Using Video to Examine Formative Assessment Practices as Measures of Expertise for Mathematics and Science Teachers

  • Amelia Wenk GotwalsEmail author
  • Joanne Philhower
  • Dante Cisterna
  • Steven Bennett


Formative assessment practices, including eliciting a broad range of student ideas, noticing the nuances in students' ideas, using these ideas to guide instruction, and promoting student self-regulation of learning are key components of expert teaching. Given the inherent dialogical nature of formative assessment in the classroom, video can provide a powerful tool for capturing and analyzing teachers' formative assessment interactions with students. In this study, we provide a framework for examining expertise in formative assessment and use this framework to quantitatively and qualitatively analyze the practices of 13 mathematics and science teachers. While we only saw a few instances of true expertise in formative assessment practices in our examination of videos, our findings indicate that teachers with more expertise in formative assessment let students' ideas guide their teaching. This leads to higher correlations among the dimensions of practice that we articulate in our framework for expert teachers. However, because many of the instructional decisions that teachers make are not visible on video, video alone may not provide enough information to judge expertise in formative assessment.


Formative assessment Video analysis Mathematics Science 



Work on the Formative Assessment for Michigan Educators (FAME) project was supported by the Michigan Department of Education.


  1. Allal, L. (2010). Assessment and the regulation of learning. In P. Peterson, E. Baker & B. McGaw (Eds.), International Encyclopedia of Education (Vol. 3, pp. 348–352). Oxford, England: Elsevier.CrossRefGoogle Scholar
  2. Ash, D. & Lewitt, K. (2003). Working within the zone of proximal development: formative assessment as professional development. Journal of Science Teacher Education, 14(1), 23–48.CrossRefGoogle Scholar
  3. Ausubel, D. P. (1968). Educational psychology: a cognitive view. New York, NY: Holt, Rinehart & Winston.Google Scholar
  4. Bell, B. & Cowie, B. (2001). The characteristics of formative assessment in science education. Science Education, 85, 536–553.CrossRefGoogle Scholar
  5. Bennett, R. (2011). Formative assessment: a critical review. Assessment in Education: Principles, Policy & Practice, 18(1), 5–25.CrossRefGoogle Scholar
  6. Black, P., Harrison, C., Lee, C., Marshall, B. & Wiliam, D. (2004). Working inside the black box: assessment for learning in the classroom. Phi Delta Kappan, 86(1), 8–21.CrossRefGoogle Scholar
  7. Black, P. & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy and Practice, 5(1), 7–73.CrossRefGoogle Scholar
  8. Bransford, J. D., Brown, A. L. & Cocking, R. R. (1999). How people learn: brain, mind, experience, and school. Washington, D.C: National Academy Press.Google Scholar
  9. Buck, G. A. & Trauth-Nare, A. E. (2009). Preparing teachers to make formative assessment process integral to science teaching and learning. Journal of Science Teacher Education, 20, 475–494.CrossRefGoogle Scholar
  10. Coffey, J. E., Hammer, D., Levin, D. M. & Grant, T. (2011). The missing disciplinary substance of formative assessment. Journal of Research in Science Teaching, 48(10), 1109–1136.CrossRefGoogle Scholar
  11. Cowie, B. & Bell, B. (2001). A model of formative assessment in science education. Assessment in Education, 6(1), 101–116.CrossRefGoogle Scholar
  12. Crossouard, B. & Pryor, J. (2012). How theory matters: formative assessment theory and practices and their different relations to education. Studies in Philosophy and Education, 31(3), 251–263.CrossRefGoogle Scholar
  13. di Sessa, A. A. & Minstrell, J. (1998). Cultivating conceptual change with benchmark lessons. In J. G. Greeno & S. V. Goldman (Eds.), Thinking practices in mathematics and science learning (pp. 155–187). New York, NY: Routledge.Google Scholar
  14. Duschl, R. A. & Gitomer, D. H. (1997). Strategies and challenges to changing the focus of assessment and instruction in science classrooms. Educational Assessment, 4(1), 37–73.CrossRefGoogle Scholar
  15. Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In A. Ericsson, N. Charness, P. J. Feltovich & R. R. Hoffman (Eds.), The Cambridge Handbook of Expertise and Expert Performance. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  16. Franke, M. L., Carpenter, T. P., Levi, L. & Fennema, E. (2001). Capturing teacher's generative growth: a follow-up study of professional development in mathematics. American Education Research Journal, 38(3), 653–690.CrossRefGoogle Scholar
