What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation

Huping Shang; Qingying Han; Yan Li

doi:10.29333/ejmste/89519

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Huping Shang ¹, Qingying Han ¹, Yan Li ² ^*

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¹ Zhou Enlai School of Government, Nankai University, Tianjin CHINA² Division of Hunanities and Social Sciences, Dalian University of Technology, Dalian CHINA^* Corresponding Author

Abstract

How to predict the performance of an applicant is a core issue in the process of research project funding. Unlike the traditional way, we use a back-chaining evaluation method to test what factors of an applicant are influencing the performance of the research project based on the data of Chinese National Science Foundation. We find that the gender never affects the performance, and the age group of 41-45 is significantly helpful in improving the performance, but the age group of 46-50 obviously does harm in improving the performance. What’s more, the affiliation of 211-poject university could do good to the performance, while the educational or academic titles of academician and Yangtze River Scholar prevent the applicants from improving their performances. According to these findings, we advice to take the measures of implementing some specific research projects, some special projects, and some exclusive projects to varied research groups to improve the research performance.

Keywords

research performance
back-chaining performance evaluation
applicant
influencing factors

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2018, Volume 14, Issue 7, 2803-2815

https://doi.org/10.29333/ejmste/89519

Publication date: 26 Apr 2018

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References

Bentley, J. T., & Adamson, R. (2003). Gender differences in the careers of academic scientists and engineers: A literature review (Special report), National Science Foundation. Retrieved from http://www.nsf.gov/sbe/srs/nsf03322/pdf/nsf03322.pdf.
Bornmann, L., & Daniel, H. D. (2005). Selection of research fellowship recipients by committee peer review: Reliability, fairness and predictive validity of board of trustees’ decisions. Scientometrics, 63(2), 297-320. https://doi.org/10.1007/s11192-005-0214-2.
Brouns, M. (2000). The gendered nature of assessment procedures in scientific research funding: The Dutch case. Higher Education in Europe, 25(2), 193-199. https://doi.org/10.1080/713669261.
Ceci, S. J., & Williams, W. M. (2011). Understanding current causes of women’s underrepresentation in science. Proceedings of the National Academy of Sciences, 108(8), 3157-3162. https://doi.org/10.1073/pnas.1014871108.
Chan, Y., & Walmsley, R. P. (1997). Learning and understanding the Kruskal-Wallis one-way analysis-of-variance-by-ranks test for differences among three or more independent groups. Physical therapy, 77(12), 1755-1761. https://doi.org/10.1093/ptj/77.12.1755.
Chinese State Statistical Bureau, Chinese Ministry of Science and Technology, & Chinese Ministry of Finance. (2010). Statistical Bulletin of National Scientific Input in 2010 [in Chinese]. http://www.most.gov.cn/kjbgz/201109/t20110927_89857.htm.
Daniel, H. D. (1993). Guardians of Science: Fairness and Reliability of Peer Review. New York: VCH Verlagsgesellschaft mbH. https://doi.org/10.1002/3527602208.
Demicheli, V., & Di Pietrantonj, C. (2007). Peer review for improving the quality of grant applications. Cochrane Database of Systematic Reviews, (2). https://doi.org/10.1002/14651858.MR000003.pub2.
Deng, G. H., Guo, J., & Zhang, X. Q. (2009). Studies in review system of scientific research project approval [in Chinese]. Scientific Research Management, (1), 49-55.
Fagerland, M. W., & Sandvik, L. (2009). The wilcoxon–mann–whitney test under scrutiny. Statistics in Medicine, 28(10), 1487-1497. https://doi.org/10.1002/sim.3561.
Hartmann, I. (1990). Begutachtung in der Forschungsfo¨rderung. Die Argumente der Gutachter in der Deutschen Forschungsgemeinschaft. Frankfurt: R.G. Fischer.
Hartmann, I., & Neidhardt, F. (1990). Peer review at the Deutsche Forschungsgemeinschaft. Scientometrics, 19(5), 419-425. https://doi.org/10.1007/BF02020704.
Henderson, T., & Taylor, K. (2009). Eye on the horizon-evaluating the impact of the CSIRO Flagship Program. Poster at the 11th Annual Conference of the Australasian Research Management Society (ARMS). Retrieved on November 2009 from http://www.arms2009.org/.
Horner, K. L., Rushton, J. P., & Vernon, P. A. (1986). Relation between aging and research productivity of academic psychologists. Psychology and Aging, 1(4), 319.
Jin, T. J., & Yuan, J. J. (2011). Relation mode between government and enterprise and the revolute rules [in Chinese]. Social Science in China, (1), 102-118.
Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of econometrics, 90(1), 1-44. https://doi.org/10.1016/S0304-4076(98)00023-2.
Kyvik, S. (1990). Age and scientific productivity. Differences between fields of learning. Higher Education, 19(1), 37-55. https://doi.org/10.1007/BF00142022.
Langfeldt, L. (2001). The decision-making constraints and processes of grant peer review, and their effects on the review outcome. Social Studies of Science, 31(6), 820-841. https://doi.org/10.1177/030631201031006002.
Liu, J. R., Zhu, Y., & Wang, Y. Z. (2005). Rational analysis of cadres with double duties at colleges and universities [in Chinese]. Higher Engineering Education Research, (6), 48-50.
Liu, Z. Y. (2004). Review for scientific research project approval in the process of government funding [in Chinese]. Basic Science in China, (4), 46-49.
Merton, R. K. (1973). The Sociology of Science: Theoretical and Empirical Investigations. Chicago and London: The University of Chicago Press. https://doi.org/10.1126/science.184.4137.656.
Reinhart, M. (2009). Peer review of grant applications in biology and medicine. Reliability, fairness, and validity. Scientometrics, 81(3), 789-809. https://doi.org/10.1007/s11192-008-2220-7.
Shang, H. P., & Yu, W. X. (2013). Assessing Chinese managerial competencies from different perspectives. Social Behavior and Personality: an International Journal, 41(9), 1469-1485. https://doi.org/10.2224/sbp.2013.41.9.1469.
Shang, H. P., Jin, T. J., & Liu, W. (2016). Is harmony still in the local socialist officials’ hearts: An exploratory assessment of Chinese county and department level officials? Chinese Management Studies, 10(3), 480-509. https://doi.org/10.1108/CMS-07-2015-0152.
Shang, H. P., Ye, J., & Zhao, P. P. (2012). Public finance efficiency of scientific research in China: low efficiency, ineffectiveness and waste [in Chinese]. Studies in Science of Science, (10), 1470-1472.
Shen, W. Q. (2010-9-7). Scientific research funding should be away from power and ways of people [in Chinese]. People’s Daily.
Shi, X. Q., & Fan, Z. Q. (2007). Data analysis and statistical modeling/statistical method in social science research [in Chinese]. Shanghai: Shanghai People’s Publishing House.
Shi, Y., & Rao, Y. (2010). China’s research culture [in Chinese]. Science, 329(5996), 1128-1128.
Wan, G. (2013). Rage and distress about scientific research corruption [in Chinese]. Retrieved from http://news.sohu.com/20131012/n388014946.shtml.
Wang, P. T. (1983). Factors in raising scientific efficiency [in Chinese]. Scientology and S&T Management, (5), 38-39.
Xu, B. (2012). Scientific research funds increase year by year [in Chinese]. Retrieved from http://www.cnstock.com/roll/201207/2125554.htm.
Zhou, C. X. (2006). Approval of scientific research project based on grey theory [in Chinese]. Scientology and S&T management, (4), 39-43.

