Skip to main content
SpringerLink
Log in

Teaching Quality and Student Outcomes in TIMSS and PISA

  • Living reference work entry
  • First Online:
International Handbook of Comparative Large-Scale Studies in Education

Part of the book series: Springer International Handbooks of Education ((SIHE))

Abstract

While there is consensus that teachers’ teaching quality is of utmost importance to student outcomes, conceptualizations and measures differ between studies and countries. Moreover, it is not clear which aspects or dimensions of teaching quality are related to student outcomes, or how this varies across countries. In this chapter, we present a systematic review of TIMSS and a narrative review of PISA focusing on (a) how teaching quality has been measured in these studies, and how this has developed from the early cycles until today; and (b) how teaching quality is related to student outcomes. Both international reports from PISA and TIMSS as well as studies performing secondary analyses based on TIMSS and PISA data are reviewed. Our reviews reveal that the latest cycles of TIMSS and PISA have more extensive frameworks and more reliable measures of teaching quality than previous cycles. Findings on the relations between teaching quality and student outcomes are mixed, but mostly aligned with findings from the field, including longitudinal studies. The results further show that secondary analyses of PISA and TIMSS often suffer from conceptual and methodological flaws. We discuss the implications for policy and practice and contributions to the field of education, and we provide suggestions to enhance the validity of the use of teaching quality measures, such as extending current study designs longitudinally.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

References

  • Adams, R. (Ed.). (2009). PISA 2006 Technical Report. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Adams, R., & Wu, M. (2002). PISA 2000 Technical Report. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Adams, R. J., Lietz, P. & Berezner, A. (2013). On the use of rotated context questionnaires in conjunction with multilevel item response models. Large-scale Assessments in Education, 1(5).

    Google Scholar 

  • Aditomo, A. & Klieme, E. (2020). Forms of inquiry-based science instruction and their relations with learning outcomes: Evidence from high and low-performing education systems. International Journal of Science Education, 42(4), 504–525.

    Google Scholar 

  • Aditomo, A. & Köhler, C. (2020). Do student ratings provide reliable and valid information about teaching quality at the school level? Evaluating measures of science teaching in PISA 2015. Educational Assessment, Evaluation and Accountability, 32(3), 275–310.

    Google Scholar 

  • Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., Klusmann, U., Krauss, S., Neubrand, M. & Tsai, Y. M. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180.

    Google Scholar 

  • Bell, C., Castellano, K., Klieme, E. Schweig, J. & Doan, S. (2021). Measuring Teaching Using Different Modes. Paper presented at the annual meeting of the American Educational Research Association.

    Google Scholar 

  • Bellens, K., Van Damme, J., Van Den Noortgate, W., Wendt, H., & Nilsen, T. (2019). Instructional quality: catalyst or pitfall in educational systems’ aim for high achievement and equity? An answer based on multilevel SEM analyses of TIMSS 2015 data in Flanders (Belgium), Germany, and Norway, Large-scale Assessments in Education, 7.

    Google Scholar 

  • Blömeke, S., & Olsen, R. V. (2019). Consistency of results regarding teacher effects across subjects, school levels, outcomes and countries. Teaching and Teacher Education, 77, 170–182. https://doi.org/10.1016/j.tate.2018.09.018

    Article  Google Scholar 

  • Buchholz, J. & Hartig, J. (2017). Comparing attitudes across groups: An IRT-based item-fit statistic for the analysis of measurement invariance. Applied Psychological Measurement, 43(3), 241–250.

    Google Scholar 

  • Burstein, R. (2014). The IEA study of mathematics III: Student growth and classroom processes. Elsevier.

    Google Scholar 

  • Caro, D. H., Lenkeit, J., & Kyriakides, L. (2016). Teaching strategies and differential effectiveness across learning contexts: Evidence from PISA 2012. Studies in Educational Evaluation, 49, 30–41.

    Article  Google Scholar 

  • Chi, S., Liu, X., Wang, Z. & Won Han, S. (2018). Moderation of the Effects of Scientific Inquiry Activities on Low SES Students’ PISA 2015 Science Achievement by School Teacher Support and Disciplinary Climate in Science Classroom across Gender. International Journal of Science Education, 40(11), 1284–1304.

