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The Effect of Content Knowledge and Pedagogical Content Knowledge on Instructional Quality and Student Achievement

  • Jürgen Baumert
  • Mareike Kunter
Chapter
Part of the Mathematics Teacher Education book series (MTEN, volume 8)

Abstract

This chapter presents the findings of analyses testing whether and to what extent mathematics teachers’ content knowledge and pedagogical content knowledge systematically impact the quality of their instruction and, in turn, their students’ learning progress. Analyses based on a representative sample of grade 10 classes and their mathematics teachers showed that teachers’ pedagogical content knowledge was theoretically and empirically distinguishable from their content knowledge. Multilevel structural equation models revealed a substantial positive effect of pedagogical content knowledge on students’ learning gains that was mediated by the provision of cognitive activation and individual learning support.

Keywords

Content Knowledge Mathematics Teacher Pedagogical Content Knowledge Mathematical Knowledge Teacher Education Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. American Council on Education (1999) To touch the future: transforming the way teachers are taught. American Council on Education, Washington, DCGoogle Scholar
  2. Attewell P, Domina T (2008) Raising the bar: curricular intensity and academic performance. Educ Eval Policy Anal 30(1):51–71. doi: 10.3102/0162373707313409 Google Scholar
  3. Ball DL (1990) The mathematical understandings that prospective teachers bring to teacher education. Elem School J 90(4):449–466. doi: 10.1086/461626 Google Scholar
  4. Ball DL (1991) Research on teaching mathematics: making subject-matter knowledge part of the equation. In: Brophy J (ed) Advances in research on teaching, vol 2, Teachers’ knowledge of subject matter as it relates to their teaching practice. JAI Press, Greenwich, pp 1–48Google Scholar
  5. Ball DL, Bass H (2003) Toward a practice-based theory of mathematical knowledge for teaching. In: Davis B, Simmt E (eds) Proceedings of the 2002 annual meeting of the Canadian Mathematics Education Study Group, Canadian Mathematics Education Study Group/Groupe Canadien d’étude en didactique des mathématiques, Edmonton/Alberta, pp 3–14Google Scholar
  6. Ball DL, Lubienski ST, Mewborn DS (2001) Research on teaching mathematics: the unsolved problem of teachers’ mathematical knowledge. In: Richardson V (ed) Handbook of research on teaching, 4th edn. American Educational Research Association, Washington, DC, pp 433–456Google Scholar
  7. Ballou D, Podgursky M (2000) Reforming teacher preparation and licensing: what is the evidence? Teach Coll Rec 102(1):5–27. doi: 10.1111/0161-4681.00046 Google Scholar
  8. Baumert J, Artelt C (2002) Bereichsübergreifende Perspektiven [Domain-transcending perspectives]. In: Baumert J, Artelt C, Klieme E, Neubrand M, Prenzel M, Schiefele U, … Weiß M (eds) PISA 2000: Die Länder der Bundesrepublik Deutschland im Vergleich. Leske + Budrich, Opladen, pp 219–235Google Scholar
  9. Baumert J, Kunter M (2006) Stichwort: Professionelle Kompetenz von Lehrkräften [Teachers’ professional competence]. Zeitschrift für Erziehungswissenschaft 9(4):469–520. doi: 10.1007/s11618-006-0165-2 Google Scholar
  10. Baumert J, Schümer G (2001) Familiäre Lebensverhältnisse, Bildungsbeteiligung und Kompetenzerwerb [Family background, educational participation, and competency acquisition]. In: Baumert J, Klieme E, Neubrand M, Prenzel M, Schiefele U, Schneider W, … Weiß M (eds) PISA 2000: Basiskompetenzen von Schülerinnen und Schülern im internationalen Vergleich. Leske + Budrich, Opladen, pp 323–407Google Scholar
