Teacher Evaluation, Ambitious Mathematics Instruction, and Mathematical Knowledge for Teaching: Evidence from Early-Career Teachers

Author:
Jihyun Kim Sungshin Women’s University, Seoul, South Korea

Search for other papers by Jihyun Kim in
Current site
Google Scholar
PubMed
Close
,
Kenneth Frank Michigan State University

Search for other papers by Kenneth Frank in
Current site
Google Scholar
PubMed
Close
,
Peter Youngs University of Virginia

Search for other papers by Peter Youngs in
Current site
Google Scholar
PubMed
Close
,
Serena Salloum Ball State University

Search for other papers by Serena Salloum in
Current site
Google Scholar
PubMed
Close
, and
Kristen Bieda Michigan State University

Search for other papers by Kristen Bieda in
Current site
Google Scholar
PubMed
Close

Teacher evaluation policies have been central to policy efforts to enhance teaching quality. At the same time, ambitious mathematics instruction has been emphasized by teacher education programs as well as by the Common Core State Standards. Drawing on observation and survey data from early-career teachers, this study examines how teachers’ perceived pressure of teacher evaluation policies shape their ambitious mathematics instruction. We found that teachers who perceived a strong pressure of teacher evaluation on their instructional practices tended to move further away from enacting ambitious mathematics instruction. Moreover, the negative association between the pressure of teacher evaluation and ambitious instruction was stronger for teachers with a high level of mathematical knowledge for teaching.

Contributor Notes

Jihyun Kim, College of Education, Sungshin Women’s University, Seoul 02844, South Korea; toveave@gmail.com

Kenneth Frank, College of Education, Michigan State University, East Lansing, MI 48864; kenfrank@msu.edu

Peter Youngs, School of Education and Human Development, University of Virginia, Charlottesville, VA 22903; pay2n@virginia.edu

Serena Salloum, Teachers College, Ball State University, Muncie, IN 47306; sjsalloum@bsu.edu

Kristen Bieda, College of Education, Michigan State University, East Lansing, MI 48864; kbieda@msu.edu

  • Collapse
  • Expand
Journal for Research in Mathematics Education
  • Ball, D. L., Thames, M. H., & Phelps, G. (2008). Content knowledge for teaching: What makes it special? Journal of Teacher Education, 59(5), 389407. https://doi.org/10.1177/0022487108324554

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bidwell, C. E. (2001). Analyzing schools as organizations: Long-term permanence and short-term change. Sociology of Education, 74, 100114. https://doi.org/10.2307/2673256

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bieda, K. N., Lane, J., Evert, K., Hu, S., Opperman, A., & Ellefson, N. (2020). A large-scale study of how districts’ curriculum policies and practices shape teachers’ mathematics lesson planning. Journal of Curriculum Studies, 52(6), 770799. https://doi.org/10.1080/00220272.2020.1754921

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blazar, D. (2015). Effective teaching in elementary mathematics: Identifying classroom practices that support student achievement. Economics of Education Review, 48, 1629. https://doi.org/10.1016/j.econedurev.2015.05.005

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bloom, H. S. (1995). Minimum detectable effects: A simple way to report the statistical power of experimental designs. Evaluation Review, 19(5), 547556. https://doi.org/10.1177/0193841X9501900504

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boston, M. (2012). Assessing instructional quality in mathematics. The Elementary School Journal, 113(1), 76104. https://doi.org/10.1086/666387

  • Bridwell-Mitchell, E. N., & Sherer, D. G. (2017). Institutional complexity and policy implementation: How underlying logics drive teacher interpretations of reform. Educational Evaluation and Policy Analysis, 39(2), 223247. https://doi.org/10.3102/0162373716677567

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, A., & Croudace, T. J. (2015). Scoring and estimating score precision using multidimensional IRT models. In S. P. Reise & D. A. Revicki (Eds.), Handbook of item response theory modeling: Applications to typical performance assessment (pp. 307333). Routledge.

