A framework for helping developers in the integration of external tools into virtual learning environments

Lorenzo, Emilio; Centeno, Roberto; Rodriguez-Artacho, Miguel

doi:10.1145/2536536.2536556

Cited by 4 publications

(6 citation statements)

References 8 publications

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“…[21], [22], [23], [24], [25], [8], [26], [27], [28]. [29], [30], [31], [32], [33], [5], [34], [35], [36], [ 37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [1], [51], [52], [53],…”

Section: Figure 12 Distribution Of Papers Discussing the Effect Of E-...unclassified

“…[157], [158], [159], [160] , [161] [21], [157], [8], [26], [27], [158], [29], [32], [33], [5], [34], [35], [36], [38], [40], [41 ], [42], [43], [44], [45], [125], [49], [126], [127], [128], [129], [1], [51], [52], [53], [5 4], [55], [56], [58], [59], [60], [61], [62], [63], [64], [65], [65], [68], [70], [4], [72], [7 3],…”

Section: Figure 12 Distribution Of Papers Discussing the Effect Of E-...mentioning

confidence: 99%

“…[21], [22], [157], [25], [33], [35], [37], [163], [41], [45], [1], [51], [52], [55], [59], [60], [61], [62], [63], [68 ], [70], [71], [4], [72], [73], [142], [7], [81], [89], [90], [161], [96], [97], [131], [148], [135], [136], [124], [1 38], [156], [140] General 33 21% [8], [26], [158], [29], [32], [5], [36], [43], [44], [125],…”

Section: E-learning Effectmentioning

confidence: 99%

See 2 more Smart Citations

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

Eljak,

Ibrahim,

Saeed

et al. 2024

IEEE Access

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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.

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Section: Figure 12 Distribution Of Papers Discussing the Effect Of E-...unclassified

Section: Figure 12 Distribution Of Papers Discussing the Effect Of E-...mentioning

confidence: 99%

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

Eljak,

Ibrahim,

Saeed

et al. 2024

IEEE Access

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“…Shape-from-shadow is another common approach to enhance shape perception. Lee et al used multiple lights and local illumination to adaptively enhance the shapes of different parts of structures [25]. However, local illumination may destroy the rendering of different structures and cannot provide the correct location information of the targets.…”

Section: Introductionmentioning

confidence: 99%

Perception enhancement using importance-driven hybrid rendering for augmented reality based endoscopic surgical navigation

Chu¹,

Xu²,

Yang³

et al. 2018

Biomed. Opt. Express

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Misleading depth perception may greatly affect the correct identification of complex structures in image-guided surgery. In this study, we propose a novel importancedriven hybrid rendering method to enhance perception for navigated endoscopic surgery. First, the volume structures are enhanced using gradient-based shading to reduce the color information in low-priority regions and improve the distinctions between complicated structures. Second, an importance sorting method based on the order-independent transparency rendering is introduced to intensify the perception of multiple surfaces. Third, volume data are adaptively truncated and emphasized with respect to the perspective orientation and the illustration of critical information for viewing range extension. Various experimental results prove that with the combination of volume and surface rendering, our method can effectively improve the depth distinction of multiple objects both in simulated and clinical scenes. Our importance-driven surface rendering method demonstrates improved average performance and statistical significance as rated by 15 participants (five clinicians and ten non-clinicians) on a five-point Likert scale. Further, the average frame rate of hybrid rendering with thin-layer sectioning reaches 42 fps. Given that the process of the hybrid rendering is fully automatic, it can be utilized in real-time surgical navigation to improve the rendering efficiency and information validity.

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“…These educational resources are currently stored in a SQL Database, and we have been happy with it. However, since the teachers and students started learning the educational resources online, the database is not able to keep up and the teachers and students are experiencing delays [1]. As teachers and students base and educational resources grow rapidly, we spend money buying more and more Hardware/Software, but to no avail.…”

Section: Introductionmentioning

confidence: 99%

Big Data X-Learning Resources Integration and Processing in Cloud Environments

Kong¹

2014

Int. J. Emerg. Technol. Learn.

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The cloud computing platform has good flexibility characteristics, more and more learning systems are migrated to the cloud platform. Firstly, this paper describes different types of educational environments and the data they provide. Then, it proposes a kind of heterogeneous learning resources mining, integration and processing architecture. In order to integrate and process the different types of learning resources in different educational environments, this paper specifically proposes a novel solution and massive storage integration algorithm and conversion algorithm to the heterogeneous learning resources storage and management cloud environments.

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A framework for helping developers in the integration of external tools into virtual learning environments

Cited by 4 publications

References 8 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

Perception enhancement using importance-driven hybrid rendering for augmented reality based endoscopic surgical navigation

Big Data X-Learning Resources Integration and Processing in Cloud Environments

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