  11. Baumert J, Kunter M, Blum W, Brunner M, Dubberke T, Jordan A, … Tsai Y-M (2010) Teachers’ mathematical knowledge, cognitive activation in the classroom and student progress. Am Educ Res J 47(1):133–180. doi:10.3102/0002831209345157Google Scholar
  12. Blömeke S, Kaiser G, Lehmann R (eds) (2008) Professionelle Kompetenz angehender Lehrerinnen und Lehrer: Wissen, Überzeugungen und Lerngelegenheiten deutscher Mathematik-­Studierender und -Referendare – erste Ergebnisse zur Wirksamkeit der Lehrerausbildung [Professional ­competence of prospective teachers—knowledge, beliefs, and learning opportunities of mathematics teacher candidates in Germany: initial findings on the effectiveness of teacher education]. Waxmann, MünsterGoogle Scholar
  13. Blömeke S, Lehmann R, Kaiser G (eds) (2010) TEDS-M 2008: Professionelle Kompetenz und Lerngelegenheiten angehender Mathematiklehrkräfte für die Sekundarstufe I im internationalen Vergleich [TEDS-M 2008: professional competence and learning opportunities of prospective lower secondary mathematics teachers in international comparison]. Waxmann, MünsterGoogle Scholar
  14. Bloom HS, Hill CJ, Black AR, Lipsey MW (2008) Performance trajectories and performance gaps as achievement effect-size benchmarks for educational interventions. J Res Educ Eff 1(4):289–328Google Scholar
  15. Bollen KA, Long JS (1993) Testing structural equation models. Sage, Newbury ParkGoogle Scholar
  16. Borko H, Livingston C (1989) Cognition and improvisation: differences in mathematics instruction by expert and novice teachers. Am Educ Res J 26(4):473–498Google Scholar
  17. Borko H, Eisenhart M, Brown C, Underhill R, Jones D, Agard P (1992) Learning to teach hard mathematics: do novice teachers and their instructors give up too easily? J Res Math Educ 23(3):194–222. doi: 10.2307/749118 Google Scholar
  18. Bransford J, Darling-Hammond L, LePage P (2005a) Introduction. In: Darling-Hammond L, Bransford J (eds) Preparing teachers for a changing world. Jossey-Bass, San Francisco, pp 1–39Google Scholar
  19. Bransford J, Derry SJ, Berliner CD, Hammerness K (2005b) Theories of learning and their roles in teaching. In: Darling-Hammond L, Bransford J (eds) Preparing teachers for a changing world. Jossey-Bass, San Francisco, pp 40–87Google Scholar
  20. Bromme R (1992) Der Lehrer als Experte [The teacher as expert]. Huber, BerneGoogle Scholar
  21. Bromme R (1997) Kompetenzen, Funktionen und unterrichtliches Handeln des Lehrers [Competencies, functions, and instructional practice of teachers]. In: Weinert FE (ed) Enzyklopädie der Psychologie, vol 3, Psychologie des Unterrichts und der Schule. Hogrefe, Göttingen, pp 177–212Google Scholar
  22. Brophy J (2000) Teaching. International Academy of Education, BrusselsGoogle Scholar
  23. Clausen M (2002) Unterrichtsqualität – Eine Frage der Perspektive? [Instructional quality–a question of perspective?]. Waxmann, MünsterGoogle Scholar
  24. Cochran-Smith M, Zeichner KM (2005) Studying teacher education: the report of the AERA panel on research and teacher education. Erlbaum, MahwahGoogle Scholar
  25. Darling-Hammond L (2000) Teacher quality and student achievement: a review of state policy evidence. Educ Policy Anal Arch 8(1):1–46Google Scholar
  26. Darling-Hammond L (2006) No child left behind and high school reform. Harv Educ Rev 76(4):642–667Google Scholar
  27. De Corte E, Greer B, Verschaffel L (1996) Mathematics teaching and learning. In: Berliner DC, Calfee RC (eds) Handbook of educational psychology. Erlbaum, Mahwah, pp 491–549Google Scholar
  28. Deng Z (2007) Knowing the subject matter of a secondary school science subject. J Curriculum Stud 39(5):503–535. doi: 10.1080/00220270701305362 Google Scholar
  29. Desimone LM (2009) Improving impact studies of teachers’ professional development: toward better conceptualizations and measures. Educ Res 38(3):181–199. doi: 10.3102/0013189X08331140 Google Scholar
