Two algorithms for estimating test complexity levels-Reference-Cited by-同舟云学术

Two algorithms for estimating test complexity levels

Published:2017-12 Issue:12 Volume:78 Page:2165-2177
ISSN:0005-1179
Container-title:Automation and Remote Control
language:en
Short-container-title:Autom Remote Control

Author:

Kibzun A. I.,Zharkov E. A.

Publisher

Pleiades Publishing Ltd

Subject

Control and Systems Engineering,Electrical and Electronic Engineering

Link

http://link.springer.com/article/10.1134/S0005117917120050/fulltext.html

Reference8 articles.

1. Kibzun, A.I., Karolinskaya, S.N., and Shayukov, R.I., A Remote Study System for Mathematical Disciplines in the University, Vestn. Komp’yut. Inform. Tekhnol., 2006, no. 4, pp. 29–36.

2. Kibzun, A.I. and Panarin, S.I., Generation of Integral Rating by Statistical Processing of the Test Results, Autom. Remote Control, 2012, vol. 73, no. 6. pp. 1029–1045.

3. Rasch, G., Probabilistic Models for Some Intelligence and Attainment Tests, Chicago: Univ. of Chicago Press, 1980.

4. Kibzun, A.I. and Inozemtsev, A.O., Using the Maximum Likelihood Method to Estimate Test Complexity Levels, Autom. Remote Control, 2014, vol. 75, no. 4, pp. 607–621.

5. Nocedal, J. and Wright, S.J., Numerical Optimization, New York: Springer, 2006, 2nd ed.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Intellectual Mathematical Support Software and Inner Architecture of LMS MAI CLASS.NET;Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software";2021

2. Interdisciplinary Aspects of Development and Software Implementation of Electronic Textbooks for Students of Technical Universities;Communications in Computer and Information Science;2020