    Google Scholar 

  • Clausen, M. (2002). Unterrichtsqualität: Eine Frage der Perspektive? Waxmann.

    Google Scholar 

  • Creemers, B. P. M. & Kyriakides, L. (2007). The dynamics of educational effectiveness: A contribution to policy, practice and theory in contemporary schools. Routledge.

    Google Scholar 

  • Cresswell, J. (Ed.) (2012). PISA 2009 Technical Report. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Crocker, R., Monseur, C., Glickman, V., Levin, B., Schachter, L., Anderson, J., Ungerleider, C., Schleicher, A., Shewbridge, C. & Zoido, P. (2010). Mathematics Teaching and Learning Strategies in PISA. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Darling-Hammond, L. (2016). Research on teaching and teacher education and its influences on policy and practice. Educational Researcher, 45(2), 83–91.

    Article  Google Scholar 

  • Decristan, J., Klieme, E., Kunter, M., Hochweber, J., Büttner, G., Fauth, B., Hondrich, A. L., Rieser, S., Hertel, S. & Hardy, I. (2015). Embedded formative assessment and classroom process quality. American Educational Research Journal, 52(6), 1133–1159.

    Google Scholar 

  • De Jong, J., Rozunick, C., van de Vijver, F., Lafontaine, D., Howie, S., Elliot, A., Hopfenbck, T. & Kaplan, D. (2019). PISA 2018 Questionnaire Framework. In OECD (Ed.), PISA 2018 Assessment and Analytical Framework (pp. 217–256). Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Doan, S., Klieme, E., Praetorius, A.K. & Mihaly, K. (2021). Alignment of Student and Teacher Reports on Different Domains of Teacher Quality: A Cross-Country Comparison. Paper presented at the American Educational Research Association.

    Google Scholar 

  • Dubberke, T., Kunter, M., McElvany, N., Brunner, M. & Baumert, J. (2008). Lerntheoretische Überzeugungen von Mathematiklehrkräften. Zeitschrift für Pädagogische Psychologie, 22(34), 193–206. https://doi.org/10.1024/1010-0652.22.34.193

  • Echazarra, A., Salinas, D., Méndez, I., Denis, V. & Rech, G. (2016). How teachers teach and students learn: Successful strategies for school. OECD Education Working Paper No. 130. https://doi.org/10.1787/5jm29kpt0xxx-en

  • Fauth, B., Decristan, J., Rieser, S., Klieme, E., & Büttner, G. (2014). Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29, 1–9.

    Article  Google Scholar 

  • Fauth, B., Decristan, J., Decker, A. T., Büttner, G., Hardy, I., Klieme, E. & Kunter, M. (2019). The effects of teacher competence on student outcomes in elementary science education: The mediating role of teaching quality. Teaching and Teacher Education, 86. https://doi.org/10.1016/j.tate.2019.102882

  • Ferguson, R. F. (2012). Can student surveys measure teaching quality? Phi Delta Kappan, 94(3), 24–28.

    Article  Google Scholar 

  • Ferguson, R. F., & Danielson, C. (2014). How framework for teaching and tripod 7Cs evidence distinguish key components of effective teaching. Designing Teacher Evaluation Systems, 98–143.

    Google Scholar 

  • Fischer, J., Praetorius, A. K. & Klieme, E. (2019). The impact of linguistic similarity on cross-cultural comparability of students’ perceptions of teaching quality. Educational Assessment, Evaluation and Accountability, 31(2), 201–220.

    Google Scholar 

  • Fischer, J., He, J. & Klieme, E. (2020). The structure of teaching practices across countries: A combination of factor analysis and network analysis. Studies in Educational Evaluation, 65, 100861.

    Google Scholar 

  • Gao, S., Long, H., Li, D., & Yang, L. (2020). The mediation effect of student self-efficacy between teaching approaches and science achievement: Findings from 2011 TIMSS US data. Social Psychology of Education, 23(2), 385–410.

    Article  Google Scholar 

  • Gómez, R. L. & Suárez, A. M. (2020). Do inquiry-based teaching and school climate influence science achievement and critical thinking? Evidence from PISA 2015. International Journal of STEM Education, 7(43).

