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Spatial Models for Identifying Factors in Student Academic Achievement

Year 2020, Volume: 7 Issue: 4, 735 - 752, 20.12.2020
https://doi.org/10.21449/ijate.722460

Abstract

In the literature, estimation results of the determinants of academic achievement are controversial. There may be several reasons for these controversial results, including sample or cultural differences. Conversely, these results may arise from ignoring certain important facts, such as an interaction effect. Some studies do not consider interactions among students, and some studies may not use effective models. Surprisingly, very few studies have focused on student academic achievement using spatial models, which may be one of the most suitable models for testing interaction effects. In this study, we estimated student achievement using spatial models and a data sets from Turkey. We observed an interaction between students who live in the same neighbourhood and found evidence of an interaction among students in terms of their achievement based on a spatial error model.

References

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  • Bayer, P., Hjalmarsson, R., & Pozen, D. (2009). Building criminal capital behind bars: Peer effects in juvenile corrections. The Quarterly Journal of Economics, 124(1), 105–147. https://doi.org/10.3386/w12932
  • Bernheim, B. D. (1994). A theory of conformity. Journal of Political Economy, 102, 841-877. https://doi.org/10.1086/261957
  • Blatchford, P., & Mortimore, P. (1994). The issue of class size for young children in schools: What can we learn from the research?. Oxford Review of Education, 20(4), 411-428. https://doi.org/10.1080/0305498940200402
  • Booth, A., & Kee, H. (2006). Birth order matters: The effect of family size and birth order on educational attainment. Journal of Population Economics, 22(2), 367 397. https://doi.org/10.1007/s00148-007-0181-4
  • Brannstrom, L. (2008). Making their mark: The effects of neighbourhood and upper secondary school on educational achievement. European Sociological Review, 24(4), 463–478. https://doi.org/10.1093/esr/jcn013
  • Bray, M. (2013). Shadow education: comparative perspectives on the expansion and implications of private supplementary tutoring. Procedia - Social and Behavioral Sciences, 77(22), 412-420. https://doi.org/10.1016/j.sbspro.2013.03.096
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  • Dincer, M. A. & Uysal, G. (2010). The determinants of student achievement in Turkey, International Journal of Educational Development, 30(6), 592 598. https://doi.org/10.1016/j.ijedudev.2010.05.005
  • Dubow, E.F., Boxer, P., & Huesmann, L. R. (2009). Long-term effects of parents’ education on children’s educational and occupational success: Mediation by family interactions, child aggression, and teenage aspirations, Merrill-Palmer Quarterly, 55(3), 224-249. https://doi.org/10.1353/mpq.0.0030
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  • Elhorst, J. P. (2010). Dynamic panels with endogenous interaction effects when T is small, Regional Science and Urban Economics, 40(5), 272 282. https://doi.org/10.1016/j.regsciurbeco.2010.03.003
  • Elhorst, J. P. (2013). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer-Verlag.
  • Elhorst, P., Zandberg, E., & de Haan, J. (2013). The impact of interaction effects among neighbouring countries on financial liberalization and reform: A dynamic spatial panel data approach. Spatial Economic Analysis, 8(3), 293 313. https://doi.org/10.1080/17421772.2012.760136
  • Ertur, C., & Koch, W. (2007). Growth, technological interdependence and spatial externalities: Theory and evidence. Journal of Applied Econometrics, 22(6), 1033 1062. https://doi.org/10.1002/jae.963
  • Evans, W. N., Oates, W. E., & Schwab, R. M. (1992). Measuring peer group effects: A study of teenage behavior. The Journal of Political Economy, 100(5), 966-991. https://doi.org/10.1086/261848
  • Farber, A., Huu Tu, N., Tran, D., & Vuong, Q. H. (2008). The financial storms in Vietnam's transition economy: A reasoning on the 1991-2008 period. Working Papers CEB, ULB.
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  • Fowler, M. G., Davenport, M. G., & Garg, R. (1992). School functioning of US children with asthma. Pediatrics, 90(6), 939-944.
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  • Gould, E., Lavy, V., & Paserman, S. D. (2009). Sixty years after the magic carpet ride: The long-run effect of the early childhood environment on social and economic outcomes. Review of Economic Studies, 78(3), 938-973. https://doi.org/10.3386/w14884
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  • Hanushek, E. A. (1979). Conceptual and empirical issues in the estimation of educational production functions. Journal of Human Resources, 14(3), 351 88. https://doi.org/10.2307/145575
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Spatial Models for Identifying Factors in Student Academic Achievement

Year 2020, Volume: 7 Issue: 4, 735 - 752, 20.12.2020
https://doi.org/10.21449/ijate.722460

Abstract

In the literature, estimation results of the determinants of academic achievement are controversial. There may be several reasons for these controversial results, including sample or cultural differences. Conversely, these results may arise from ignoring certain important facts, such as an interaction effect. Some studies do not consider interactions among students, and some studies may not use effective models. Surprisingly, very few studies have focused on student academic achievement using spatial models, which may be one of the most suitable models for testing interaction effects. In this study, we estimated student achievement using spatial models and a data sets from Turkey. We observed an interaction between students who live in the same neighbourhood and found evidence of an interaction among students in terms of their achievement based on a spatial error model.

