Teaching strategy specialization and student achievement

References

• Agasisti, T., M. Gil-Izquierdo, and S. W. Han. 2020. “ICT Use at Home for School-Related Tasks: What is the Effect on a Student’s Achievement? Empirical Evidence from OECD PISA Data.” Education Economics 28 (6): 601–620. doi:10.1080/09645292.2020.1822787.
   Web of Science ®Google Scholar
• Agasisti, T., and S. Murtinu. 2012. “‘Perceived’ Competition and Performance in Italian Secondary Schools: New Evidence from OECD—PISA 2006.” British Educational Research Journal 38 (5): 841–858. doi:10.1080/01411926.2011.588314.
   Web of Science ®Google Scholar
• Algan, Y., P. Cahuc, and A. Shleifer. 2013. “Teaching Practices and Social Capital.” American Economic Journal: Applied Economics 5 (3): 189–210. doi: 10.1257/app.5.3.189.
   Web of Science ®Google Scholar
• Altonji, J. G., T. E. Elder, and C. R. Taber. 2008. “Using Selection on Observed Variables to Assess Bias from Unobservables When Evaluating Swan-Ganz Catheterization.” American Economic Review 98 (2): 345–350. doi:10.1257/aer.98.2.345.
   Web of Science ®Google Scholar
• Baumert, J., M. Kunter, W. Blum, M. Brunner, T. Voss, A. Jordan, and Y. M. Tsai. 2010. “Teachers’ Mathematical Knowledge, Cognitive Activation in the Classroom, and Student Progress.” American Educational Research Journal 47 (1): 133–180. doi:10.3102/0002831209345157.
   Web of Science ®Google Scholar
• Bietenbeck, J. 2014. “Teaching Practices and Cognitive Skills.” Labour Economics 30: 143–153. doi:10.1016/j.labeco.2014.03.002.
   Web of Science ®Google Scholar
• Brewer, D. J., and D. D. Goldhaber. 1997. “Why Don't Schools and Teachers Seem to Matter? Assessing the Impact of Unobservables on Educational Productivity.” Journal of Human Resources 32 (3): 505–523. doi:10.2307/146181.
   Web of Science ®Google Scholar
• Caliendo, M., and S. Kopeinig. 2008. “Some Practical Guidance for the Implementation of Propensity Score Matching.” Journal of Economic Surveys 22 (1): 31–72. doi:10.1111/j.1467-6419.2007.00527.x.
   Web of Science ®Google Scholar
• Camburn, E. M., and S. W. Han. 2011. “Two Decades of Generalizable Evidence on U.S. Instruction from National Surveys.” Teachers College Record 113 (3): 561–610. doi:10.1177/016146811111300308
   Web of Science ®Google Scholar
• Campbell, J., L. Kyriakides, D. Muijs, and W. Robinson. 2012. Assessing Teacher Effectiveness: Different Models. London: Routledge Falmer.
   Google Scholar
• Capps, D. K., B. A. Crawford, and M. A. Constas. 2012. “A Review of Empirical Literature on Inquiry Professional Development: Alignment with Best Practices and a Critique of the Findings.” Journal of Science Teacher Education 23 (3): 291–318. doi:10.1007/s10972-012-9275-2.
   Google Scholar
• Caro, D. H., J. Lenkeit, and L. Kyriakides. 2016. “Teaching Strategies and Differential Effectiveness Across Learning Contexts: Evidence from PISA 2012.” Studies in Educational Evaluation 49: 30–41. doi:10.1016/j.stueduc.2016.03.005.
   Web of Science ®Google Scholar
• Cordero, J. M., V. Cristóbal, and D. Santín. 2018. “Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS.” Journal of Economic Surveys 32 (3): 878–915. doi:10.1111/joes.12217.
   Web of Science ®Google Scholar
• Cordero, J. M., and M. Gil-Izquierdo. 2018. “The Effect of Teaching Strategies on Student Achievement: An Analysis Using TALIS-PISA-Link.” Journal of Policy Modeling 40 (6): 1313–1331. doi:10.1016/j.jpolmod.2018.04.003.
   Web of Science ®Google Scholar
• De Witte, K., and C. Van Klaveren. 2014. “How are Teachers Teaching? A Nonparametric Approach.” Education Economics 22 (1): 3–23. doi:10.1080/09645292.2011.560448.