    Google Scholar 

  • Göllner, R., Fauth, B., & Wagner, W. (2021). Student ratings of teaching quality dimensions: Empirical findings and future directions. In W. Rollett, H. Bijlsma, & S. Röhl (Eds.), Student feedback on teaching in schools. Springer. https://doi.org/10.1007/978-3-030-75150-0_7

    Chapter  Google Scholar 

  • Gough, D., Oliver, S., & Thomas, J. (2017). An introduction to systematic reviews. Sage.

    Google Scholar 

  • Grasha, A. F. (1996). Teaching with style: A practical guide to enhancing learning by understanding teaching and learning styles. Alliance publishers.

    Google Scholar 

  • Gurevitch, J., Koricheva, J., Nakagawa, S., et al. (2018). Meta-analysis and the science of research synthesis. Nature, 555, 175–182. https://doi.org/10.1038/nature25753

    Article  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 1. School Effectiveness and School Improvement, 24(3), 275–295.

    Article  Google Scholar 

  • Hann, T. (2020). Investigating the impact of teacher practices and noncognitive factors on mathematics achievement. Research in Education, 108(1), 22–45.

    Google Scholar 

  • Hastedt, D., Knoll, S., Carstens, R. & Westphal, F. (Eds.) (2010). TALIS 2008 Technical Report. Organisation for Economic Co-operation and Development (OECD). Retrieved from https://www.oecd.org/education/school/44978960.pdf

  • He, J., Buchholz, J. & Klieme, E. (2017). Effects of anchoring vignettes on comparability and predictive validity of student self-reports in 64 cultures. Journal of Cross-Cultural Psychology, 48(3), 319–334.

    Google Scholar 

  • Herbert, B., Fischer, J. & Klieme, E. (Under review). How valid are student perceptions of teaching quality across education systems?. Submitted for publication.

    Google Scholar 

  • Hooper, M., Mullis, I. V. S., Martin, M. O., & Fishbein, B. (2013). TIMSS 2015 context questionnaire framework. In Mullis, I.V.S. & Martin, M.O. (Eds.). TIMSS 2015 Assessment Frameworks. Retrieved from Boston College, TIMSS & PIRLS International Study Center http://timssandpirls.bc.edu/timss2015/frameworks.html (pp. 61–82).

  • Hopfenbeck, T. N., Lenkeit, J., El Masri, Y., Cantrell, K., Ryan, J., & Baird, J.-A. (2018). Lessons learned from PISA: A systematic review of peer-reviewed articles on the programme for international student assessment. Scandinavian Journal of Educational Research, 62(3), 333–353.

    Article  Google Scholar 

  • Husén, T., & Postlethwaite, T. N. (1996). A brief history of the international association for the evaluation of educational achievement (TEA). Assessment in Education: Principles, Policy & Practice, 3(2), 129–141.

    Google Scholar 

  • Hwang, J., Choi, K. M., Bae, Y. & Shin, D. H. (2018). Do teachers’ instructional practices moderate equity in mathematical and scientific literacy?: An investigation of the PISA 2012 and 2015. International Journal of Science and Mathematics Education, 16(S1), 25–45.

    Google Scholar 

  • Jhang, F.-H. (2014). The influences of inductive instruction and resources on students’ attitudes toward reading: Evidence from PISA 2009. Educational Research and Evaluation, 20(5), 386–410.

    Article  Google Scholar 

  • Kane, T., & Cantrell, S. (2012). Gathering feedback for teaching. Combining high-quality observations with student surveys and achievement gains. Retrieved from http://www.metproject.org/downloads/MET_Gathering_Feedback_for_Teaching_Summary.pdf

  • Kaya, S., & Rice, D. C. (2010). Multilevel effects of student and classroom factors on elementary science achievement in five countries. International Journal of Science Education, 32(10), 1337–1363.

    Article  Google Scholar 

  • Kirsch, I., Lennon, M., von Davier, M., Gonzalez, E., & Yamamoto, K. (2013). On the growing importance of international large-scale assessments. In The role of international large-scale assessments: Perspectives from technology, economy, and educational research (pp. 1–11). Springer.

    Google Scholar 

  • Kjærnsli, M. & Lie, S. (2011). Students’ preference for science careers: International comparisons based on PISA 2006. International Journal of Science Education, 33(1), 121–144.