  30. Döhrmann M, Kaiser G, Blömeke S (2010) Messung des mathematischen und mathematikdidaktischen Wissen: Theoretischer Rahmen und Teststruktur [Measuring mathematical knowledge and mathematical pedagogical knowledge: theoretical framework and test structure]. In: Blömeke S, Lehmann R, Kaiser G (eds) TEDS-M 2008: Professionelle Kompetenz und Lerngelegenheiten angehender Mathematiklehrkräfte für die Sekundarstufe I im internationalen Vergleich. Waxmann, Münster, pp 169–196Google Scholar
  31. Ehmke T, Blum W, Neubrand M, Jordan A, Ulfig F (2006) Wie verändert sich die mathematische Kompetenz von der neunten zur zehnten Klassenstufe? [How does mathematical literacy change from grade 9 to 10?]. In: Prenzel M, Baumert J, Blum W, Lehmann R, Leutner D, Neubrand M, … Schiefele U (eds) PISA 2003: Untersuchungen zur Kompetenzentwicklung im Verlauf eines Schuljahres. Waxmann, Münster, pp 63–86Google Scholar
  32. Eisenhart M, Borko H, Underhill R, Brown C, Jones D, Agard P (1993) Conceptual knowledge fall through the cracks: complexities of learning to teach mathematics for understanding. J Res Math Educ 24(1):8–40. doi: 10.2307/749384 Google Scholar
  33. Expertenkommission (2007) Ausbildung von Lehrerinnen und Lehrern in Nordrhein-Westfalen – Empfehlungen der Expertenkommission zur Ersten Phase [Education of teachers in North Rhein-Westphalia: recommendations of the expert committee]. Ministry of Innovation, Science, Research, and Technology, DüsseldorfGoogle Scholar
  34. Fennema E, Franke ML (1992) Teachers’ knowledge and its impact. In: Grouws DA (ed) Handbook of research on mathematics teaching and learning. Macmillan, New York, pp 147–164Google Scholar
  35. Fennema E, Carpenter TP, Franke ML, Levi L, Jacobs VR, Empson SB (1996) A longitudinal study of learning to use children’s thinking in mathematics instruction. J Res Math Educ 27(4):403–434. doi: 10.2307/749875 Google Scholar
  36. Floden RE, Meniketti M (2005) Research on the effects of coursework in the arts and sciences and in the foundations of education. In: Cochran-Smith M, Zeichner KM (eds) Studying teacher education. Erlbaum, Mahwah, pp 261–308Google Scholar
  37. Ganzeboom HBG, Treiman DJ (2003) Three internationally standardised measures for comparative research on occupational status. In: Hoffmeyer-Zlotnik JHP, Wolf C (eds) Advances in cross-national comparison: a European working book for demographic and socio-economic variables. Kluwer Academic/Plenum, New York, pp 159–193Google Scholar
  38. Goldhaber D, Brewer DJ (1997) Evaluating the effect of teacher degree level on educational performance. In: Fowler JW (ed) Developments in school finance 1996. National Center for Education Statistics, U.S. Department of Education, Washington, DC, pp 197–210Google Scholar
  39. Goldhaber D, Brewer DJ (2000) Does teacher certification matter? High school teacher certification status and student achievement. Educ Eval Policy Anal 22(2):129–145Google Scholar
  40. Goodson IF, Marsh C (1996) Studying school subjects. Falmer Press, LondonGoogle Scholar
  41. Goodson IF, Anstead CJ, Mangan JM (1998) Subject knowledge: readings for the study of school subjects. Falmer Press, LondonGoogle Scholar
  42. Goodson IF, Hopmann S, Riquarts K (1999) Das Schulfach als Handlungsrahmen: Vergleichende Untersuchung zur Geschichte und Funktion der Schulfächer [The school subject as a frame of reference: a comparative study of the history and function of school subjects]. Böhlau, CologneGoogle Scholar
  43. Graham JW, Cumsille PE, Elek-Fisk E (2003) Methods for handling missing data. In: Velicer WF (ed) Handbook of psychology: research methods in psychology, vol 2. Wiley, Hoboken, pp 87–114Google Scholar
  44. Greeno JG, Collins AM, Resnick LB (1996) Cognition and learning. In: Berliner DC, Calfee RC (eds) Handbook of educational psychology. Erlbaum, Mahwah, pp 15–46Google Scholar
