiveness intense “Island 10–22”, held in July 2019 in Skolkovo, in which 100 university teams, teams of research and educational centers, teams of schoolchildren — winners of competitions, olympiads, hackathons (“Young Talents”) participated. The results of the intense confirmed the effectiveness of the use of light gamification methods in adult training. Thus, the conclusions presented in the article reveal a number of advantages that light gamification has in comparison with hard gamification.

Hindrance to the Integration of e-learning Adoption in Nigerian Universities

GIS Business ◽  
2019 ◽  
Vol 14 (5) ◽  
pp. 21-28
Author(s):  
Abasiama G. Akpan ◽  
Chris Eriye Tralagba
Keyword(s):  
Teaching And Learning ◽  
Case Study Research ◽  
University Education ◽  
Learning Approach ◽  
University System ◽  
Electronic Learning ◽  
E Learning ◽  
Nigerian University ◽  
The University

Electronic learning or online learning is a part of recent education which is dramatically used in universities all over the world. As well as the use and integration of e-learning is at the crucial stage in all developing countries. It is the most significant part of education that enhances and improves the educational system. This paper is to examine the hindrances that influence e-learning in Nigerian university system. In order to have an inclusive research, a case study research was performed in Evangel University, Akaeze, southeast of Nigeria. The paper demonstrates similar hindrances on country side. This research is a blend of questionnaires and interviews, the questionnaires was distributed to lecturers and an interview was conducted with management and information technology unit. Research had shown the use of e-learning in university education which has influenced effectively and efficiently the education system and that the University education in Nigeria is at the crucial stage of e-learning. Hence, some of the hindrances are avoiding unbeaten integration of e-learning. The aim of this research is to unravel the barriers that impede the integration of e-learning in universities in Nigeria. Nevertheless, e-learning has modified the teaching and learning approach but integration is faced with many challenges in Nigerian University.

scholarly journals Detection and Severity Classification of COVID-19 in CT Images Using Deep Learning

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 893
Author(s):  
Yazan Qiblawey ◽  
Anas Tahir ◽  
Muhammad E. H. Chowdhury ◽  
Amith Khandakar ◽  
Serkan Kiranyaz ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Neural Networks ◽  
Early Stage ◽  
Similarity Coefficient ◽  
Dice Similarity Coefficient ◽  
Lung Region ◽  
Computed Tomography Images ◽  
Feature Pyramid ◽  
Severity Levels

Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients. In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from computed tomography images. An extensive set of experiments were performed using Encoder–Decoder Convolutional Neural Networks (ED-CNNs), UNet, and Feature Pyramid Network (FPN), with different backbone (encoder) structures using the variants of DenseNet and ResNet. The conducted experiments for lung region segmentation showed a Dice Similarity Coefficient (DSC) of 97.19% and Intersection over Union (IoU) of 95.10% using U-Net model with the DenseNet 161 encoder. Furthermore, the proposed system achieved an elegant performance for COVID-19 infection segmentation with a DSC of 94.13% and IoU of 91.85% using the FPN with DenseNet201 encoder. The proposed system can reliably localize infections of various shapes and sizes, especially small infection regions, which are rarely considered in recent studies. Moreover, the proposed system achieved high COVID-19 detection performance with 99.64% sensitivity and 98.72% specificity. Finally, the system was able to discriminate between different severity levels of COVID-19 infection over a dataset of 1110 subjects with sensitivity values of 98.3%, 71.2%, 77.8%, and 100% for mild, moderate, severe, and critical, respectively.

scholarly journals Cross-evaluation of social mining for classification of depressed online personas

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alina Trifan ◽  
José Luis Oliveira
Keyword(s):  
Transfer Learning ◽  
Early Stage ◽  
Post Partum ◽  
Evaluation Study ◽  
Continuous Increase ◽  
Digital Phenotyping ◽  
Public Datasets ◽  
The Impact ◽  
Social Mining

Abstract With the continuous increase in the use of social networks, social mining is steadily becoming a powerful component of digital phenotyping. In this paper we explore social mining for the classification of self-diagnosed depressed users of Reddit as social network. We conduct a cross evaluation study based on two public datasets in order to understand the impact of transfer learning when the data source is virtually the same. We further complement these results with an experiment of transfer learning in post-partum depression classification, using a corpus we have collected for the matter. Our findings show that transfer learning in social mining might still be at an early stage in computational research and we thoroughly discuss its implications.

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