   Google Scholar
• Echazarra, A., D. Salinas, I. Méndez, V. Denis, and G. Rech. 2016. How teachers teach and students learn: Successful strategies for school. In OECD Education Working Papers, no. 130. OECD Publishing, Paris. doi:10.1787/5jm29kpt0xxx-e.
   Google Scholar
• Ehrenberg, R. G., and D. J. Brewer. 1994. “Do School and Teacher Characteristics Matter? Evidence from High School and Beyond.” Economics of Education Review 13 (1): 1–17. doi:10.1016/0272-7757(94)90019-1.
   Google Scholar
• Gao, S. 2014. “Relationship Between Science Teaching Practices and Students’ Achievement in Singapore, Chinese Taipei, and the US: An Analysis Using TIMSS 2011 Data.” Frontiers of Education in China 14 (4): 519–551. doi:10.3868/s110-003-014-0043-x.
   Google Scholar
• Gil-Izquierdo, M., and J. M. Cordero. 2018a. “Guidelines for Data Fusion with International Large Scale Assessments: Insights from the TALIS-PISA Link Database.” Studies in Educational Evaluation 59: 10–18. doi:10.1016/j.stueduc.2018.02.002.
   Web of Science ®Google Scholar
• Gil-Izquierdo, M., and J. M. Cordero. 2018b. “The Effect of Teaching Strategies on Student Achievement: An Analysis Using TALIS-PISA-Link.” Journal of Policy Modeling 40 (6): 1313–1331. doi:10.1016/j.jpolmod.2018.04.003.
   Web of Science ®Google Scholar
• Gil-Izquierdo, M., J. M. Cordero, and V. Cristóbal. 2018. “Teaching Practices and Results in PISA 2015.” Revista de Educación 379: 32–55. DOI: 10.4438/1988-592X-RE-2017-379-368.
   Google Scholar
• Guo, S., and M. W. Fraser. 2010. Propensity Score Analysis. Statistical Methods and Applications. London: SAGE publications.
   Google Scholar
• Gustafsson, J. E. 2013. “Causal Inference in Educational Effectiveness Research: A Comparison of Three Methods to Investigate Effects of Homework on Student Achievement.” School Effectiveness and School Improvement 24 (3): 275–295. doi:10.1080/09243453.2013.806334.
   Web of Science ®Google Scholar
• Hanushek, E. A. 2011. “The Economic Value of Higher Teacher Quality.” Economics of Education Review 30 (3): 466–479. doi:10.1016/j.econedurev.2010.12.006.
   Web of Science ®Google Scholar
• Hanushek, E. A., M. Piopiunik, and S. Wiederhold. 2019. “The Value of Smarter Teachers International Evidence on Teacher Cognitive Skills and Student Performance.” Journal of Human Resources 54 (4): 857–899. DOI: 10.3368/jhr.54.4.0317.8619R1.
   Web of Science ®Google Scholar
• Hattie, J. 2009. Visible Learning: A Synthesis of Over 800 Meta-Analysis Relating to Achievement. Abingdon: Routledge.
   Google Scholar
• Hidalgo, A., and C. López-Mayan. 2018. “Teaching Styles and Achievement: Student and Teacher Perspectives.” Economics of Education Review 67: 184–206. doi:10.1016/j.econedurev.2018.10.009.
   Web of Science ®Google Scholar
• House, J. D. 2009. “Elementary-School Mathematics Instruction and Achievement of Fourth-Grade Students in Japan: Findings from the TIMSS 2007 Assessment.” Education 130 (2): 301–308.
   Google Scholar
• Hox, J. J. 2010. Multilevel Analysis: Techniques and Applications 2nd Edition. New York: Routledge.
   Google Scholar
• INEE. 2011. Evaluación General de Diagnostico 2010. Informe de Resultados. Madrid: Ministerio de Educación.
   Google Scholar
• Koenker, R., and G. Bassett. 1978. “Regression Quantiles.” Econometrica 46 (1): 33–50. doi:10.2307/1913643.
   Web of Science ®Google Scholar
• Lavy, V. 2011. What Makes an Effective Teacher? Quasi-Experimental Evidence. NBER Working Paper 16885. http://www.nber.org/papers/w16885.