  45. Grossman PL (1995) Teachers’ knowledge. In: Anderson LW (ed) International encyclopedia of teaching and teacher education, vol 2. Pergamon Press, Oxford, UK, pp 20–24Google Scholar
  46. Grossman PL, McDonald M (2008) Back to the future: directions for research in teaching and teacher education. Am Educ Res J 45(1):184–205. doi: 10.3102/0002831207312906 Google Scholar
  47. Grossman PL, Schoenfeld A (2005) Teaching subject matter. In: Darling-Hammond L, Bransford J (eds) Preparing teachers for a changing world. Jossey-Bass, San Francisco, pp 201–231Google Scholar
  48. Gudmundsdottir S (1991) Pedagogical models of subject matter. In: Brophy J (ed) Advances in research on teaching, vol 2, Teachers’ knowledge of subject matter as it relates to their teaching practice. JAI Press, Greenwich, pp 265–304Google Scholar
  49. Harbison RW, Hanushek EA (1992) Educational performance of the poor: lessons from rural northeast Brazil. Oxford University Press, Oxford, UKGoogle Scholar
  50. Heller KA, Perleth C (2000) Kognitiver Fähigkeitstest für 4.–12. Klassen: (KFT 4–12+R) [Cognitive abilities test for grades 4–12: (KFT 4–12+R)]. Hogrefe, GöttingenGoogle Scholar
  51. Hiebert J, Stigler JW, Jacobs JK, Givvin KB, Garnier H, Smith M, … Gallimore R (2005) Mathematics teaching in the United States today (and tomorrow): results from the TIMSS 1999 Video Study. Educ Eval Policy Anal 27(2):111–132. doi: 10.3102/01623737027002111 Google Scholar
  52. Hiebert J, Morris AK, Berk D, Jansen A (2007) Preparing teachers to learn from teaching. J Teach Educ 58(1):47–61. doi: 10.1177/0022487106295726 Google Scholar
  53. Hill HC (2007) Mathematical knowledge of middle school teachers: implications for the no child left behind policy initiative. Educ Eval Policy Anal 29(2):95–114. doi: 10.3102/0162373707301711 Google Scholar
  54. Hill HC, Lubienski ST (2007) Teachers’ mathematics knowledge for teaching and school context: a study of California teachers. Educ Policy 21(5):747–768. doi: 10.1177/0895904807307061 Google Scholar
  55. Hill HC, Schilling SG, Ball DL (2004) Developing measures of teachers’ mathematics knowledge for teaching. Elem School J 105(1):11–30. doi: 10.1086/428763 Google Scholar
  56. Hill HC, Rowan B, Ball D (2005) Effects of teachers’ mathematical knowledge for teaching on student achievement. Am Educ Res J 42(2):371–406. doi: 10.3102/00028312042002371 Google Scholar
  57. Hill HC, Ball DL, Blunk M, Goffney IM, Rowan B (2007) Validating the ecological assumption: the relationship of measure scores to classroom teaching and student learning. Meas Interdiscip Res Perspect 5(2–3):107–117Google Scholar
  58. Hill CJ, Bloom HS, Black AR, Lipsey MW (2008) Empirical benchmarks for interpreting effect sizes in research. Child Dev Perspect 2(3):172–177. doi: 10.1111/j.1750-8606.2008.00061.x Google Scholar
  59. Jordan A, Ross N, Krauss S, Baumert J, Blum W, Neubrand M, … Kunter M (2006) Klassifikationsschema für Mathematikaufgaben: Dokumentation der Aufgabenkategorisierung im COACTIV-Projekt [Classification scheme for mathematics tasks: documentation of task categorization in the COACTIV project]. Max Planck Institute for Human Development, BerlinGoogle Scholar
  60. Jöreskog KG, Sörbom D, Du Toit S, Du Toit M (2003) LISREL 8: new statistical features (3rd printing with revisions). Scientific Software International, LincolnwoodGoogle Scholar
  61. Kahan J, Cooper D, Bethea K (2003) The role of mathematics teachers’ content knowledge in their teaching: a framework for research applied to a study of student teachers. J Math Teach Educ 6(3):223–252. doi: 10.1023/A:1025175812582 Google Scholar