    • Search Google Scholar
    • Export Citation
  • Butters, R. B., Asarta, C. J., & Fischer, T. J. (2011). Human capital in the classroom: The role of teacher knowledge in economic literacy. The American Economist, 56(2), 4757. https://doi.org/10.1177/056943451105600207

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cobb, P., & Smith, T. (2008). District development as a means of improving mathematics teaching and learning at scale. In K. Krainer & T. Wood (Eds.), International handbook of mathematics teacher education: Vol. 3. Participants in mathematics teacher education (pp. 231254). Sense. https://doi.org/10.1163/9789087905491_012

    • Search Google Scholar
    • Export Citation
  • Coburn, C. E. (2001). Collective sensemaking about reading: How teachers mediate reading policy in their professional communities. Educational Evaluation and Policy Analysis, 23(2), 145170. https://doi.org/10.3102/01623737023002145

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coburn, C. E., Hill, H. C., & Spillane, J. P. (2016). Alignment and accountability in policy design and implementation: The Common Core State Standards and implementation research. Educational Researcher, 45(4), 243251. https://doi.org/10.3102/0013189X16651080

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coburn, C. E., & Russell, J. L. (2008). District policy and teachers’ social networks. Educational Evaluation and Policy Analysis, 30(3), 203235. https://doi.org/10.3102/0162373708321829

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Routledge. https://doi.org/10.4324/9780203774441

    • Search Google Scholar
    • Export Citation
  • Cook, T. D., Shadish, W. R., & Wong, V. C. (2008). Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons. Journal of Policy Analysis and Management, 27(4), 724750. https://doi.org/10.1002/pam.20375

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Danielson, C. (2013). Framework for Teaching evaluation instrument. The Danielson Group. https://danielsongroup.org/downloads/framework-teaching-evaluation-instrument

    • Search Google Scholar
    • Export Citation
  • Dee, T. S., & Wyckoff, J. (2015). Incentives, selection, and teacher performance: Evidence from IMPACT. Journal of Policy Analysis and Management, 34(2), 267297. https://doi.org/10.1002/pam.21818

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delvaux, E., Vanhoof, J., Tuytens, M., Vekeman, E., Devos, G., & Van Petegem, P. (2013). How may teacher evaluation have an impact on professional development? A multilevel analysis. Teaching and Teacher Education, 36, 111. https://doi.org/10.1016/j.tate.2013.06.011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donaldson, M. L. (2012). Teachers’ perspectives on evaluation reform. Center for American Progress. https://www.americanprogress.org/article/teachers-perspectives-on-evaluation-reform/

    • Search Google Scholar
    • Export Citation
  • Donaldson, M. L., Woulfin, S., LeChasseur, K., & Cobb, C. D. (2016). The structure and substance of teachers’ opportunities to learn about teacher evaluation reform: Promise or pitfall for equity? Equity & Excellence in Education, 49(2), 183201. https://doi.org/10.1080/10665684.2016.1144831

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Egalite, A. J., Fusarelli, L. D., & Fusarelli, B. C. (2017). Will decentralization affect educational inequity? The Every Student Succeeds Act. Educational Administration Quarterly, 53(5), 757781. https://doi.org/10.1177/0013161X17735869

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Erdfelder, E., Faul, F., & Buchner, A. (1996). GPOWER: A general power analysis program. Behavior Research Methods, Instruments, & Computers, 28(1), 111. https://doi.org/10.3758/BF03203630

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Every Student Succeeds Act, 20 U.S.C. § 6301 (2015). https://www.congress.gov/114/plaws/publ95/PLAW-114publ95.pdf

  • Firestone, W. A., Herriott, R. E., & Wilson, B. L. (1984). Explaining differences between elementary and secondary schools: Individual, organizational, and institutional perspectives. Research for Better Schools. https://files.eric.ed.gov/fulltext/ED342054.pdf

    • Search Google Scholar
    • Export Citation
  • Frank, K. A. (2000). Impact of a confounding variable on a regression coefficient. Sociological Methods & Research, 29(2), 147194. https://doi.org/10.1177/0049124100029002001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frank, K. A., Kim, J., Salloum, S. J., Bieda, K. N., & Youngs, P. (2020). From interpretation to instructional practice: A network study of early-career teachers’ sensemaking in the era of accountability pressures and Common Core State Standards. American Educational Research Journal, 57(6), 22932338. https://doi.org/10.3102/0002831220911065