References

  • Aaronson, D. (1998). Using sibling data to estimate the impact of neighborhoods on children’s educational outcomes. Journal of Human Resources, 33, 915 946. https://doi.org/10.2307/146403
  • Adejoro, O. E. (2016), Does location also matter? A spatial analysis of social achievements of young south Australians [Unpublished Master Thesis]. Department of Physical Geography and Ecosystem Science, Lund University, Lund, 2016.
  • Akerhielm, K. (1995). Does class size matter?. Economics of Education Review, 14(3), 229-241. https://doi.org/10.1016/0272-7757(95)00004-4
  • Akerlof, G. A. (1997). Social distance and social decisions. Econometrica, 65(5), 1005-1027. https://doi.org/10.2307/2171877
  • Anselin, L. (1988). Spatial Econometrics: Methods and Models. Springer Science & Business Media.
  • Aslund, O., Edin, Per-Anders, Fredriksson, P., & Grönqvist, H. (2011). Peers, neighborhoods, and immigrant student achievement: evidence from a placement policy. American Economic Journal: Applied Economics, 3(2), 67-95. https://doi.org/10.1257/app.3.2.67
  • Bayer, P., Hjalmarsson, R., & Pozen, D. (2009). Building criminal capital behind bars: Peer effects in juvenile corrections. The Quarterly Journal of Economics, 124(1), 105–147. https://doi.org/10.3386/w12932
  • Bernheim, B. D. (1994). A theory of conformity. Journal of Political Economy, 102, 841-877. https://doi.org/10.1086/261957
  • Blatchford, P., & Mortimore, P. (1994). The issue of class size for young children in schools: What can we learn from the research?. Oxford Review of Education, 20(4), 411-428. https://doi.org/10.1080/0305498940200402
  • Booth, A., & Kee, H. (2006). Birth order matters: The effect of family size and birth order on educational attainment. Journal of Population Economics, 22(2), 367 397. https://doi.org/10.1007/s00148-007-0181-4
  • Brannstrom, L. (2008). Making their mark: The effects of neighbourhood and upper secondary school on educational achievement. European Sociological Review, 24(4), 463–478. https://doi.org/10.1093/esr/jcn013
  • Bray, M. (2013). Shadow education: comparative perspectives on the expansion and implications of private supplementary tutoring. Procedia - Social and Behavioral Sciences, 77(22), 412-420. https://doi.org/10.1016/j.sbspro.2013.03.096
  • Brock, W. A., & Durlauf, S. N. (2001). Discrete choice with social interactions. The Review of Economic Studies, 68(2), 235-260. https://doi.org/10.1111/1467-937X.00168
  • Bronfenbrenner, U. (1994). Ecological models of human development. Readings on the Development of Children, 2(1), 37-43.
  • Brooks-Gunn, J., Duncan, G. J., Klebanov, P. K., & Sealand, N. (1993). Do neighborhoods influence child and adolescent development?. American Journal of Sociology, 99, 353-95. https://doi.org/10.1086/230268
  • Coleman, J. S. (1961). The adolescent society: the social life of the teenager and its impact on education. Free Press of Glencoe.
  • Correa, H. (1993). An economic analysis of class size and achievement in education. Education Economics, 1(2), 129-35. https://doi.org/10.1080/09645299300000019
  • Dietz, R. D. (2002). The estimation of neighborhood effects in the social sciences: An interdisciplinary approach. Social Science Research, 31(4), 539 575. https://doi.org/10.1016/S0049-089X(02)00005-4
  • Dincer, M. A. & Uysal, G. (2010). The determinants of student achievement in Turkey, International Journal of Educational Development, 30(6), 592 598. https://doi.org/10.1016/j.ijedudev.2010.05.005
  • Dubow, E.F., Boxer, P., & Huesmann, L. R. (2009). Long-term effects of parents’ education on children’s educational and occupational success: Mediation by family interactions, child aggression, and teenage aspirations, Merrill-Palmer Quarterly, 55(3), 224-249. https://doi.org/10.1353/mpq.0.0030
  • Duncan, G. J., Yeung, W. J., Brooks-Gunn, J., & Smith, J. R. (1998). How much does childhood poverty affect the life chances of children?. American Sociological Review, 63(3), 406-423. https://doi.org/10.2307/2657556