  62. Klieme E, Schümer G, Knoll S (2001) Mathematikunterricht in der Sekundarstufe I: „Aufgabenkultur“ und Unterrichtsgestaltung [Mathematics instruction at lower secondary level: “Task culture” and quality of instruction]. In: Klieme E, Baumert J (eds) TIMSS: Impulse für Schule und Unterricht. Forschungsbefunde, Reforminitiativen, Praxisberichte und Video-­Dokumente. BMBF, Bonn, pp 43–57Google Scholar
  63. Krauss S, Baumert J, Blum W (2008a) Secondary mathematics teachers’ pedagogical content knowledge and content knowledge: validation of the COACTIV constructs. Int J Math Educ 40(5):873–892. doi: 10.1007/s11858-008-0141-9 Google Scholar
  64. Krauss S, Brunner M, Kunter M, Baumert J, Blum W, Neubrand M, Jordan A (2008b) Pedagogical content knowledge and content knowledge of secondary mathematics teachers. J Educ Psychol 100(3):716–725. doi: 10.1037/0022-0663.100.3.716 Google Scholar
  65. Kunter M, Baumert J (2006) Who is the expert? Construct and criteria validity of student and teacher ratings of instruction. Learn Environ Res 9(3):231–251Google Scholar
  66. Kunter M, Dubberke T, Baumert J, Blum W, Brunner M, Jordan A, … Tsai Y-M (2006) Mathematikunterricht in den PISA-Klassen 2004: Rahmenbedingungen, Formen und Lehr-­Lernprozesse [Mathematics instruction in the PISA 2004 classes: conditions, forms, and teaching and learning processes]. In: Prenzel M, Baumert J, Blum W, Lehmann R, Leutner D, Neubrand M, … Schiefele U (eds) PISA 2003: Untersuchungen zur Kompetenzentwicklung im Verlauf eines Schuljahres. Waxmann, Münster, pp 161–194Google Scholar
  67. Lanahan L, McGrath DJ, McLaughlin M, Burian-Fitzgerald M, Salganik L (2005) Fundamental problems in the measurement of instructional processes: estimating reasonable effect sizes and conceptualizing what is important to measure. American Institutes for Research, Washington, DCGoogle Scholar
  68. Leinhardt G (2001) Instructional explanations: a commonplace for teaching and location for contrast. In: Richardson V (ed) Handbook of research on teaching, 4th edn. American Educational Research Association, Washington, DC, pp 333–357Google Scholar
  69. Lüdtke O, Robitzsch A, Trautwein U, Köller O (2007) Umgang mit fehlenden Werten in der psychologischen Forschung [Handling of missing data in psychological research: problems and solutions]. Psychologische Rundschau 58(2):103–117Google Scholar
  70. Ma L (1999) Knowing and teaching elementary mathematics: teachers’ understanding of fundamental mathematics in China and the United States. Erlbaum, HillsdaleGoogle Scholar
  71. Mayer RE (2004) Should there be a three-strikes rule against pure discovery learning? Am Psychol 59(1):14–19. doi: 10.1037/0003-066X.59.1.14 Google Scholar
  72. Mewborn D (2003) Teachers, teaching, and their professional development. In: Kilpatrick J, Martin WG, Schifter D (eds) A research companion to principles and standards for school mathematics. National Council of Teachers of Mathematics, Reston, pp 45–52Google Scholar
  73. Mitchell R, Barth P (1999) Not good enough: a content analysis of teacher licensing examinations: how teacher licensing tests fall short. Thinking K-16 3(1):1–20Google Scholar
  74. Monk DH (1994) Subject area preparation of secondary mathematics and science teachers and student achievement. Econ Educ Rev 1(2):125–145. doi: 10.1016/0272-7757(94)90003-5 Google Scholar
  75. Monk DH, King JA (1994) Multilevel teacher resource effects in pupil performance in secondary mathematics and science: the case of teacher subject matter preparation. In: Ehrenberg RG (ed) Choices and consequences: contemporary policy issues in education. ILR Press, Ithaca, pp 29–58Google Scholar
  76. Mullens JE, Murnane RJ, Willett JB (1996) The contribution of training and subject matter knowledge to teaching effectiveness: a multilevel analysis of longitudinal evidence from Belize. Comp Educ Rev 40(2):139–157. doi: 10.1086/447369 Google Scholar
