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Paper
Title

Data mining to predict the performance of the staffs in elementary schools

سومین کنفرانس بین المللی مدیریت در قرن 21
Year: 1395
Publish place:
COI: ICMNG03_159
Language: EnglishView: 496
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Authors

Reza Samizadeh - Faculty member of Industrial Engineering, Alzahra University, Tehran, Iran
Solaleh Sadat Kalantari Kohbanani - PhD student of Industrial Engineering, Alzahra University, Tehran, Iran

Abstract:

One of the most important elements to promote the level of an educational system is inviting staff with a proper and acceptable performance. Hence, predicting staff ` performance is critical. There are many valuable researches in educational data mining. But they concentrate on predicting students more than staff. Therefore this study addresses the predicting performance of the staffs in elementary schools. We apply data mining tools to do the mentioned object. Nine variables which are seems to have more contribution on staff` s performance are considered and then results related in classification coming through decision tree and clustering from Simple K-Means clustering algorithm are presented. Furthermore Apriori algorithm is used to discover explore association rules. Finally it can be found that degree of education, The relationship between one`s field of study and his career duties and reading daily time are more noticeable parameters to have a higher performance.

Keywords:

Paper COI Code

This Paper COI Code is ICMNG03_159. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/538223/

How to Cite to This Paper:

If you want to refer to this Paper in your research work, you can simply use the following phrase in the resources section:
Samizadeh, Reza and Kalantari Kohbanani, Solaleh Sadat,1395,Data mining to predict the performance of the staffs in elementary schools,سومین کنفرانس بین المللی مدیریت در قرن 21,https://civilica.com/doc/538223

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  • Baker, R. S., & Yacef, K. (2009). The state of ...
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  • Cabrera, D. F. M, & Zareipour, H. (2013). Data association ...
  • Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & This, ...
  • Garcfa, E., Romero, C., Ventura, S., & de Castro, C. ...
  • Gobert, J. D., Kim, Y. J., Sao Pedro, M. A., ...
  • He, W. (2013). Examining students" online interaction in a live ...
  • Kabakchieva, D. (2013). Predicting student performance by using data mining ...
  • Kaur, P., Singh, M.. & Josan, G. S. (2015). Classification ...
  • Kick, M., & Paramythis, A. (2011). Activity sequence modelling and ...
  • Kovacic, Z. J. (2010, June). Early prediction of student Success: ...
  • Kriger, A., Merceron, A., & Wolf, B. (2010, June). A ...
  • Xing, W., Guo, R., Petakovic, E., & Goggins, S. (2015). ...
  • Zengin, K., Esgi, N., Erginer, E., & Aksoy, M. E. ...

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Scientometrics

The specifications of the publisher center of this Paper are as follows:
Type of center: دانشگاه دولتی
Paper count: 7,645
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