    Google Scholar 

  • Klette, K. (2007). Trends in research on teaching and learning in schools: Didactics meets classroom studies. European Educational Research Journal, 6(2), 147–160.

    Article  Google Scholar 

  • Klieme, E. (2019). Teaching quality. Conceptualization, measurement, and findings for European countries. Keynote lecture presented at the EU “PISA and Beyond Conference”, Helsinki, Finland. https://doi.org/10.13140/RG.2.2.11701.55529

  • Klieme, E. (2020). Policies and practices of assessment: A showcase for the use (and misuse) of international large scale assessments in educational effectiveness research. In J. Hall, A. Lindorff & P. Sammons (Eds.), International perspectives in educational effectiveness research (p. 147–181). Springer.

    Google Scholar 

  • Klieme, E., Schümer, G. & Knoll, S. (2001). Mathematikunterricht in der Sekundarstufe I: „Aufgabenkultur“ und Unterrichtsgestaltung. In E. Klieme (Eds.), TIMSS – Impulse für Schule und Unterricht (S. 43–57). Bundesministerium für Bildung und Forschung.

    Google Scholar 

  • Klieme, E., Jude, N., Rauch, D., Ehlers, H., Helmke, A., Eichler, W., … Willenberg, H. (2008). Alltagspraxis, Qualität und Wirksamkeit des Deutschunterrichts. In DESI-Konsortium (Ed.), Unterricht und Kompetenzerwerb in Deutsch und Englisch: Ergebnisse der DESI-Studie (pp. 319–344). Weinheim/Basel: Beltz.

    Google Scholar 

  • Klieme, E., Pauli, C., & Reusser, K. (2009). The pythagoras study: Investigating effects of teaching and learning in Swiss and German mathematics classrooms. In T. Janik & T. Seidel (Eds.), The power of video studies in investigating teaching and learning in the classroom (pp. 137–160). Waxmann Publicing Co.

    Google Scholar 

  • Klieme, E., Steinert, B. & Hochweber, J. (2010). Zur Bedeutung der Schulqualität für Unterricht und Lernergebnisse. In W. Bos, E. Klieme & O. Köller (Eds.), Schulische Lerngelegenheiten und Kompetenzentwicklung (S. 231–255). Waxmann.

    Google Scholar 

  • Klieme, E., Vieluf, S., Backhoff, E., Hong, Y., Kaplan, D., Levin, H. M., Scheerens, J., Schmidt, W. H. & van de Vijver, F. (2013). PISA 2012 context questionnaires framework. In OECD (Ed.), PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy (p. 167–258). Organisation for Economic Co-operation and Development. https://doi.org/10.1787/9789264190511-en

  • Klieme, E. & Kuger, S., Kaplan, D., Elacqua,G., Kjærnsli, M., Kyriakides, L., Levin, H.M., Miyake, N., Osborne, J., Scalise, K., van de Vijver, F. & Wößmann, L. (2017). PISA 2015 context questionnaires framework. In OECD (Ed.), PISA 2015 assessment and analytical framework. Revised Edition (pp. 103–121). Organisation for Economic Co-operation and Development. https://doi.org/10.1787/9789264255425-7-en

  • Kobarg, M., Prenzel, M., Seidel, T., Walker, M., McCrae, B., Cresswell, J. & Wittwer, J. (2011). An international comparison of science teaching and learning. Further results from PISA 2006. Waxmann.

    Google Scholar 

  • Kounin, J. S. (1970). Discipline and group management in classrooms. Holt, Rinehart and Winston.

    Google Scholar 

  • Kuger, S., Klieme, E., Jude, N., & Kaplan, D. (2016). Assessing contexts of learning: An international perspective. Springer.

    Book  Google Scholar 

  • Kuger, S., Klieme, E., Lüdtke, O., Schiepe-Tiska, A., & Reiss, K. (2017). Mathematikunterricht und Schülerleistung in der Sekundarstufe: Zur Validität von Schülerbefragungen in Schulleistungsstudien. Zeitschrift für Erziehungswissenschaft. Sonderheft, 33, 61–98.

    Article  Google Scholar 

  • Kunter, M. (2005). Multiple Ziele im Mathematikunterricht (Pädagogische Psychologie und Entwicklungspsychologie, Bd. 51). Waxmann.