  77. Munby H, Russell T, Martin AK (2001) Teachers’ knowledge and how it develops. In: Richardson V (ed) Handbook of research on teaching, 4th edn. American Educational Research Association, Washington, DC, pp 877–904Google Scholar
  78. Muthén LK, Muthén BO (2004) Mplus statistical analysis with latent variables: user’s guide, 3rd edn. Muthén & Muthén, Los AngelesGoogle Scholar
  79. National Council of Teachers of Mathematics (NCTM) (2000) Principles and standards for school mathematics. NCTM, RestonGoogle Scholar
  80. National Education Longitudinal Study (NELS) (1995) National education longitudinal study of 1988: conducting cross-cohort comparisons using HS&B, NAEP, and NELS:88 academic transcript dataGoogle Scholar
  81. National Mathematics Advisory Panel (2008) Foundations for success: the final report of the National Mathematics Advisory Panel. U.S. Department of Education, Washington, DCGoogle Scholar
  82. Nye B, Hedges LV, Konstantopoulos S (2000) Effects of small classes on academic achievement: the results of the Tennessee class size experiment. Am Educ Res J 37(1):123–151Google Scholar
  83. Nye B, Konstantopoulos S, Hedges LV (2004) How large are teacher effects? Educ Eval Policy Anal 26(3):237–257. doi: 10.3102/01623737026003237 Google Scholar
  84. Organisation for Economic Co-operation and Development (OECD) (eds) (2004) PISA: Learning for tomorrow’s world. First results from PISA 2003. France: OECDGoogle Scholar
  85. Peugh JL, Enders CK (2004) Missing data in educational research: a review of reporting practices and suggestions for improvement. Rev Educ Res 74(4):525–556Google Scholar
  86. Pintrich PR, Marx RW, Boyle RA (1993) Beyond cold conceptual change: the role of motivational beliefs and classroom contextual factors in the process of conceptual change. Rev Educ Res 63(2):167–199Google Scholar
  87. Prenzel M, Carstensen CH, Schöps K, Maurischat C (2006) Die Anlage des Längsschnitts bei PISA 2003 [The design of the PISA 2003 longitudinal study]. In: Prenzel M, Baumert J, Blum W, Lehmann R, Leutner D, Neubrand M, … Schiefele U (eds) PISA 2003: Untersuchungen zur Kompetenzentwicklung im Verlauf eines Schuljahres. Waxmann, Münster, pp 29–62Google Scholar
  88. Puntambekar S, Hübscher R (2005) Tools for scaffolding students in a complex learning environment: what have we gained and what have we missed? Educ Psychol 40(1):1–12. doi: 10.1207/s15326985ep4001_1 Google Scholar
  89. Putnam RT, Heaton RM, Prawat RS, Remillard J (1992) Teaching mathematics for understanding: discussing case studies of four fifth-grade teachers. Elem School J 93(2):213–228. doi: 10.1086/461723 Google Scholar
  90. Reynolds MC (ed) (1989) Knowledge base for the beginning teacher. Pergamon Press, New YorkGoogle Scholar
  91. Rosenbaum PR, Rubin DB (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 Google Scholar
  92. Rowan B, Chiang F-S, Miller RJ (1997) Using research on employees’ performance to study the effects of teachers on students’ achievement. Sociol Educ 70(4):256–284. doi: 10.2307/2673267 Google Scholar
  93. Schafer JL, Graham JW (2002) Missing data: our view of the state of the art. Psychol Methods 7:147–177. doi: 10.1037/1082-989X.7.2.147 Google Scholar
  94. Scheerens J, Bosker R (1997) The foundations of educational effectiveness. Pergamon Press, Oxford, UKGoogle Scholar
  95. Schilling SG, Hill HC (2007) Assessing measures of mathematical knowledge for teaching: A validity argument approach. Measurement: Interdisciplinary Research and Perspectives, 5(2–3): 70–80Google Scholar
  96. Schmidt WH, Tatto MT, Bankov K, Blömeke S, Cedillo T, Cogan L, … Schwille J (2007) The preparation gap: teacher education for middle school mathematics in six countries mathematics teaching in the 21st century (MT21). MSU Center for Research in Mathematics and Science Education, East LansingGoogle Scholar