   Google Scholar
• Lavy, V. 2015. “Do Differences in Schools’ Instruction Time Explain International Achievement Gaps? Evidence from Developed and Developing Countries.” The Economic Journal 125 (588): F397–F424. doi:10.1111/ecoj.12233.
   Web of Science ®Google Scholar
• Le Donné, N., P. Fraser, and G. Bousquet. 2016. “Teaching Strategies for Instructional Quality: Insights from the TALIS-PISA Link Data.” OECD Education Working Papers, No. 148, Paris: OECD Publishing. doi:10.1787/5jln1hlsr0lr-en.
   Google Scholar
• Machin, S., and S. McNally. 2008. “The Literacy Hour.” Journal of Public Economics 92 (5-6): 1441–1462. doi:10.1016/j.jpubeco.2007.11.008.
   Web of Science ®Google Scholar
• Mancebón, M. J., D. P. Ximénez-de-Embún, M. Mediavilla, and J. M. Gómez-Sancho. 2019. “Does the Educational Management Model Matter? New Evidence from a Quasiexperimental Approach.” Empirical Economics 56 (1): 107–135. doi:10.1007/s00181-017-1351-1.
   Web of Science ®Google Scholar
• Meroni, E. C., E. Vera-Toscano, and P. Costa. 2015. “Can Low Skill Teachers Make Good Students? Empirical Evidence from PIAAC and PISA.” Journal of Policy Modeling 37 (2): 308–323. doi:10.1016/j.jpolmod.2015.02.006.
   Web of Science ®Google Scholar
• Muijs, D., A. Harris, C. Chapman, L. Stoll, and J. Russ. 2004. “Improving Schools in Socioeconomically Disadvantagedareas? A Review of Research Evidence.” School Effectiveness and School Improvement 15 (2): 149–175. doi:10.1076/sesi.15.2.149.30433.
   Web of Science ®Google Scholar
• Murname, R. J., and B. Phillips. 1981. “What do Effective Teachers of Inner-City Children Have in Common?” Social Science Review 10 (1): 83–100. https://doi.org/10.1016/0049-089X(81)90007-7.
   Google Scholar
• O’Dwyer, L. M., Y. Wang, and K. A. Shields. 2015. “Teaching for Conceptual Understanding: A Cross-National Comparison of the Relationship Between Teachers’ Instructional Practices and Student Achievement in Mathematics.” Large-scale Assessments in Education 3 (1): 1–30. doi:10.1186/s40536-014-0011-6.
   Google Scholar
• OECD. 2009. PISA Data Analysis Manual: SPSS. Second Edition. Paris: OECD Publishing.
   Google Scholar
• OECD. 2017. How Your School Compares Internationally: OECD Test For Schools. Paris: OECD Publishing.
   Google Scholar
• OECD. 2022. PISA for Schools. Technical Report. Paris: OECD Publishing.
   Google Scholar
• Oster, E. 2019. “Unobservable Selection and Coefficient Stability: Theory and Evidence.” Journal of Business & Economic Statistics 37 (2): 187–204. doi:10.1080/07350015.2016.1227711.
   Web of Science ®Google Scholar
• Palardy, G. J., and R. W. Rumberger. 2008. “Teacher Effectiveness in First Grade: The Importance of Background Qualifications, Attitudes, and Instructional Practices for Student Learning.” Educational Evaluation and Policy Analysis 30 (2): 111–140. doi:10.3102/0162373708317680.
   Web of Science ®Google Scholar
• Papanastasiou, C. 2008. “A Residual Analysis of Effective Schools and Effective Teaching in Mathematics.” Studies in Educational Evaluation 34 (1): 24–30. doi:10.1016/j.stueduc.2008.01.005.
   Google Scholar
• Rasch, G. 1960/1980. Probabilistic Models for Some Intelligence and Attainment Tests. Copenhagen: Danish Institute for Educational Research.
   Google Scholar
• Rosenbaum, P., and D. Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70 (1): 41–55. doi:10.1093/biomet/70.1.41
   Web of Science ®Google Scholar
• Rosenshine, B., and R. Stevens. 1986. “Teaching Functions.” In Handbook of Research on Teaching: A Project of the American Educational Research Association, edited by M. C. en Wittrock, 376–391. New York: Collier-Macmillan.