    Google Scholar 

  • Kunter, M. & Voss, T. (2011). Das Modell der Unterrichtsqualität in COACTIV: Eine multikriterale Analyse. In M. Kunter, J. Baumert, W. Blum, U. Klusmann, S. Krauss & M. Neubrand (Eds.), Professionelle Kompetenz von Lehrkräften: Ergebnisse des Forschungsprogramms COACTIV (p. 85–113). Waxmann.

    Google Scholar 

  • Kyllonen, P. C., & Bertling, J. J. (2014). Innovative questionnaire assessment methods to increase crosscountry comparability. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and methods of data analysis (pp. 277–286). CRC Press.

    Google Scholar 

  • Kyriakides, L., Creemers, B. P., Panayiotou, A., Vanlaar, G., Pfeifer, M., Cankar, G., & McMahon, L. (2014). Using student ratings to measure quality of teaching in six European countries. European Journal of Teacher Education, 37(2), 125–143.

    Article  Google Scholar 

  • Lau, K. C. & Lam, T. Y. P. (2017). Instructional practices and science performance of 10 top-performing regions in PISA 2015. International Journal of Science Education, 39(15), 2128–2149.

    Google Scholar 

  • Lavonen, J. & Laaksonen, S. (2009). Context of teaching and learning school science in Finland: Reflections on PISA 2006 results. Journal of Research in Science Teaching, 46(8), 922–944.

    Google Scholar 

  • Lenkeit, J. (2013). Effectiveness measures for cross-sectional studies: A comparison of value-added models and contextualised attainment models. School Effectiveness and School Improvement, 24(1), 39–63.

    Google Scholar 

  • Li, H. (2016). How Is Formative Assessment Related to Students’ Reading Achievement? Findings from PISA 2009. Assessment in Education: Principles, Policy & Practice, 23(4), 473–494.

    Google Scholar 

  • Lipowsky, F., Rakoczy, K., Pauli, C., Drollinger-Vetter, B., Klieme, E., & Reusser, K. (2009). Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean Theorem. Learning and Instruction, 19(6), 527–537.

    Article  Google Scholar 

  • Lipowsky, F., Drollinger-Vetter, B., Klieme, E., Pauli, C. & Reusser, K. (2018). Generische und fachdidaktische Dimensionen von Unterrichtsqualität – Zwei Seiten einer Medaille? In M. Martens, K. Rabenstein, K. Bräu, M. Fetzer, H. Gresch, I. Hardy & C. Schelle (Hrsg.), Konstruktionen von Fachlichkeit: Ansätze, Erträge und Diskussionen in der empirischen Unterrichtsforschung (S. 183–202). Klinkhardt.

    Google Scholar 

  • Martin, M. O., & Kelly, D. L. (1996). TIMSS Technical Report In Vol. 1.

    Google Scholar 

  • McLaughlin, M., McGrath, D. J., Burian-Fitzgerald, M. A., Lanahan, L., Scotchmer, M., Enyeart, C., & Salganik, L. (2005). Student content engagement as a construct for the measurement of effective classroom instruction and teacher knowledge. Paper presented at the annual meeting of the American Educational Research Association, Montréal.

    Google Scholar 

  • Meinck, S. (2020). Sampling, weighting, and variance estimation. In H. Wagemaker (Ed.), Reliability and validity of international large-scale assessment (pp. 113–129). Springer.

    Chapter  Google Scholar 

  • Meng, L., Muñoz, M., King Hess, K. & Liu, S. (2017). Effective teaching factors and student reading strategies as predictors of student achievement in PISA 2009: The case of China and the United States. Educational Review, 69(1), 68–84.

    Google Scholar 

  • Müller, K., Prenzel, M., Seidel, T., Schiepe-Tiska, A. & Kjærnsli, M. (2016). Science teaching and learning in schools: Theoretical and empirical foundations for investigating classroom-level processes. In S. Kuger, E. Klieme, N. Jude & D. Kaplan (Hrsg.), Assessing contexts of learning. Methodology of educational measurement and assessment (S. 423–446). Springer.

    Google Scholar 

  • Mullis, I. V. S., & Martin, M. O. (2017). TIMSS 2019 assessment frameworks. ERIC.