  97. Schneider B, Carnoy M, Kilpatrick J, Raudenbush S, Schmidt W, Shavelson R (2005) Estimating causal effects in experiments and secondary analyses of large-scale datasets in education: a think tank white paper. American Educational Research Association, Washington, DCGoogle Scholar
  98. Schoenfeld AH (1998) Toward a theory of teaching-in-context. Issues Educ 4(1):1–94. doi: 10.1016/S1080-9724(99)80076-7 Google Scholar
  99. Schoenfeld AH, Minstrell J, van Zee E (2000) The detailed analysis of an established teacher carrying out a non-traditional lesson. J Math Behav 18(3):281–325. doi: 10.1016/S0732-3123 (99)00035-8 Google Scholar
  100. Seidel T, Shavelson RJ (2007) Teaching effectiveness research in the past decade: the role of theory and research design in disentangling meta-analysis results. Rev Educ Res 7(4):454–499. doi: 10.3102/0034654307310317 Google Scholar
  101. Sfard A (2003) Balancing the unbalanceable: the NCTM standards in the light of theories of learning mathematics. In: Kilpatrick J, Martin G, Schifter D (eds) A research companion for NCTM standards. National Council for Teachers of Mathematics, Reston, pp 353–392Google Scholar
  102. Sherin MG (1996) The nature and dynamics of teachers’ content knowledge. Unpublished doctoral dissertation, University of California, BerkeleyGoogle Scholar
  103. Shuell T (1996) Teaching and learning in the classroom context. In: Berliner CD, Calfee RC (eds) Handbook of educational psychology. Macmillan, New York, pp 726–764Google Scholar
  104. Shulman LS (1986) Those who understand: knowledge growth in teaching. Educ Res 15(2):4–14Google Scholar
  105. Shulman LS (1987) Knowledge and teaching: foundations of the new reform. Harv Educ Rev 57(1):1–22Google Scholar
  106. Shulman LS, Quinlan KM (1996) The comparative psychology of school subjects. In: Berliner DC, Calfee RC (eds) Handbook of educational psychology. Macmillan, New York, pp 399–422Google Scholar
  107. Stefanou CR, Perencevich K, DiCintio M, Turner JC (2004) Supporting autonomy in the classroom: ways teachers encourage student decision making and ownership. Educ Psychol 39(2):97–110. doi: 10.1207/s15326985ep3902_2 Google Scholar
  108. Stein MK, Baxter JA, Leinhardt G (1990) Subject-matter knowledge and elementary instruction: a case from functions and graphing. Am Educ Res J 27(4):639–663Google Scholar
  109. Stengel BS (1997) “Academic discipline” and “school subject”: contestable curricular concepts. J Curriculum Stud 29(5):585–602. doi: 10.1080/002202797183928 Google Scholar
  110. Stigler J, Hiebert J (2004) Improving mathematics teaching. Educ Leadersh 61(5):12–17Google Scholar
  111. Stodolsky SS (1988) The subject matters: classroom activity in math and social studies. University of Chicago Press, ChicagoGoogle Scholar
  112. Stodolsky SS, Grossman PL (1995) The impact of subject matter on curricular activity: an analysis of five academic subjects. Am Educ Res J 32(2):227–249Google Scholar
  113. Stuart EA (2007) Estimating causal effects using school-level data sets. Educ Res 36(4):187–198. doi: 10.3102/0013189X07303396 Google Scholar
  114. Swafford JO, Jones GA, Thornton CA (1997) Increased knowledge in geometry and instructional practice. J Res Math Educ 28(4):476–483. doi: 10.2307/749683 Google Scholar
  115. Tatto MT, Schwille J, Senk S, Ingvarson L, Peck R, Rowley G (2008) Teacher Education and Development Study in Mathematics (TEDS-M): conceptual framework. Michigan State University, College of Education, Teacher Education and Development International Study Center, East LansingGoogle Scholar
  116. Thompson PW, Thompson AG (1994) Talking about rates conceptually, part I: a teacher’s struggle. J Res Math Educ 25(3):279–303. doi: 10.2307/749339 Google Scholar
