Developing Statistical Process Control to Monitor the Values Education Process

Document Type : Research Paper

Authors

1 Ph.D. student, Payame Noor University, Tehran, Iran

2 Iran University of Science and Technology

3 Faculty of Psychology & Educational Sciences – Allameh Tabataba'i University, Tehran, Iran

10.22070/jqepo.2020.4514.1112

Abstract

Statistical process control (SPC) is a leading method in monitoring process performance and detecting process deviations from goals, and measure progress in improving programs. Despite the widespread use of SPC in various processes, its capability has not yet been well studied in the values education process (VEP). Some challenges in using this method were: the lack of appropriate quantitative data for using in the SPC, invalid and untrusted data, the presence of different values that make it difficult to focus on values education, and choosing the proper process characteristic and control charts associated with it. In this paper, a framework is presented to resolve these challenges includes: extracting the quantitative data related to the values using event count items and check sheet, removing invalid data and its sources from the research process through statistical tests, prioritizing values based on four attributes related to values, and finally, measuring the value changes in students as Process characteristic. We used a modified deviation from the nominal (DNOM ) control chart to identify and analyze the VEP changes. The results of a case study at a school were quite promising. It increased team knowledge, helped decision-makers design and improved the VEP, and developed the SPC method capability in a new area.

Keywords


Aliverdi, R., Moslemi Naeni, L., Salehipour, A., (2013). Monitoring project duration and cost in a construction project by applying statistical quality control charts. Int. J. Proj. Manag. 31 (3), 411–423.
Allport, G. W. (1921). Personality and character. Psychological Bulletin, 18, 441-455. Available from http://dx.doi.org/doi:10.1037/h0066265.
Allport.G., Vernon, P., & Lindsey, G. (1960). Study of values. Boston: Houghton Mifflin.
Amiri, A., Ghashghaei, R., & Maleki, M. R. (2018). On the effect of measurement errors in simultaneous monitoring of mean vector and covariance matrix of multivariate processes. Transactions of the Institute of Measurement and Control, 40(1), 318-330.
Ashley L, Armitage G, Neary M, Hollingsworth G. A. (2010). Practical guide to Failure Mode and Effects Analysis in health care: Making the most of the team and its meetings. Joint Commission Journal on Quality and Patient Safety; 36 (8):351-8.
Ashuri, A., Bashiri, M., & Amiri, A. (2018). Preferred Robust Response Surface Design with Missing Observations Based on Integrated TOPSIS-AHP Method. Journal of Quality Engineering and Production Optimization, 3, 1, 81-91.
Aspin, D. (2000). A clarification of some key terms in values discussions. Moral education and pluralism: Education, culture and values, 37, 171-180.
Campbell, J., Jayawickreme, F., Hanson, E., (2015). Measures of Values and Moral Personality. Measures of Personality and Social Psychological Constructs. 505-529.
Carr, L.(1992). Applying cost of quality to a service business, Sloan Manage. Rev, 33, 72–77.
Colin, J., Vanhoucke, M.(2015). Developing a framework for statistical process control approaches in project management, International Journal of Project Management, 33, 6, 1193-1416.
Colnerud, G. (2006).Teacher ethics as a research problems: Syntheses achieved and new issues. Teachers and Teaching: Theory and Practice, 12,365–385.
Ding, Xin., Wardell, Don., Verma, Rohit. (2006). An Assessment of Statistical Process Control-Based Approaches for Charting Student Evaluation Scores. Cornell University School of Hotel Administration. http://scholarship.sha.cornell.edu/articles/532.
Earley, P.C. (1993). East meetsWest meets Mideast: further explorations of collectivistic and individualistic work groups. Academy of Management Journal 36 (2), 319–348.