    Google Scholar 

  • Mullis, I. V. S., Martin, M. O., Smith, T. A., Garden, R. A., Gregory, K. D., Gonzalez, E. J., … O’Connor, K. M. (2003). TIMSS Assessment Frameworks and Specifications 2003. International Study Center, Lynch School of Education, Boston College.

    Google Scholar 

  • Mullis, I. V. S., Martin, M. O., Ruddock, G. J., O’Sullivan, C. Y., Arora, A., & Erberber, E. (2005). TIMSS 2007 Assessment Frameworks. TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College.

    Google Scholar 

  • Mullis, I. V. S., Martin, M. O., Ruddock, G. J., O’Sullivan, C. Y., & Preuschoff, C. (2012). TIMSS 2011 Assesment Frameworks. TIMSS & PIRLS International Study Center. Lynch School of Education, Boston College.

    Google Scholar 

  • Mullis, I. V. S., Martin, M. O. & von Davier, M. (Eds.) (2021). TIMSS 2023 Assessment Frameworks. TIMSS & PIRLS International Study Center. Lynch School of Education, Boston College.

    Google Scholar 

  • Murnane, R. J., & Willett, J. B. (2010). Methods matter: Improving causal inference in educational and social science research. Oxford University Press.

    Google Scholar 

  • Nehls, C., König, J., Kaiser, G., & Blömeke, S. (2020). Profiles of teachers’ general pedagogical knowledge: Nature, causes and effects on beliefs and instructional quality. ZDM, 52(2), 343–357.

    Article  Google Scholar 

  • Neumann, K., Kauertz, A., & Fischer, H. E. (2012). Quality of instruction in science education. In Second international handbook of science education (pp. 247–258). Springer.

    Chapter  Google Scholar 

  • Nilsen, T., & Gustafsson, J.-E. (2016). Teacher quality, instructional quality and student outcome. Relationships across countries, cohorts and time (Vol. 2). Springer.

    Book  Google Scholar 

  • Nilsen, T., Gustafsson, J.-E., & Blömeke, S. (2016). Conceptual framework and methodology of this report. Teacher Quality, Instructional Quality and Student Outcomes, 1.

    Google Scholar 

  • Nilsen, T., Slot, P., Cigler, H., & Chen, M. (2020). Measuring process quality in early childhood education and care through Situational Judgement Questions: Findings from TALIS Starting Strong 2018 Field Trial. OECD Education Working Papers, No. 217. Retrieved from https://doi.org/10.1787/852602c5-en

  • OECD (2001). Knowledge and skills for life. First results from PISA 2000. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • OECD (2004). Learning for Tomorrow’s World. First Results from PISA 2003. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • OECD (2007). PISA 2006. Science competencies for tomorrow’s world. Volume 1: Analysis. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • OECD (2010). PISA 2009 Results: What Students Know and Can Do. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • OECD. (2012). Equity and Quality in Education: Supporting Disadvantaged Students and Schools. In. Retrieved from https://doi.org/10.1787/9789264130852-en

  • OECD. (2013). PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy. OECD.

    Book  Google Scholar 

  • OECD (2014). PISA 2012 Results: What Students Know and Can Do (Volume I, Revised edition). Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • OECD (2016). PISA 2015 Results (Volume II): Policies and Practices for Successful Schools. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • OECD (2019). PISA 2018 Results (Volume III): What School Life Means for Students’ Lives. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Opfer, D., Bell, C., Klieme, E., McCaffrey, D., Schweig, J., & Stecher, B. (2020). Understanding and measuring mathematics teaching practice. In OECD (Ed.), OECD Global Teaching InSights: A video study of teaching. OECD Publishing.

    Google Scholar 

  • Paik, S. J. (2004). Korean and US families, schools, and learning. International Journal of Educational Research, 41(1), 71–90.

    Article  Google Scholar 

  • Pianta, R., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38(2), 109–119.

    Article  Google Scholar 

  • Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667–686.

    Article  Google Scholar 

  • Potužníková, E. (2018). Factors explaining the interest of Czech students in reading and mathematics. Orbis Scholae, 12(2), 101–124.

    Article  Google Scholar 

  • Praetorius, A.-K., Klieme, E., Herbert, B., & Pinger, P. (2018). Generic dimensions of teaching quality: The German framework of three basic dimensions. ZDM, 50(3), 407–426.