  117. Thompson AG, Thompson PW (1996) Talking about rates conceptually, part II: mathematical knowledge for teaching. J Res Math Educ 27(1):2–24. doi: 10.2307/749194 Google Scholar
  118. Thorndike RL, Hagen E (1971) Cognitive Abilities Test (CAT). Houghton Mifflin, BostonGoogle Scholar
  119. Turner JC, Meyer DK, Cox KE, Logan C, DiCintio M, Thomas CT (1998) Creating contexts for involvement in mathematics. J Educ Psychol 90(4):730–745. doi: 10.1037/0022-0663.90.4.730 Google Scholar
  120. Tymms P (2004) Effect sizes in multilevel models. In: Schagen I, Elliot K (eds) But what does it mean? The use of effect sizes in educational research. National Foundation for Educational Research, London, pp 55–66Google Scholar
  121. Vosniadou S, Vamvakoussi X (2005) Examining mathematics learning from a conceptual change point of view: implications for the design of learning environments. In: Verschaffel L, Dochy F, Boekaerts M, Vosniadou S (eds) Instructional psychology: past, present and future trends. Fifteen essays in honour of Erik De Corte. Elsevier, Oxford, UK, pp 55–70Google Scholar
  122. Vosniadou S, Verschaffel L (2004) Extending the conceptual change approach to mathematics learning and teaching. Learn Instr 14(5):445–451Google Scholar
  123. Walberg HJ, Paik SJ (2000) Effective educational practices. International Academy of Education, BrusselsGoogle Scholar
  124. Walshaw M, Anthony G (2008) The teacher’s role in classroom discourse: a review of recent research into mathematics classrooms. Rev Educ Res 78(3):516–551. doi: 10.3102/0034654308320292 Google Scholar
  125. Wang M, Haertel G, Walberg H (1993) Toward a knowledge base for school learning. Rev Educ Res 63(3):249–294Google Scholar
  126. Warm TA (1989) Weighted likelihood estimation of ability in item response theory. Psychometrika 54(3):427–450. doi: 10.1007/BF02294627 Google Scholar
  127. Wayne AJ, Youngs P (2003) Teacher characteristics and student achievement gains: a review. Rev Educ Res 73(1):89–122. doi: 10.3102/00346543073001089 Google Scholar
  128. Wenglinsky H (2002) How schools matter: the link between teacher classroom practices and student academic performance. Educ Policy Anal Arch 10(12). Retrieved from http://epaa.asu.edu/epaa/v10n12/
  129. Wilson SM, Floden R (2003) Creating effective teachers: concise answers for hard questions. American Association of Colleges for Teacher Education, Washington, DCGoogle Scholar
  130. Wilson SM, Youngs P (2005) Research on accountability processes in teacher education. In: Cochran-Smith M, Zeichner KM (eds) Studying teacher education: the report of the AERA panel on research and teacher education. Erlbaum, Mahwah, pp 591–643Google Scholar
  131. Wilson SM, Floden R, Fernini-Mundy J (2001) Teacher preparation research: current knowledge, gaps, and recommendations. A research report prepared for the U.S. Department of Education. Center for the Study of Teaching and Policy, Washington, DCGoogle Scholar
  132. Winship C, Morgan SL (2007) Counterfactuals and causal inference: methods and principles for social research. Cambridge University Press, Cambridge, UKGoogle Scholar
  133. Wu ML, Adams RJ, Wilson M (1997) ConQuest: generalized item response modelling software manual. Australian Council for Educational Research, MelbourneGoogle Scholar
  134. Zumwalt KM, Craig E (2005) Teachers’ characteristics: research on the indicators of quality. In: Cochran-Smith M, Zeichner KM (eds) Studying teacher education: the report of the AERA panel on research and teacher education. Erlbaum, Mahwah, pp 157–260Google Scholar

Copyright information

© Springer Science+Busine0ss Media New York 2013

Authors and Affiliations

  1. 1.Center for Educational ResearchMax Planck Institute for Human DevelopmentBerlinGermany
  2. 2.Institute of PsychologyGoethe University FrankfurtFrankfurtGermany

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