Fernandez, D.R., Carlson, D.S., Stepina, L.P., et al., (1997). Hofstede's country classification 25 years later. Journal of Social Psychology 137 (1), 43–54.
Fris'en, M., ed. (2008). Financial Surveillance. Hoboken, NJ: John Wiley & Sons, Inc.
Fris'en, M. (2009). "Optimal Sequential Surveillance for Finance, Public Health, and Other Areas (with Discussion)". Sequential Analysis 28, pp. 310–337.
Gholami, A., Maleki,H., Emami,C. (2011). Studying the effectiveness degree of active teaching methods on religious and moral education of students at fifth grade of primary school in Shiraz from teachers' point of view. Procedia Social and Behavioral Sciences, 15, 2132-2136.
Gomaa, A. S., & Birch, J. B. (2019). A semiparametric nonlinear mixed model approach to phase I profile monitoring. Communications in Statistics-Simulation and Computation, 48(6), 1677-1693.
Graham, J., Haidt, J., & Nosek, B. A. (2009). Liberals and conservatives rely on different sets of moral foundations. Journal of Personality and Social Psychology, 96, 10291046. Available from http://dx.doi.org/doi:10.1037/a0015141.
Hacking, I. (1983). Representing and intervening: Introductory topics in the philosophy of natural science. Cambridge: Cambridge University Press.
Hofstede, G. (1991). Cultures and Organizations: Software of Mind. McGraw Hill, London.
Hu, X.; Castagliola, P.; Sun, J.; Khoo, M.B.: The effect of measurement errors on the synthetic  chart. Qual. Reliab. Eng. Int. 31(8), 1769–1778 (2015)
Hu, X.; Castagliola, P.; Sun, J.; Khoo, M.B. (2016). The performance of variable sample size  chart with measurement errors. Qual. Reliab. Eng. Int. 32(3), 969–983.
Kalaei, M., Atashgar, K., Niaki, S. T. A., & Soleimani, P. (2018). Phase I monitoring of simple linear profiles in multistage processes with cascade property. The International Journal of Advanced Manufacturing Technology, 94(5-8), 1745-1757.
Khurshid, A.; Chakraborty, A.B. (2014). Measurement error effect on the power of the control chart for zero-truncated binomial distribution under standardization procedure. Int. J. Qual. Res. 8(4), 495–504.
Inglehart, R., Welzel, C. (2005). Modernization, Cultural Change and Democracy: The Human Development Sequence. Cambridge University Press, New York.
Jones, T. M. (2009). Framing the framework: discourses in Australia's national values education policy. Educational Research for Policy and Practice, 8,35 57.
Knight, J. E., Allen, S., & Tracy, D. L. (2010). Using six sigma methods to evaluate the reliability of a teaching assessment rubric. The Journal for American Academy of Research Cambridge, 15(1), 1-6.
Maleki, M.R.; Amiri, A.; Castagliola, P. (2017). Measurement errors in statistical process monitoring: a literature review. Comput. Ind. Eng. 103, 316–329.
Mann, Henry B.; Whitney, Donald R. (1947). "On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other". Annals of Mathematical Statistics. 18 (1): 50–60. 
Marks, N., & Connell, R. (2003). Using statistical control charts to analyze data from student evaluations of teaching. Decision Sciences Journal of Innovative Education, 1(2), 259– 272.
Mazumder, Q.H. (2014) 'Applying Six Sigma in higher education quality improvement', ASEE Annual Conference and Exposition, 15–18 June, 2014, Indianapolis, IN.
Melvin,C. (1993). Application of Control Charts to an Educational System, Performance Improvement Quarterly, 6(3) pp. 74-85.
Montgomery, D. C. (2009). Introduction to Statistical Quality Control. (7th Ed.). New York: Wiley.
Noorossana,R.;Zerehsaz,Y.:Effect ofmeasurement error on phase IImonitoring of simple linear profiles. Int. J. Adv.Manuf. Technol. 79(9), 2031–2040 (2015).
Oser, F. K., Althof, W., & Higgins-D’Allessandro, A. (2008). The Just Community approach to moral education: System change or individual change? Journal of Moral Education, 37, 395–415.