    Article  Google Scholar 

  • Praetorius, A. K., Klieme, E., Kleickmann, T., Brunner, E., Lindmeier, A., Taut, S. & Charalambous, C. (2020). Towards developing a theory of generic teaching quality: Origin, current status, and necessary next steps regarding the Three Basic Dimensions model. Zeitschrift für Pädagogik. Beiheft, 66, 15–36.

    Google Scholar 

  • Praetorius, A.-K., Fischer, J. & Klieme, E. (2021). Teacher and student questionnaire development. In OECD (Hrsg.), Global teaching insights technical report (p. 1–20). OECD Publishing. https://www.oecd.org/education/school/GTI-TechReport-Chapter9.pdf

  • Purves, A. C. (1987). The evolution of the IEA: A memoir. Comparative Education Review, 31(1), 10–28.

    Google Scholar 

  • Rakoczy, K. (2008). Motivationsunterstützung im Mathematikunterricht: Unterricht aus der Perspektive von Lernenden und Beobachtern. Waxmann.

    Google Scholar 

  • Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39(1), 33–38.

    Google Scholar 

  • Rosenshine, B., & Furst, N. (1973). The use of direct observation to study teaching. In R. M. W. Travers (Ed.), Second handbook of research on teaching (p. 122–183). RandMcNally.

    Google Scholar 

  • Rutkowski, L. (2016). Introduction to special issue on quasi-causal methods. Large-Scale Assessments in Education, 4(1), 8. https://doi.org/10.1186/s40536-016-0023-5

    Article  Google Scholar 

  • Rutkowski, L., von Davier, M., & Rutkowski, D. (2014). Handbook of international large-scale assessment. Background, technical issues, and methods of data analysis. Chapman and Hall/CRC.

    Google Scholar 

  • Saarinen, A., Lipsanen, J., Hintsanen, M., Huotilainen, M. & Keltikangas-Järvinen, L. (2020). Student-oriented teaching practices and educational equality: A population-based study. Electronic Journal of Research in Education Psychology, 18(51), 153–178. https://doi.org/10.25115/ejrep.v18i51.2784

  • Salchegger, S., Wallner-Paschon, C. & Bertsch, C. (2021). Explaining Waldorf students’ high motivation but moderate achievement in science: Is inquiry-based science education the key? Large-scale Assessments in Education, 9(14).

    Google Scholar 

  • Scherer, R., Nilsen, T., & Jansen, M. (2016). Evaluating individual students’ perceptions of instructional quality: An investigation of their factor structure, measurement invariance, and relations to educational outcomes. Frontiers in Psychology, 7(110). https://doi.org/10.3389/fpsyg.2016.00110

  • Scherer, R., Siddiq, F., & Nilsen, T. (2021, October 24). The potential of international large-scale assessments for meta-analyses in education. https://doi.org/10.31234/osf.io/bucf9

  • Seidel, T., & Prenzel, M. (2006). Teaching and learning of science. In ACER (Ed.), PISA 2006 conceptual framework. Australian Council of Educational Research (ACER).

    Google Scholar 

  • Seidel, T. & Shavelson, R. J. (2007). Teaching effectiveness research in the past decade: The role of theory and research design in disentangling meta-analysis results. Review of Educational Research, 77(4), 454–499.

    Google Scholar 

  • Senden, B., Nilsen, T., & Blömeke, S. (2021). Instructional Quality: A Review of Conceptualizations, Measurement Approaches, and Research Findings. In M. Blikstad-Balas, K. Klette, & M. Tengberg (Red.), Ways of Analyzing Teaching Quality (pp. 140–172). Scandinavian University Press.

    Google Scholar 

  • Stigler, J., & Hiebert, J. (1997). Understanding and improving classroom mathematics instruction: An overview of the TIMSS video study. Paper presented at the ACER National Conference 1997.

    Google Scholar 

  • Tan, C. Y. & Dimmock, C. (2020). The relationships among between-class ability grouping, teaching practices, and mathematics achievement: A large-scale empirical analysis. Educational Studies, 1–19.