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frank, K. A., Maroulis, S. J., Duong, M. Q., & Kelcey, B. M. (2013). What would it take to change an inference? Using Rubin’s causal model to interpret the robustness of causal inferences. Educational Evaluation and Policy Analysis, 35(4), 437460. https://doi.org/10.3102/0162373713493129

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frank, K. A., Zhao, Y., & Borman, K. (2004). Social capital and the diffusion of innovations within organizations: The case of computer technology in schools. Sociology of Education, 77(2), 148171. https://doi.org/10.1177/003804070407700203

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frank, K. A., Zhao, Y., Penuel, W. R., Ellefson, N., & Porter, S. (2011). Focus, fiddle, and friends: Experiences that transform knowledge for the implementation of innovations. Sociology of Education, 84(2), 137156. https://doi.org/10.1177/0038040711401812

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grossman, P. L., Valencia, S. W., Evans, K., Thompson, C., Martin, S., & Place, N. (2000). Transitions into teaching: Learning to teach writing in teacher education and beyond. Journal of Literacy Research, 32(4), 631662. https://doi.org/10.1080/10862960009548098

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hallinger, P., Heck, R. H., & Murphy, J. (2014). Teacher evaluation and school improvement: An analysis of the evidence. Educational Assessment, Evaluation and Accountability, 26(1), 528. https://doi.org/10.1007/s11092-013-9179-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heid, M. K., Blume, G. W., Zbiek, R. M., & Edwards, B. S. (1998). Factors that influence teachers learning to do interviews to understand students’ mathematical understandings. Educational Studies in Mathematics, 37(3), 223249. https://doi.org/10.1023/A:1003657820047

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herbst, P., & Chazan, D. (2012). On the instructional triangle and sources of justification for actions in mathematics teaching. ZDM, 44(5), 601612. https://doi.org/10.1007/s11858-012-0438-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hill, H. C., Ball, D. L., Blunk, M., Goffney, I. M., & Rowan, B. (2007). Validating the ecological assumption: The relationship of measure scores to classroom teaching and student learning. Measurement: Interdisciplinary Research and Perspectives, 5(2–3), 107118. https://doi.org/10.1080/15366360701487138

    • Search Google Scholar
    • Export Citation
  • Hill, H. C., & Charalambous, C. Y. (2012). Teacher knowledge, curriculum materials, and quality of instruction: Lessons learned and open issues. Journal of Curriculum Studies, 44(4), 559576. https://doi.org/10.1080/00220272.2012.716978

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42(2), 371406. https://doi.org/10.3102/00028312042002371

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hill, H. C., Schilling, S. G., & Ball, D. L. (2004). Developing measures of teachers’ mathematics knowledge for teaching. The Elementary School Journal, 105(1), 1130. https://doi.org/10.1086/428763.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, J. Y., Sporte, S. E., & Luppescu, S. (2015). Teacher perspectives on evaluation reform: Chicago’s REACH students. Educational Researcher, 44(2), 105116. https://doi.org/10.3102/0013189X15575517

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kane, T. J., Owens, A. M., Marinell, W. H., Thal, D. R. C., & Staiger, D. O. (2016). Teaching higher: Educators’ perspectives on Common Core implementation. Center for Education Policy Research, Harvard University. https://cepr.harvard.edu/files/cepr/files/teaching-higher-report.pdf?m=1601433015

    • Search Google Scholar
    • Export Citation
  • Kim, J., Sun, M., & Youngs, P. (2019). Developing the “will": The relationship between teachers’ perceived policy legitimacy and instructional improvement. Teachers College Record, 121(3), 144. https://www.tcrecord.org/content.asp?contentid=22590

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koedel, C., Li, J., Springer, M. G., & Tan, L. (2019). Teacher performance ratings and professional improvement. Journal of Research on Educational Effectiveness, 12(1), 90115. https://doi.org/10.1080/19345747.2018.1490471

