Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Building an automatic analysis system of tests results within the analytical unit of the E-learning system of the mass trade workers in JSC 'Russian Railways'. / Gadasina, L. V.; Sedov, M. S.; Kuranova, O. N.
2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. 7911560.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
}
TY - GEN
T1 - Building an automatic analysis system of tests results within the analytical unit of the E-learning system of the mass trade workers in JSC 'Russian Railways'
AU - Gadasina, L. V.
AU - Sedov, M. S.
AU - Kuranova, O. N.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Main internal HR risks as determined by JSC 'Russian Railways' are risks connected with the training level of its staff. Technical learning is a tool to sustain a high knowledge level of the employees and to assess their knowledge level. Presently, the emphasis is on modern information technologies, namely the e-learning system. Using these systems broadens opportunities to analyze employees learning results and allows real-time recording of potential deficiencies in the training level. However, due to a large number of personnel undergoing trainings, there is a necessity to develop methods for automated evaluation of the obtained results that will assist in managerial decisions. This work suggests a clusterization of the technical study outcome for automatization and also provides the necessary metrics for solving the problem.
AB - Main internal HR risks as determined by JSC 'Russian Railways' are risks connected with the training level of its staff. Technical learning is a tool to sustain a high knowledge level of the employees and to assess their knowledge level. Presently, the emphasis is on modern information technologies, namely the e-learning system. Using these systems broadens opportunities to analyze employees learning results and allows real-time recording of potential deficiencies in the training level. However, due to a large number of personnel undergoing trainings, there is a necessity to develop methods for automated evaluation of the obtained results that will assist in managerial decisions. This work suggests a clusterization of the technical study outcome for automatization and also provides the necessary metrics for solving the problem.
KW - Centroid Method
KW - cluster analysis
KW - Data Mining
KW - E-Learning
KW - technical education
KW - testing results
UR - http://www.scopus.com/inward/record.url?scp=85019260508&partnerID=8YFLogxK
U2 - 10.1109/ICIEAM.2016.7911560
DO - 10.1109/ICIEAM.2016.7911560
M3 - Conference contribution
AN - SCOPUS:85019260508
BT - 2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016
Y2 - 19 May 2016 through 20 May 2016
ER -
ID: 36836359