Classy AA-NECTAR: Personalized Ubiquitous E-Learning Recommender System with Ontology and Data Science Techniques

Tahir, Alishba; Ijaz, Ahsan; Javed, Fawad

doi:10.1109/icodt252288.2021.9441481

Cited by 3 publications

(3 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[98], [101], [102], [104], [162], [130], [110], [112], [113], [114], [115], [116], [119] Performance 27 18% [34], [38], [40], [49], [50], [129], [160], [64], [65], [65], [75], [82], [105], [106], [132], [133], [107], [111], [117], [122], [123], [149], [137], [150], [151], [138], [120] Virtual 10 7% [23], [159], [147], [50], [118], [120], [152], [153], [154], [50], …”

Section: E-learning Effectmentioning

confidence: 99%

See 1 more Smart Citation

E-Learning-Based Cloud Computing Environment: A Systematic Review, Challenges, and Opportunities

Eljak,

Ibrahim,

Saeed

et al. 2024

IEEE Access

View full text Add to dashboard Cite

New technologies drive educational shifts, transforming offline to online learning. This study investigates e-learning and cloud computing integration to understand synergies and their potential impact. The study addresses two primary research questions: the influence of elearning on factors like architecture, software, performance, security, hardware, network, and virtual aspects, and the examination of cloud computing services and models such as SaaS, PaaS, IaaS, and S.O.A. The research aims to provide insights into how e-learning is incorporated in a cloud computing environment. The motivation behind this study is to investigate the intricate relationship between e-learning and cloud computing. By analyzing 154 scientific papers, the study delves into the specifics of this integration, highlighting trends and areas that have received more attention. The study examines e-learning in a cloud computing environment, focusing on architecture (27%), general topics (21%), software (19%), and performance (18%). Virtual environments have fewer security issues, while storage and network focus are more prevalent. Cloud computing services are mainly all services, with software as a service (18%), infrastructure as a service (17%), and platforms as a service (10%). Most studies are based on public clouds (74%), all other models (11%), and hybrid clouds (3%). The study examines elearning integration in cloud computing, highlighting limitations in hybrid and private clouds, specialized infrastructure, and a gap in platforms and infrastructure offerings.

show abstract

Section: E-learning Effectmentioning

confidence: 99%

“…[75], [76], [143], [80], [83], [85], [88], [9], [144], [145], [146], [164], [162], [106], [13], [133], [110], [112], [114], [115], [116], [117], [119], [121], [123], [153], [154], [155], [156] Opinion paper 27 17%…”

Section: E-learning Effectmentioning

confidence: 99%

E-Learning-Based Cloud Computing Environment: A Systematic Review, Challenges, and Opportunities

Eljak,

Ibrahim,

Saeed

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The libraries are designed to organize fragments into easily available information sources, and they perform tasks such as unified distributed schemes that include information sources for elements 6 . Although the data is offered for the relevant region of the design guidelines, 7 digital libraries still require the identification to be refined. The canonical type is used to reduce the collection system designation to the description by connecting the designation components to the concepts of the ontological context via the corresponding topic areas and documenting the subject areas of ontological description and collection with the distributed ontology.…”

Section: Introductionmentioning

confidence: 99%

Personalized ontology and deep training tree‐based optimal gated recurrent unit‐recurrent neural network for prediction of students' behavior

Fernandez

Ramana²,

Shabana³

et al. 2022

Concurrency and Computation

View full text Add to dashboard Cite

Summary Digital libraries are now widely used by students all around the world due to the hassle‐free services it offers in the form of digitized study materials, ebooks, multimedia content and so forth. However, to increase user satisfaction and allegiance, a personalized digital library needs to be deployed to offer customized services to the users. To accomplish this objective, this article presents a novel scheme to design personalized digital libraries via the usage of the Protégé editor and machine learning techniques. The Protégé 4.3 tool is used to generate the digital library ontologies and identify the interrelated concepts. Domain knowledge acquisition, ontology organization, ontology elaboration, ensuring the consistency of the information, and ontology validation. The gated recurrent unit‐recurrent neural network (GRU‐RNN) with a deep training tree (DTT) is used to predict the different user behavior styles such as cognitive behavior, learning speed behavior, sedentary behavior, and aggressive behavior. The DTT is mainly incorporated to overcome the vanishing gradient issue associated with the GRU‐RNN and used in the place of gradient‐based optimization. A black widow optimization approach is employed to update the weights of the GRU‐RNN network in order to increase its accuracy. The efficiency of the proposed methodology is analyzed by using different performance metrics such as F‐score, accuracy, loss, precision, and recall scores. The results show that the personalized digital library created can be efficient in terms of usability.

show abstract

Adaptive learning in programming education: A systematic mapping of the literature

Mota Vieira,

Magalhães Netto

2023

2023 IEEE Frontiers in Education Conference (FIE)

View full text Add to dashboard Cite

Classy AA-NECTAR: Personalized Ubiquitous E-Learning Recommender System with Ontology and Data Science Techniques

Cited by 3 publications

References 41 publications

E-Learning-Based Cloud Computing Environment: A Systematic Review, Challenges, and Opportunities

E-Learning-Based Cloud Computing Environment: A Systematic Review, Challenges, and Opportunities

Personalized ontology and deep training tree‐based optimal gated recurrent unit‐recurrent neural network for prediction of students' behavior

Adaptive learning in programming education: A systematic mapping of the literature

Contact Info

Product

Resources

About