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Regional differences in Italian students’ performance: a simulation model
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Jan 12, 2017
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Abstract
This work presents the first results of a research project seeking to build a simulation model able to reproduce the differences of Italian students’ performance at regional level. A preliminary qualitative cause-and-effect model defines the main variable involved in the inter-generational skill formation processes, as well as their interplay with the job market context and the triggering of motivational forces for new skill acquisition. Such model was designed according to a system dynamics perspective, considered suitable for capturing the interrelatedness of key variables and for providing useful simulation tools to conduct and communicate future scenario analyses.   Â
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Keywords: regional difference; educational achievement; system dynamics; PISA;
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Regional differences in Italian students’ performance: a simulation model. (2017). New Trends and Issues Proceedings on Humanities and Social Sciences, 2(5). Retrieved from https://un-pub.eu/ojs/index.php/pntsbs/article/view/1117
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References
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Benabou, R. (2002). Tax and education policy in a heterogeneous agent economy: what levels of redistribution maximize growth and efficiency? Econometrica, 70(2), 481–517. http://doi.org/10.1111/1468-0262.00293
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http://doi.org/10.1016/B978-0-444-53429-3.00002-8
INVALSI (2013). OCSE PISA 2012 Rapporto Nazionale, Retrieved from http://www.invalsi.it/invalsi/ri/pisa2012/rappnaz/Rapporto_NAZIONALE_OCSE_PISA2012.pdf
López, L., Guevara, P., & Zúñiga-Saenz, R. G. (2005). Forecasting Primary Education Efficiency. In Proceedings of the 23rd International Conference of the System Dynamics Society, July 17-21, Boston
Matteucci, M., & Mignani, S. (2014). Exploring regional differences in the reading competencies of Italian students. Evaluation Review, 38(3), 251–290. doi: 10.1177/0193841X14540289
OECD. (2013). PISA 2012 results: Ready to learn. Students’ engagement, drive and self-beliefs (Volume III). Retrieved from https://www.oecd.org/pisa/keyfindings/PISA-2012-results-volume-III.pdf
Ponzo, M. (2011). The effects of school competition on the achievement of Italian students. Managerial and Decision Economics, 32(1), 53–61. http://doi.org/10.1002/mde.1517
Richardson, G. P. (1991). System dynamics: Simulation for policy analysis from a feedback perspective. In P. A. Fishwick & P. A. Luker (Eds.), Qualitative Simulation Modeling and Analysis (pp. 144–169). New York, NY: Springer New York. http://doi.org/10.1007/978-1-4613-9072-5_7
Scholl, H. J. (2001). Agent-based and system dynamics modeling: A call for cross study and joint research. In Proceedings of the 34th Hawaii International Conference on System Sciences (pp. 1-8). http://doi.org/10.1109/HICSS.2001.926296
Seta, L., Pipitone, V., Gentile, M., & Allegra, M. (2014). A model to explain Italian regional differences in PISA 2009 outcomes. Procedia: Social & Behavioral Sciences, 143, 185–189. doi: http://dx.doi.org/10.1016/j.sbspro.2014.07.384
Shonkoff, J. P., & Phillips, D. A. (2000). From neurons to neighborhoods: The science of early childhood development. National Academies Press
Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. Boston: Irwin/McGraw-Hill.
Sterman, J. (2014). Interactive web-based simulations for strategy and sustainability: The MIT Sloan LearningEdge management flight simulators, Part II. System Dynamics Review, 30(3), 206–231. http://doi.org/10.1002/sdr.1519
Winch, G. W. (2001). Management of the “skills inventory†in times of major change. System Dynamics Review, 17(2), 151–159. http://doi.org/10.1002/sdr.208
Aiyagari, S. R., Greenwood, J., & Seshadri, A. (2002). Efficient investment in children. Journal of Economic Theory, 102(2), 290–321. http://doi.org/10.1006/jeth.2001.2852
Barlas, Y., & Diker, V. G. D. (2000). A dynamic simulation game (UNIGAME) for strategic university management. Simulation & Gaming, 31(3), 331–358. http://doi.org/10.1177/104687810003100302
Becker, G. S., & Tomes, N. (1979). An equilibrium theory of the distribution of income and intergenerational mobility. The Journal of Political Economy, 87(6), 1153–1189. http://doi.org/10.2307/1833328
Benadusi, L., & Giancola, O. (2014). Saggio introduttivo: sistemi di scuola secondaria comprensivi versus selettivi. Una comparazione in termini di equità. Scuola Democratica, 2, pp. 461-482. Retreived from: https://www.rivisteweb.it/doi/10.12828/77426
Bratti, M., Checchi, D., & Filippin, A. (2007). Geographical differences in Italian students’ mathematical competencies: evidence from Pisa 2003. Giornale Degli Economisti E Annali Di Economia, 33(3), 299–331.
Benabou, R. (2002). Tax and education policy in a heterogeneous agent economy: what levels of redistribution maximize growth and efficiency? Econometrica, 70(2), 481–517. http://doi.org/10.1111/1468-0262.00293
Clauset, K.H., Jr. & Gaynor, A.K. (1982). Effective schooling: a systems perspective. Educational Leadership, 40(3), 54-59.