  • Duncan, G., & Magnuson, K. (2005). Can family socioeconomic resources account for racial and ethnic test score gaps?. Future of Children, 15(1), 35 54. https://doi.org/10.1353/foc.2005.0004
  • Duncan, G J. (1994). Families and neighbors as sources of disadvantage in the schooling decisions of black and white adolescents. American Journal of Education, 103(1), 20-53. https://doi.org/10.1086/444088
  • Elhorst, J. P. (2010). Dynamic panels with endogenous interaction effects when T is small, Regional Science and Urban Economics, 40(5), 272 282. https://doi.org/10.1016/j.regsciurbeco.2010.03.003
  • Elhorst, J. P. (2013). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer-Verlag.
  • Elhorst, P., Zandberg, E., & de Haan, J. (2013). The impact of interaction effects among neighbouring countries on financial liberalization and reform: A dynamic spatial panel data approach. Spatial Economic Analysis, 8(3), 293 313. https://doi.org/10.1080/17421772.2012.760136
  • Ertur, C., & Koch, W. (2007). Growth, technological interdependence and spatial externalities: Theory and evidence. Journal of Applied Econometrics, 22(6), 1033 1062. https://doi.org/10.1002/jae.963
  • Evans, W. N., Oates, W. E., & Schwab, R. M. (1992). Measuring peer group effects: A study of teenage behavior. The Journal of Political Economy, 100(5), 966-991. https://doi.org/10.1086/261848
  • Farber, A., Huu Tu, N., Tran, D., & Vuong, Q. H. (2008). The financial storms in Vietnam's transition economy: A reasoning on the 1991-2008 period. Working Papers CEB, ULB.
  • Fisher, S., Frazer, N. &Murray, K. (1986). Homesickness and health in boarding school children. Journal of Environmental Psychology, 6(1), 35 47. https://doi.org/10.1016/S0272-4944(86)80033-0
  • Fowler, M. G., Davenport, M. G., & Garg, R. (1992). School functioning of US children with asthma. Pediatrics, 90(6), 939-944.
  • Gibbons, S., Silva, S., & Weinhardt, F. (2013). Everybody needs good neighbours? Evidence from students’ outcomes in England. The Economic Journal, 123(571), 831-874. https://doi.org/10.1111/ecoj.12025
  • Gould, E., Lavy, V., & Paserman, S. D. (2009). Sixty years after the magic carpet ride: The long-run effect of the early childhood environment on social and economic outcomes. Review of Economic Studies, 78(3), 938-973. https://doi.org/10.3386/w14884
  • Hanushek, E. A. (1997). Assesing the effect of school resources on student performace: An update. Educational Evoluation and Policy Analysis, 19(2), 141 164. https://doi.org/10.3102/01623737019002141
  • Hanushek, E. A. (1979). Conceptual and empirical issues in the estimation of educational production functions. Journal of Human Resources, 14(3), 351 88. https://doi.org/10.2307/145575
  • Heck, R. H. (2009). Teacher effectiveness and student achievement: Investigating a multilevel cross-classified model. Journal of Education Administration, 7(22), 227-249. https://doi.org/10.1108/09578230910941066
  • Hopland, A. O. (2012). School Building Conditions and Student Achievement: Norwegian Evidence. Working Paper No. 2/2012, Department of Economics, Norwegian University of Science and Technology.
  • Hoxby, C. M. (2000). Peer Effects in the Classroom: Learning from Gender and Race Variation, NBER Working Paper no. 7867, National Bureau of Economic Research.
  • Hsieh, C. S., & Lin, X (2019), Social Interactions and Social Preferences in Social Networks, Working Paper.
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There are 88 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Articles
Authors

Filiz Akbaş-yeşilyurt 0000-0003-1629-4747

Hüseyin Koçak 0000-0001-9683-6096

Muhammet Ensar Yeşilyurt 0000-0001-5610-3146

Publication Date December 20, 2020
Submission Date April 18, 2020
Published in Issue Year 2020 Volume: 7 Issue: 4

Cite

APA Akbaş-yeşilyurt, F., Koçak, H., & Yeşilyurt, M. E. (2020). Spatial Models for Identifying Factors in Student Academic Achievement. International Journal of Assessment Tools in Education, 7(4), 735-752. https://doi.org/10.21449/ijate.722460

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