DocumentCode
1858787
Title
An Automatic Grading Model for Learning Assessment
Author
Liu, Yang
Author_Institution
Sch. of Inf. & Electron. Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
fYear
2010
fDate
22-24 Jan. 2010
Firstpage
217
Lastpage
220
Abstract
Particle swarm optimization (PSO) is an algorithm modelled on swarm intelligence that finds a solution to an optimization problem in a search space. In this paper, a PSO-based artificial neural network algorithm is proposed to automatically grading the learning results. Basically, the PSO algorithm is utilized to adjust the connection weights of the selected ANN topology. Taken mandarin learning as example, we introduced the PSO-based ANN algorithm to grading mandarin learning, the experimental results shown it´s an effective method.
Keywords
educational administrative data processing; neural nets; particle swarm optimisation; ANN topology; PSO algorithm; artificial neural network; automatic grading model; learning assessment; particle swarm optimization; search space; swarm intelligence; Artificial neural networks; Birds; Education; Electronic learning; Equations; Network topology; Neurofeedback; Particle swarm optimization; Quality management; Space technology; artificial neural network; learning assessment; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
e-Education, e-Business, e-Management, and e-Learning, 2010. IC4E '10. International Conference on
Conference_Location
Sanya
Print_ISBN
978-1-4244-5680-2
Electronic_ISBN
978-1-4244-5681-9
Type
conf
DOI
10.1109/IC4E.2010.32
Filename
5432425
Link To Document