Cunha, F., & Heckman, J. (2007). The technology of skill formation. In American Economic Review (Vol. 97, pp. 31–47). http://doi.org/10.1257/aer.97.2.31
Cunha, F., Heckman, J., & Schennach, S. (2010). Estimating the technology of cognitive and noncognitive skill formation. Econometrica, 78(3), 883–931. http://doi.org/10.3982/ECTA6551
Conte, R., Gilbert, N., & Sichman, J. S. (1998). MAS and social simulation: a suitable sommitment. Proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation, (1), 1–9. http://doi.org/10.1007/10692956_1
Coleman, J. S., Campbell, H. Q., Hobson, C. J., McPartland, J., Mood, A. M., Weinfeld, F. D., & York, R. L. (1966). Equality of educational opportunity. Washington, DC: US Department of Health, Education & Welfare. Office of Education
Deci, E. L., & Ryan, R. M. (1988). Intrinsic motivation and self-determination in human behavior. Contemporary Sociology (Vol. 17). http://doi.org/10.2307/2070638
Diawati, L., Kawashima, H., & Hayashi, Y. (1994). Skill formation and its impact on the adaptation process of new production systems. System Dynamics Review, 10(1), 29–47. http://doi.org/10.1002/sdr.4260100103
Dweck, C. S., & Elliott, E. S. (1983). Achievement motivation. Handbook of child psychology, 4, 643–691. http://doi.org/10.1016/B978-0-12-373951-3.00002-8
Eccles, J. S., Adler, T., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., & Midgley, C. (1983). Expectancies, Values, and Academic Behaviors. Achievement and Achievement Motivation. http://doi.org/10.1207/s15327752jpa8502
Forrester, J. W. (1958). Industrial dynamics: a major breakthrough for decision makers. Harvard Business Review, 37-66, retrieved from:
http://www.lottepiil.dk/kandidat/Industrial Dynamics (Forrester 1958).pdf
Forrester, J. W. (1969). Urban Dynamics. Portland, OR: Productivity Press.
GERESE (2005). L´equite des systemes educatifs europeens. Un ensemble d´indicateurs. Liege: Commission Europeene. Direction generale de l´education et de la culture.
Grolnick, W. S., Friendly, R., & Bellas, V. (2009). Parenting and children’s motivation at school. Handbook of Motivation at School, (1966), 279–300. Retrieved from http://books.google.com/books?hl=nl&lr=&id=P5GOAgAAQBAJ&pgis=1
Hanushek, E. A., & Woessmann, L. (2011). The economics of international differences in educational achievement. In E.A. Hanushek, S. Machin, and L. Woessmann (Eds). Handbook of the Economics of Education, (pp. 165-172). The Netherlands: North-Holland
http://doi.org/10.1016/B978-0-444-53429-3.00002-8
INVALSI (2013). OCSE PISA 2012 Rapporto Nazionale, Retrieved from http://www.invalsi.it/invalsi/ri/pisa2012/rappnaz/Rapporto_NAZIONALE_OCSE_PISA2012.pdf
López, L., Guevara, P., & Zúñiga-Saenz, R. G. (2005). Forecasting Primary Education Efficiency. In Proceedings of the 23rd International Conference of the System Dynamics Society, July 17-21, Boston
Matteucci, M., & Mignani, S. (2014). Exploring regional differences in the reading competencies of Italian students. Evaluation Review, 38(3), 251–290. doi: 10.1177/0193841X14540289
OECD. (2013). PISA 2012 results: Ready to learn. Students’ engagement, drive and self-beliefs (Volume III). Retrieved from https://www.oecd.org/pisa/keyfindings/PISA-2012-results-volume-III.pdf
Ponzo, M. (2011). The effects of school competition on the achievement of Italian students. Managerial and Decision Economics, 32(1), 53–61. http://doi.org/10.1002/mde.1517
Richardson, G. P. (1991). System dynamics: Simulation for policy analysis from a feedback perspective. In P. A. Fishwick & P. A. Luker (Eds.), Qualitative Simulation Modeling and Analysis (pp. 144–169). New York, NY: Springer New York. http://doi.org/10.1007/978-1-4613-9072-5_7
Scholl, H. J. (2001). Agent-based and system dynamics modeling: A call for cross study and joint research. In Proceedings of the 34th Hawaii International Conference on System Sciences (pp. 1-8). http://doi.org/10.1109/HICSS.2001.926296
Seta, L., Pipitone, V., Gentile, M., & Allegra, M. (2014). A model to explain Italian regional differences in PISA 2009 outcomes. Procedia: Social & Behavioral Sciences, 143, 185–189. doi: http://dx.doi.org/10.1016/j.sbspro.2014.07.384
Shonkoff, J. P., & Phillips, D. A. (2000). From neurons to neighborhoods: The science of early childhood development. National Academies Press
Sterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. Boston: Irwin/McGraw-Hill.
Sterman, J. (2014). Interactive web-based simulations for strategy and sustainability: The MIT Sloan LearningEdge management flight simulators, Part II. System Dynamics Review, 30(3), 206–231. http://doi.org/10.1002/sdr.1519
Winch, G. W. (2001). Management of the “skills inventory†in times of major change. System Dynamics Review, 17(2), 151–159. http://doi.org/10.1002/sdr.208