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kraft, M. A., & Gilmour, A. F. (2017). Revisiting The Widget Effect: Teacher evaluation reforms and the distribution of teacher effectiveness. Educational Researcher, 46(5), 234249. https://doi.org/10.3102/0013189X17718797

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lampert, M., Beasley, H., Ghousseini, H., Kazemi, E., & Franke, M. (2010). Using designed instructional activities to enable novices to manage ambitious mathematics teaching. In M. K. Stein & L. Kucan (Eds.), Instructional explanations in the discipline (pp. 129141). Springer. https://doi.org/10.1007/978-1-4419-0594-9_9

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lampert, M., Franke, M. L., Kazemi, E., Ghousseini, H., Turrou, A. C., Beasley, H., Cunard, A., & Crowe, K. (2013). Keeping it complex: Using rehearsals to support novice teacher learning of ambitious teaching. Journal of Teacher Education, 64(3), 226243. https://doi.org/10.1177/0022487112473837

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159174. https://doi.org/10.2307/2529310

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lave, J. (1996). Teaching, as learning, in practice. Mind, Culture, and Activity, 3(3), 149164. https://doi.org/10.1207/s15327884mca0303_2

  • Learning Mathematics for Teaching Project. (2011). Measuring the mathematical quality of instruction. Journal of Mathematics Teacher Education, 14(1), 2547. https://doi.org/10.1007/s10857-010-9140-1

    • Search Google Scholar
    • Export Citation
  • Leko, M. M., & Brownell, M. T. (2011). Special education preservice teachers’ appropriation of pedagogical tools for teaching reading. Exceptional Children, 77(2), 229251. https://doi.org/10.1177/001440291107700205

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McLaughlin, M. W. (1987). Learning from experience: Lessons from policy implementation. Educational Evaluation and Policy Analysis, 9(2), 171178. https://doi.org/10.3102/01623737009002171

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McNeil, L. M. (2000). Contradictions of school reform: Educational costs of standardized testing. Routledge.

  • National Governors Association Center for Best Practices & Council of Chief State School Officers. (n.d.-a). Frequently asked questions. http://www.corestandards.org/wp-content/uploads/FAQs.pdf

  • National Governors Association Center for Best Practices & Council of Chief State School Officers. (n.d.-b). Key shifts in mathematics. http://www.corestandards.org/other-resources/key-shifts-in-mathematics/

  • National Governors Association Center for Best Practices & Council of Chief State School Officers. (2010). Common core state standards for mathematics. http://www.corestandards.org

  • Opfer, V. D., Kaufman, J. H., & Thompson, L. E. (2016). Implementation of K–12 State Standards for mathematics and English language arts and literacy: Findings from the American Teacher Panel. RAND.

    • Search Google Scholar
    • Export Citation
  • Penuel, W. R., Sun, M., Frank, K. A., & Gallagher, H. A. (2012). Using social network analysis to study how collegial interactions can augment teacher learning from external professional development. American Journal of Education, 119(1), 103136. https://doi.org/10.1086/667756

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polikoff, M. S., & Porter, A. C. (2014). Instructional alignment as a measure of teaching quality. Educational Evaluation and Policy Analysis, 36(4), 399416. https://doi.org/10.3102/0162373714531851

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Porter, A., McMaken, J., Hwang, J., & Yang, R. (2011). Common Core standards: The new U.S. intended curriculum. Educational Researcher, 40(3), 103116. https://doi.org/10.3102/0013189X11405038

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Sage.

  • Reinhorn, S. K., Johnson, S. M., & Simon, N. S. (2017). Investing in development: Six high-performing, high-poverty schools implement the Massachusetts teacher evaluation policy. Educational Evaluation and Policy Analysis, 39(3), 383406. https://doi.org/10.3102/0162373717690605

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rogoff, B. (1994). Developing understanding of the idea of communities of learners. Mind, Culture, and Activity, 1(4), 209229.

