Using Maximum Information Selection Strategy to Computer Adaptive Test

Yong Jun Jing; Xin Li; Tian Hua Liu

doi:10.4028/www.scientific.net/AMR.1022.282

Paper Titles

Study on Dehazing Technology of Digital Image
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Research on Image Technology with Application of K-Means Based on Genetic Simulated Annealing Algorithm in CT Image Segmentation
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Applied-Information Technology in Design of Core Particle Classification Test System Based on GPIB Interface
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Applied Technology the Test of Elevator Running Mileage (Dynamic) of Scientific Significance
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Using Maximum Information Selection Strategy to Computer Adaptive Test
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Applied-Information Technology with DSP-Based Recognition Algorithms of Driver Fatigue
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Design and Development of Detection Node in Wireless Sensor Network Based on Neural Network
p.292

Experimental Study of Information Processing Application in Second Language to Computer Interface of Brain
p.296

Applied Technology and Data Processing in Plight and Breakthrough of Academic Research for Librarian
p.300

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1022Using Maximum Information Selection Strategy to...

Using Maximum Information Selection Strategy to Computer Adaptive Test

Abstract:

As psychology, education measure theory and with the combination of computer technology of continuous research and development, based on Computer Adaptive Test (CAT) become a new type of test form. Based on the analysis and state the topic of CAT theory and Maximum Information Selection Strategy (MISS), the method of maximum information selection strategy in the key issues in an adaptive testing system solutions is discussed. The effectiveness of the solution method which this topic given is proved by experiment.