    Google Scholar 

  • Tang, N. E., Tsai, C. L., Barrow, L. & Romine, W. (2019). Impacts of enquiry-based science teaching on achievement gap between high-and-low SES students: Findings from PISA 2015. International Journal of Science Education, 41(4), 448–470.

    Google Scholar 

  • Taylor, J. A., Stuhlsatz, M. A. M., & Bybee, R. W. (2009). Windows into high-achieving science classrooms. In R. W. Bybee & B. McCrae (Eds.), PISA Science 2006: Implications for science teachers and teaching (pp. 123–13). NSTA Press.

    Google Scholar 

  • Teig, N., Scherer, R., & Nilsen, T. (2018). More isn’t always better: The curvilinear relationship between inquiry-based teaching and student achievement in science. Learning and Instruction, 56, 20–29. https://doi.org/10.1016/j.learninstruc.2018.02.006

    Article  Google Scholar 

  • Tourón, J., Navarro-Asencio, E., Lizasoain, L., López-González, E. & García-San Pedro, M. J. (2019). How teachers’ practices and students’ attitudes towards technology affect mathematics achievement: Results and insights from PISA 2012. Research Papers in Education, 34(3), 263–275. https://doi.org/10.1080/02671522.2018.1424927

  • Turner, R. (Ed.) (2014). PISA 2012 Technical Report. Organisation for Economic Co-operation and Development (OECD).

    Google Scholar 

  • Vieluf, S. & Klieme, E. (in press). Teaching Effectiveness Revisited Through the Lens of Practice Theories. In Praetorius, A. K. & Charalambous, C. (Eds.), Theorizing Teaching: Bringing Together Expert Perspectives to Move the Field Forward (pp. 91–124). Springer.

    Google Scholar 

  • Vieluf, S., Hochweber, J., Klieme, E. & Kunter, M. (2015). Who has a good relationship with the teachers? A comparison of comprehensive education systems with education systems using between-school tracking. Oxford Review of Education, 41(1), 3–25.

    Google Scholar 

  • Wagemaker, H. (2020). Reliability and validity of international large-scale assessment: Understanding IEA’s comparative studies of student achievement. Springer Nature.

    Book  Google Scholar 

  • Wang, M. C., Haertel, G. D., & Walberg, H. J. (1993). Toward a knowledge base for school learning. Review of Educational Research, 63(3), 249–294.

    Google Scholar 

  • Wenglinsky, H. (2000). How teaching matters: Bringing the classroom back into discussions of teacher quality. Milken Family Foundation and Educational Testing Service.

    Google Scholar 

  • Yetisir, M. I. (2014). The multilevel effects of student and classroom factors on the science achievement of eighth graders in Turkey. Egitim ve Bilim, 39(172).

    Google Scholar 

  • Yi, H. S. & Lee, Y. (2017). A latent profile analysis and structural equation modeling of the instructional quality of mathematics classrooms based on the PISA 2012 results of Korea and Singapore. Asia Pacific Education Review, 18(1), 23–39.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. DIPF | Leibniz Institute for Research and Information in Education, Frankfurt, Germany

    Eckhard Klieme

  2. Department of Teacher Education and School Research, Faculty of Educational Sciences, University of Oslo, Oslo, Norway

    Trude Nilsen

Authors
  1. Eckhard Klieme
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Trude Nilsen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eckhard Klieme .

Editor information

Editors and Affiliations

  1. University of Oslo, Blindern, Oslo, Norway

    Trude Nilsen

  2. IEA Hamburg, Hamburg, Hamburg, Germany

    Agnes Stancel-Piątak

  3. University of Gothenburg, Gothenburg, Sweden

    Jan-Eric Gustafsson

Section Editor information

  1. CEMO, University of Oslo, Oslo, Norway

    Ronny Scherer

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Klieme, E., Nilsen, T. (2022). Teaching Quality and Student Outcomes in TIMSS and PISA. In: Nilsen, T., Stancel-Piątak, A., Gustafsson, JE. (eds) International Handbook of Comparative Large-Scale Studies in Education. Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-030-38298-8_37-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-38298-8_37-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38298-8

  • Online ISBN: 978-3-030-38298-8

  • eBook Packages: Springer Reference EducationReference Module Humanities and Social SciencesReference Module Education

Publish with us

Policies and ethics

Search

Navigation