Modeling learning technology systems as business systems

2003 ◽  
Vol 2 (2) ◽  
pp. 120-133 ◽  
Author(s):  
Paris Avgeriou ◽  
Symeon Retalis ◽  
Nikolaos Papaspyrou
Author(s):  
Valeria Marina Monetti ◽  
Loredana Randazzo ◽  
Antonello Santini ◽  
Gerardo Toraldo

Author(s):  
Vijay Kumar ◽  
Jeff Merriman

We propose a trajectory for learning technology systems that represent a departure from closed, monolithic approaches, typically inherent in the design of these systems, to open, standards-based frameworks that can support diverse pedagogy and accommodate heterogeneous technology. Central to this vision is an architectural approach, illustrated by the Open Knowledge Initiative, which supports the development of sustainable educational tools and technology through enabling commoditization and community.


2021 ◽  
Vol 34 (01) ◽  
Author(s):  
Dr. Palakh Jain ◽  
◽  
Mr. Utkarsh Kumar ◽  
Ms. Vaishnavi Gupta ◽  
Mr. Aditya Raj Jain ◽  
...  

Author(s):  
Gerard Gleeson ◽  
Claus Pahl

E-Learning has been a topic of increasing interest in recent years, due mainly to the fact that content and tool support can now be offered at a widely affordable level. As a result, many e-learning platforms and systems have been developed. Client-server, peer-to-peer and recently Web services architectures often form the basis. Drawbacks of these architectures are often their limitations in terms of scalability and the availability and distribution of resources. This chapter investigates grid architectures in the context of e-learning as a proposed answer for this problem. The principles and technologies of Grid architectures are discussed and illustrated using learning technology scenarios and systems.


2020 ◽  
Vol 39 (4) ◽  
pp. 5699-5711
Author(s):  
Shirong Long ◽  
Xuekong Zhao

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.


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