Smart Learning Objects for Online and Blended Learning Approach

Rutkauskiene, Danguole; Gudonienė, Daina; Bartkutė, Reda; Volodzkaite, Greta

doi:10.1007/978-981-13-8260-4_18

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…(10) Accuracy of design, as many instructional design models are available that suit the nature of the learning elements, and therefore their designers do not find any obstacle to their design with accuracy and efficiency. (11) Compliance with SCORM standards: Thus, learning elements can be made available through any learning and content management system, which means greater spread and wider use (Choez et al, 2021), (Basuhail, 2020), (Rutkauskiene et al, 2019).…”

Section: The Importance and Advantages Of Digital Learning Objectsmentioning

confidence: 99%

Exploring the need of using Auto-Produced e-Learning Objects (Generator) in Oman Schools

Shemy

Aboraya

Said

et al. 2021

International Journal of Internet Education

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Section: The Importance and Advantages Of Digital Learning Objectsmentioning

confidence: 99%

Exploring the need of using Auto-Produced e-Learning Objects (Generator) in Oman Schools

Shemy

Aboraya

Said

et al. 2021

International Journal of Internet Education

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“…To help practitioners, instructional designers, instructors, and curriculum developers understand the evolution of online learning and make educated choices when establishing high-quality online learning experiences, this research indicates using a longitudinal approach that tracks online learners over time to collect substantial evidence [4]. exemplifies how modern technology makes it easier, faster, and more convenient for students to absorb new information [6]. Smart education in online learners is the integration of technological tools into more conventional educational processes.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Learning Characteristics of Online Learners in the Context of Smart Education

Weihua

2024

ICST Transactions on Scalable Information Systems

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This article aims to explore the learning characteristics of online learners within the smart education framework, with a specific emphasis on how they might use Internet of Things (IoT) technologies to improve their educational experience. The term "online learning" refers to the process of acquiring knowledge via electronic means, most often the global web. Online education, e-learning, web-based learning, and computer-assisted learning all share this term. The challenging characteristics of such online learners for students are technical issues, lack of motivation, and slow loading times in online courses. Hence, in this research, the Internet of Things-empowered Smart Education (IoT-SE) Framework has been improved for online learners for students by leveraging IoT tech that tracks how learners interact with learning resources and their environment. This paper aims to revolutionize web-based education through tailored instructions targeting individuals' unique needs and fads as availed by the IoT-SE system. This paper offers evaluation parameters such as level of engagement among learners, retention rates on knowledge acquired while studying e-courses, and satisfaction from an online program. Besides overcoming limitations associated with conventional e-learning approaches, such systems like IoT-SE technology promise more effective pedagogy and student satisfaction for online learners.

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“…Although online learning can provide richer learning resources and more flexible learning methods, for reluctant students with poor consciousness and initiative, it's hard to get ideal learning effects [1][2][3][4][5][6][7][8]; as for independent students who learn by themselves, it's hard to enhance their learning abilities [9][10][11][12][13]. So, in order to give full play to the real effects of hybrid learning, Hybrid Learning Community Network (HLCN) could be built to integrate online and offline learning and form hybrid learning network communities [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Effectiveness of Hybrid Learning Activities Based on a Learning Community Network

Xie¹

2022

Int. J. Emerg. Technol. Learn.

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Hybrid Learning Community Network (HLCN) can link individuals to collectives systematically, support both virtual and actual scenarios, and share and trade knowledge, experience, and learning resources. Existing studies on HLCN are mostly theoretical research, there’re very few empirical evidences, and the integrity of the research systems is yet to be improved further. In view of these shortcomings, this paper proposed a theoretical model for HLCN and built an Evaluation Index System (EIS) for assessing the effectiveness of the hybrid learning activities and analyzing the feature parameters and centrality of the HLCN. Then in the paper, a Hybrid Learning Interactive Activity Content Network Relation (HL-IAC-NR) matrix was established based on learning community, and the indexes such as students’ learning attention on knowledge points and their learning sentiments were attained. At last, this paper used the Charnes-Cooper-Rhodes (CCR) model in Data Envelope Analysis (DEA) to evaluate the relative effectiveness, and the real-time effects of different types of hybrid learning interactive activities were analyzed. The effectiveness of the proposed model and evaluation method was verified via experiments.

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Smart Learning Objects for Online and Blended Learning Approach

Cited by 4 publications

References 9 publications

Exploring the need of using Auto-Produced e-Learning Objects (Generator) in Oman Schools

Exploring the need of using Auto-Produced e-Learning Objects (Generator) in Oman Schools

Analysis of Learning Characteristics of Online Learners in the Context of Smart Education

Evaluation of the Effectiveness of Hybrid Learning Activities Based on a Learning Community Network

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