Personalized learning effect evaluation model for vocational education with cloud computing technology Article Swipe
Xiangyu Wang
,
Kang Cao
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.sasc.2025.200264
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.sasc.2025.200264
The advent of cloud computing technology (CCT) has expedited the advancement of online learning methodologies and, to a certain extent, compensated for the limitations inherent in traditional teaching approaches. However, online teaching under CCT still has the problem of unstable teaching quality, so the study establishes a relevant learning effect evaluation model for the personalized learning platform of vocational education under CCT. To achieve more efficient and accurate evaluation of learning effect, an adjustable variation genetic algorithm-backpropagation neural network (AGA-BP) is proposed. The model introduces an adjustable mutation approach, which adapts the mutation probability in real-time in accordance with the progress of the genetic algorithm in the search process, so as to prevent entering into local optimization and ensure the maintenance of diversity. This strategy significantly enhances the convergence speed and overall search capability of the algorithm. Meanwhile, using the excellent fitting characteristics of neural network, AGA-BP model can accurately learn and simulate different students' learning behavior and effectiveness. The experiment outcomes indicate that the model's mean square error is 3.3883e*10–12, its fitness value is 1.36, and its average accuracy is 98.35 %.
Related Topics
Concepts
Cloud computing
Vocational education
Computer science
Personalized learning
Data science
Mathematics education
Psychology
Teaching method
Operating system
Pedagogy
Open learning
Cooperative learning
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.sasc.2025.200264
- OA Status
- diamond
- References
- 16
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4410000253
All OpenAlex metadata
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https://openalex.org/W4410000253Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.sasc.2025.200264Digital Object Identifier
- Title
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Personalized learning effect evaluation model for vocational education with cloud computing technologyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-05-01Full publication date if available
- Authors
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Xiangyu Wang, Kang CaoList of authors in order
- Landing page
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https://doi.org/10.1016/j.sasc.2025.200264Publisher landing page
- Open access
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1016/j.sasc.2025.200264Direct OA link when available
- Concepts
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Cloud computing, Vocational education, Computer science, Personalized learning, Data science, Mathematics education, Psychology, Teaching method, Operating system, Pedagogy, Open learning, Cooperative learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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16Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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