  17. Frederiksen, J. R., Sipusic, M., Sherin, M. & Wolfe, E. W. (1998). Video portfolio assessment: creating a framework for viewing the functions of teaching. Educational Assessment, 5(4), 225–297.CrossRefGoogle Scholar
  18. Furtak, E. M., Thompson, J., Braaten, M. & Windschitl, M. (2012). Learning progressions to support ambitious teaching practices. In A. C. Alonzo & A. W. Gotwals (Eds.), Learning Progressions in Science. Rotterdam, The Netherlands: Sense Publishers.Google Scholar
  19. Hammer, D. (2004). The variability of student reasoning, lecture 3: manifold cognitive resources. In E. Redish & M. Vicentini (Eds.), Proceedings of the Enrico Fermi Summer School, Course CLVI (pp. 321–340). Bologna, Italiana: Italian Physical Society.Google Scholar
  20. Hatch, T. & Grossman, P. L. (2009). Learning to look beyond the boundaries of representation: using technology to examine teaching (overview for a digital exhibition: learning from the practice of teaching). Journal of Teacher Education, 60(1), 70–85.CrossRefGoogle Scholar
  21. Hattie, J. & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.CrossRefGoogle Scholar
  22. Henningson, M. & Stein, M. K. (1997). Mathematical tasks and student cognition: classroom based factors that support and inhibit mathematical thinking and reasoning. Journal for Research in Mathematics Education, 28(5), 524–549.CrossRefGoogle Scholar
  23. Heritage, M. (2007). Formative assessment: what do teachers need to know and do? Phi Delta Kappan, 89(2), 140–145.CrossRefGoogle Scholar
  24. Hill, H. C., Ball, D. L. & Schilling, S. G. (2008). Unpacking pedagogical content knowledge: conceptualizing and measuring teachers’ topic specific knowledge of students. Journal for Research in Mathematics Education, 39(4), 372–400.Google Scholar
  25. Hodgen, J. & Wiliam, D. (2006). Mathematics inside the black box: assessment for learning in the mathematics classroom. London, England: GL Assessment Limited.Google Scholar
  26. Kennedy, M. M. (2010). Approaches to annual performance assessment. In M. M. Kennedy (Ed.), Teacher Assessment and the Quest for Teacher Quality. San Francisco, CA: Jossey-Bass.Google Scholar
  27. Kohler, F., Henning & Usma-Wilches, J. (2008). Preparing preservice teachers to make instructional decisions: an examination of data from the teacher work sample. Teaching and Teacher Education, 24(8), 2108–2117.CrossRefGoogle Scholar
  28. Lampert, M., Beasley, H., Ghousseini, H., Kazemi, E. & Franke, M. (2010). Using designed instructional activities to enable novices to manage ambitious mathematics teaching. In Instructional explanations in the disciplines (pp. 129-141). New York , NY: Springer.Google Scholar
  29. Lampert, M. & Graziani, F. (2009). Instructional activities as a tool for teachers’ and teacher educators’ learning. The Elementary School Journal, 109(5), 491–509.CrossRefGoogle Scholar
  30. Leahy, S., Lyon, C., Thompson, M. & Wiliam, D. (2005). Classroom assessment—minute by minute, day by day. Educational Leadership, 63, 18–24.Google Scholar
  31. Martin, S. & Siry, C. (2012). An analysis of the utilization of video-based media in science teacher education. In B. Fraser, K. Tobin & C. Campbell (Eds.), International handbook of science teaching and learning. (pp. 417–433). Rotterdam: Springer.Google Scholar
  32. McCaffrey, J. R., Lockwood, D. F., Koretz, D. M. & Hamilton, L. S. (2003). Evaluating value added models for teacher accountability [Monograph]. Retrieved from
  33. Otero, V. (2006). Moving beyond the “Get it or don’t” conception of formative assessment. Journal of Teacher Education, 57(3), 247–255.CrossRefGoogle Scholar
  34. Pryor, J. & Crossouard, B. (2010). Challenging formative assessment: disciplinary spaces and identities. Assessment & Evaluation in Higher Education, 35(3), 265–276.CrossRefGoogle Scholar
  35. Rakoczy, K., Harks, B., Klieme, E., Blum, W. & Hochweber, J. (2013). Written feedback in mathematics: mediated by students’ perception, moderated by goal orientation. Learning and Instruction, 27, 63–73.CrossRefGoogle Scholar
  36. Rivkin, S. G., Hanushek, E. A. & Kain, J. F. (2005). Teachers, schools, and academic achievement. Econometrics, 73(2), 417–458.CrossRefGoogle Scholar
  37. Ross, J. A., Hogaboam-Gray, A. & Rolheiser, C. (2002). Student self-evaluation in grade 5−6 mathematics effects on problem-solving achievement. Educational Assessment, 8(1), 43–58.CrossRefGoogle Scholar