How to cite this article

APA

Shang, H., Han, Q., & Li, Y. (2018). What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation. Eurasia Journal of Mathematics, Science and Technology Education, 14(7), 2803-2815. https://doi.org/10.29333/ejmste/89519

Vancouver

Shang H, Han Q, Li Y. What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation. EURASIA J Math Sci Tech Ed. 2018;14(7):2803-15. https://doi.org/10.29333/ejmste/89519

AMA

Shang H, Han Q, Li Y. What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation. EURASIA J Math Sci Tech Ed. 2018;14(7), 2803-2815. https://doi.org/10.29333/ejmste/89519

Chicago

Shang, Huping, Qingying Han, and Yan Li. "What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation". Eurasia Journal of Mathematics, Science and Technology Education 2018 14 no. 7 (2018): 2803-2815. https://doi.org/10.29333/ejmste/89519

Harvard

Shang, H., Han, Q., and Li, Y. (2018). What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation. Eurasia Journal of Mathematics, Science and Technology Education, 14(7), pp. 2803-2815. https://doi.org/10.29333/ejmste/89519

MLA

Shang, Huping et al. "What Factors of the Applicants are Influencing the Performance of Research Science Education? A Back-chaining Evaluation Based on the Data of China National Science Foundation". Eurasia Journal of Mathematics, Science and Technology Education, vol. 14, no. 7, 2018, pp. 2803-2815. https://doi.org/10.29333/ejmste/89519