Title :
An Automatic Grading Model for Learning Assessment
Author_Institution :
Sch. of Inf. & Electron. Eng., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
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;
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
DOI :
10.1109/IC4E.2010.32