Perry, L. (2004). Instructional effectiveness: A real-time feedback approach using statistical process control (spc). Proceedings of the 2004 American society for engineering education annual conference & exposition, Utah, USA
Peterson, C., & Seligman, M. E. P. (2004). Character strengths and virtues: A handbook and classification. Washington, DC: American Psychological Association.
Prøitz, T. S., Mausethagen, S., & Skedsmo, G. (2017). Investigative modes in research on data use in education. Nordic Journal of Studies in Educational Policy, 3(1), 42–55. https://doi.org/10.1080/20020317.2017.1326280.
Riaz, M.: Monitoring of process parameters under measurement errors. J. Test. Eval. 42(4), 980–988 (2014).
Rokeach, M. The Nature of Human Values, The Free Press, New York, 1973.
Haridy, Salah, Zhang Wu, Ka Man Lee & M. Abdur Rahim (2014) An attribute chart for monitoring the process mean and variance, International Journal of Production Research, 52:11, 3366-3380, DOI:10.1080/00207543.2013.875234.
Salmasnia, A., Maleki, M. R., & Niaki, S. T. A. (2018). Remedial measures to lessen the effect of imprecise measurement with linearly increasing variance on the performance of the MAX-EWMAMS scheme. Arabian Journal for Science and Engineering, 43(6), 3151-3162.
Schwartz, S. H. (1992). Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In M. Zanna (Ed.), Advances in experimental social psychology (pp. 165). San Diego, CA: Academic Press.
Schwartz, S. H. (2005). Robustness and fruitfulness of a theory of universals in individual values. In A. Tamayo, & J. B. Porto (Eds.), Valores ecomportamento nas organizacoes., Values and behavior in organizations, (pp. 5695). Petropolis, Brazil: Vozes.
Schwartz, S. H. (2006). Value orientations: Measurement, antecedents and consequences across nations. In R. Jowell, C. Roberts, R. Fitzgerald, & G. Eva (Eds.), Measuring attitudes cross-nationally: Lessons from the European Social Survey (pp. 169-204). London: Sage.
Skedsmo, G., Huber, S.G.(2019). Measuring teaching quality some key issues, Educational Assessment, Evaluation and Accountability volume 31, pages151–153.
Taylor, M.(1994). Overview of values education in 26 European countries. InM.Taylor (Ed.), Values education in Europe: A comparative overview of a survey of 26 countries in 1993(pp. 1–66). Dundee:Scottish Consultative Council on the Curriculum.
Taras, V., Steel, P., 2006b. Culture as a consequence: amultilevelmultivariatemeta-analysis of the effects of individual and country characteristics on work-related cultural values. Best Papers Proceedings, the Academy of Management Annual Meeting, Atlanta, GA.
Taras, v., Rowney,j., steel,p.,2009. Half a century of measuring culture: Review of approaches, challenges, and limitations based on the analysis of 121 instruments for quantifying culture. Journal of International Management 15, 357–373.
Thornberg, R. (2008). The lack of professional knowledge in values education. Teaching and Teacher Education, 24, 1791-1798.
Verger, A., Fontdevila, C., & Parcerisa, L. (2019). Reforming governance through policy instruments: How and to what extent standards, tests and accountability in education spread worldwide. Discourse: Studies in the Cultural Politics of Education. https://doi.org/10.1080/01596306.2019.1569882.
Woodall, W. H. (2006). The Use of Control Charts in Health-Care and Public-Health Surveillance. Journal of Quality Technology, Vol. 38, No. 2, April 2006.
Woodall, W. H., and D. C. Montgomery. 2014. Some current directions in the theory and application of statistical process monitoring. Journal of Quality Technology 17:78–94.
Woodall, W. H.; Grigg, O. A.; and Burkom, H. S. (2010). "Research Issues and Ideas on Health-Related Monitoring". In Frontiers in Statistical Quality Control, Lenz, H.-J.; Wilrich, P.-Th.; and Schmid, W. (eds.), vol. 9, 145–155. Heidelberg, Germany: Physica-Verlag.
Yang, S.F.; Yang, C.M., (2005). Effects of imprecise measurement on the two dependent processes control for the autocorrelated observations. Int. J. Adv. Manuf. Technol. 26(5–6), 623–630.