  • Schmitt, N. (1996). Uses and abuses of coefficient alpha. Psychological Assessment, 8(4), 350353. https://doi.org/10.1037/1040-3590.8.4.350

  • Schoenfeld, A. H., Floden, R. E., & the Algebra Teaching Study and Mathematics Assessment Project. (2014). TRU Math: Teaching for robust understanding in mathematics scoring rubric. Graduate School of Education, University of California–Berkeley & College of Education, Michigan State University. https://www.map.mathshell.org/trumath/tru_math_rubric_alpha_20140731.pdf

    • Search Google Scholar
    • Export Citation
  • Sobolewski-McMahon, L. M. (2017). The influences of middle school mathematics teachers’ practical rationality on instructional decision making regarding the Common Core State Standards for Mathematical Practices [Doctoral dissertation, Kent State University]. OhioLINK. http://rave.ohiolink.edu/etdc/view?acc_num=kent1499089403680548

    • Search Google Scholar
    • Export Citation
  • Spillane, J. P., Reiser, B. J., & Reimer, T. (2002). Policy implementation and cognition: Reframing and refocusing implementation research. Review of Educational Research, 72(3), 387431. https://doi.org/10.3102/00346543072003387

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stecher, B. M., Holtzman, D. J., Garet, M. S., Hamilton, L. S., Engberg, J., Steiner, E. D., Robyn, A., Baird, M. D., Gutierrez, I. A., Peet, E. D., Brodziak de los Reyes, I., Fronberg, K., Weinberger, G., Hunter, G. P., & Chambers, J. (2018). Improving teaching effectiveness: The Intensive Partnerships for Effective Teaching through 2015–2016. RAND. http://rand.org/pubs/research_reports/RR2242.html

    • Search Google Scholar
    • Export Citation
  • Steinberg, M. P., & Donaldson, M. L. (2016). The new educational accountability: Understanding the landscape of teacher evaluation in the post-NCLB era. Education Finance and Policy, 11(3), 340359. https://doi.org/10.1162/EDFP_a_00186

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steinberg, M. P., & Sartain, L. (2015). Does teacher evaluation improve school performance? Experimental evidence from Chicago’s Excellence in Teaching Project. Education Finance and Policy, 10(4), 535572. https://doi.org/10.1162/EDFP_a_00173

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroupe, D. (2016). Beginning teachers’ use of resources to enact and learn from ambitious instruction. Cognition and Instruction, 34(1), 5177. https://doi.org/10.1080/07370008.2015.1129337

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, M., Frank, K. A., Penuel, W. R., & Kim, C. M. (2013). How external institutions penetrate schools through formal and informal leaders. Educational Administration Quarterly, 49(4), 610644. https://doi.org/10.1177/0013161X12468148

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, E. S., & Tyler, J. H. (2012). The effect of evaluation on teacher performance. American Economic Review, 102(7), 36283651. https://doi.org/10.1257/aer.102.7.3628

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thames, M. H., & Ball, D. L. (2010). What math knowledge does teaching require? Teaching Children Mathematics, 17(4), 220229. https://doi.org/10.5951/TCM.17.4.0220

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, J., Windschitl, M., & Braaten, M. (2013). Developing a theory of ambitious early-career teacher practice. American Educational Research Journal, 50(3), 574615. https://doi.org/10.3102/0002831213476334

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tuytens, M., & Devos, G. (2009). Teachers’ perception of the new teacher evaluation policy: A validity study of the Policy Characteristics Scale. Teaching and Teacher Education, 25(6), 924930. https://doi.org/10.1016/j.tate.2009.02.014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • University of Chicago Consortium on Chicago School Research. (2017). 5Essentials survey.

  • Welch, M. J., Davis, S., Isaia, R. G., Johnston, W. T., Stein, L. B., Jenuwine, H., & Macdonald, K. (2016). Aligning evaluation: How much do teacher evaluation rubrics emphasize Common Core instruction? American Institutes for Research. https://www.air.org/sites/default/files/downloads/report/Teacher-Evaluation-Common-Core-Alignment-October-2016.pdf

    • Search Google Scholar
    • Export Citation
  • Wiseman, D. L. (2012). The intersection of policy, reform, and teacher education. Journal of Teacher Education, 63(2), 8791. https://doi.org/10.1177/0022487111429128

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 2219 1017 474
Full Text Views 644 100 9
PDF Downloads 852 162 15
EPUB Downloads 0 0 0