   Google Scholar
• Rothstein, J. 2010. “Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement.” Quarterly Journal of Economics 125 (1): 175–214. doi:10.1162/qjec.2010.125.1.175.
   Web of Science ®Google Scholar
• Rowan, B., R. Correnti, and R. J. Miller. 2002. “What Large-Scale, Survey Research Tells us About Teacher Effects on Student Achievement: Insights from the Prospects Study of Elementary Schools.” Teacher College Record 104: 1525–1567. doi:10.1111/1467-9620.00212
   Web of Science ®Google Scholar
• Schacter, J., and Y. M. Thum. 2004. “Paying for Highand low-Quality Teaching.” Economics of Education Review 23: 411–430. doi:10.1016/j.econedurev.2003.08.002.
   Web of Science ®Google Scholar
• Schwerdt, G., and A. C. Wuppermann. 2011. “Is Traditional Teaching Really all That bad? A Within-Student Between-Subject Approach.” Economics of Education Review 30 (2): 365–379. doi:10.1016/j.econedurev.2010.11.005.
   Web of Science ®Google Scholar
• Stuart, E. A., and D. B. Rubin. 2008. “Matching Methods for Causal Inference: Designing Observational Studies.” In Best Practices in Quantitative Methods, edited by J. en Osborne, 155–176. London: Sage.
   Google Scholar
• Thoemmes, F. J., and E. S. Kim. 2011. “A Systematic Review of Propensity Score Methods in the Social Sciences.” Multivariate Behavioral Research 46 (1): 90–118. doi:10.1080/00273171.2011.540475.
   PubMed Web of Science ®Google Scholar
• Vandenberghe, V., and S. Robin. 2004. “Evaluating the Effectiveness of Private Education Across Countries: A Comparison of Methods.” Labour Economics 11 (4): 487–506. doi:10.1016/j.labeco.2004.02.007.
   Web of Science ®Google Scholar
• Van Klaveren, C. 2011. “Lecturing Style Teaching and Student Performance.” Economics of Education Review 30: 729–739. doi:10.1016/j.econedurev.2010.08.007.
   Web of Science ®Google Scholar
• Wilde, E. T., and R. Hollister. 2007. “How Close is Close Enough? Evaluating Propensity Score Matching Using Data from a Class Size Reduction Experiment.” Journal of Policy Analysis and Management 26 (3): 455–477. doi:10.1002/pam.20262.
   Web of Science ®Google Scholar
• Wu, M. 2005. “The Role of Plausible Values in Large-Scale Surveys.” Studies in Educational Evaluation 31 (2-3): 114–128. http://doi.org/10.1016/j.stueduc.2005.05.005.
   Google Scholar
• Xue, Y., and S. Meisels. 2004. “Early Literacy Instruction and Learning in Kindergarten: Evidence from Early Childhood Longitudinal Study-Class of 1998-1999.” American Education Research Journal 41 (2): 191–229. doi:10.3102/00028312041001191.
   Google Scholar
• Yang, Y., and J. E. Gustafsson. 2004. “Measuring Socioeconomic Status at Individual and Collective Levels.” Educational Research and Evaluation 10 (3): 259–288. doi:10.1076/edre.10.3.259.30268.
   Google Scholar
• Zakharov, A., M. Carnoy, and P. Loyalka. 2014. “Which Teaching Practices Improve Student Performance on High-Stakes Exams? Evidence from Russia.” International Journal of Educational Development 36: 13–21. doi:10.1016/j.ijedudev.2014.01.003.
   Web of Science ®Google Scholar
• Zemelman, S., H. Daniels, and A. Hyde. 2005. Best Practice: Today's Standards for Teaching and Learning in America's Schools. Portsmouth: Heinemann.
   Google Scholar
• Zuzovsky, R. 2013. “What Works Where? The Relationship Between Instructional Variables and Schools' Mean Scores in Mathematics and Science in Low-, Medium-and High-Achieving Countries.” Large-Scale Assessments in Education 1 (1): 1–19. doi:10.1186/2196-0739-1-2.
   Google Scholar