  38. Ruiz-Primo, M. A. (2011). Informal formative assessment: the role of instructional dialogues in assessing students for science learning. Special issue in assessment for learning, Studies of Educational Evaluation, 37(1), 15–24.Google Scholar
  39. Ruiz-Primo, M. A. & Furtak, E. M. (2006). Informal formative assessment and scientific inquiry: exploring teachers’ practices and student learning. Educational Assessment, 11(3–4), 205–235.Google Scholar
  40. Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18, 119–144.CrossRefGoogle Scholar
  41. Sanders, W. L. & Rivers, J. C. (1996). Cumulative and residual effects of teachers on future student academic achievement (Research Progress Report). Knoxville, TN: University of Tennessee Value-Added Research and Assessment Center.Google Scholar
  42. Santagata, R., Zannoni, C. & Stigler, J. W. (2007). The role of lesson analysis in pre-service teacher education: an empirical investigation of teacher learning from a virtual video-based field experience. Journal of Mathematics Teacher Education, 10(2), 123–140.CrossRefGoogle Scholar
  43. Sawyer, R. K. (2008). Optimizing learning: implications of learning sciences research. Paper presented at the OECD/CERI International Conference, “Learning in the 21st Century: Research, Innovation and Policy,” Paris, France. Retrieved from
  44. Shepard, L. A. (2000). The role of assessment in a learning culture. Educational Researcher, 29(7), 4–14.CrossRefGoogle Scholar
  45. Sherin, M. G., Russ, R. S. & Colestock, A. A. (2011). Accessing mathematics teachers’ in-the-moment noticing. In M. G. Sherin, V. R. Jacobs & R. A. Philipp (Eds.), Mathematics Teacher Noticing (pp. 79–94). New York, NY: Routledge.Google Scholar
  46. Shih, S. S. & Alexander, J. M. (2000). Interacting effects of goal setting and self- or other-referenced feedback on children’s development of self-efficacy and cognitive skill within the Taiwanese classroom. Journal of Educational Psychology, 92(3), 536–543.CrossRefGoogle Scholar
  47. Smith, M. S. & Stein, M. K. (2011). 5 Practices for Orchestrating Productive Mathematics Discussions. Reston, VA: National Council of Teachers of Mathematics.Google Scholar
  48. Stigler, J. W., Gallimore, R. & Hiebert, J. (2000). Using video surveys to compare classrooms and teaching across cultures: examples and lessons from the TIMSS video studies. Educational Psychologist, 35(2), 87–100.CrossRefGoogle Scholar
  49. Tanner, H. & Jones, S. (2003). Self-efficacy in mathematics and students’ use of self-regulated learning strategies during assessment events. In N. A. Pateman, B. J., Dougherty & J. T. Zilliox (Eds.), Proceedings of the 2003 Joint Meeting of PME and PMENA (pp. 275–281). Honolulu, HI: CRDG, College of Education, University of Hawai’i.Google Scholar
  50. Teddlie, C. & Tashakkori, A. (2009). Foundations of mixed methods research: integrating quantitative and qualitative approaches in the social and behavioral sciences. Thousand Oaks, CA: Sage Publications Inc.Google Scholar
  51. Tell, C. A., Bodone, F. M. & Addie, K. L. (2000). A framework of teacher knowledge and skills necessary in a standards-based system: lessons from high school and university faculty. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA. Retrieved from
  52. Tschannen-Moran, M., Hoy, A. W. & Hoy, W. K. (1998). Teacher efficacy: its meaning and measure. Review of Educational Research, 68(2), 202–248.CrossRefGoogle Scholar
  53. Webb, M. & Jones, J. (2009). Exploring tensions in developing assessment for learning. Assessment in Education: Principles, Policy & Practice, 16(2), 165–184.CrossRefGoogle Scholar
  54. White, B. Y. & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition. Making science accessible to all students. Cognition and Instruction, 16(1), 3–118.CrossRefGoogle Scholar
  55. Wiliam, D. (2006). Formative assessment: getting the focus right. Educational Assessment, 11(3–4), 283–289.CrossRefGoogle Scholar
  56. Wiliam, D. (2009). An integrative summary of the research literature and implications for a new theory of formative assessment. In H. L. Andrade & G. J. Cizek (Eds.), Handbook of formative assessment. (pp. 18–40). New York, NY: Taylor & Francis.Google Scholar
  57. Windschitl, M., Thompson, J., Braaten, M. & Stroupe, D. (2012). Proposing a core set of instructional practices and tools for teachers of science. Science Education, 96(5), 878–903.CrossRefGoogle Scholar
  58. Windschitl, M. Thompson, J. & Braaten, M. (2011) Ambitious pedagogy by novice teachers? Who benefits from tool-supported collaborative inquiry into practice and why. Teachers College Record, 13(7), 1311–1360.Google Scholar
  59. Wright, S. P., Horn, S. P. & Sanders, W. L. (1997). Teachers and classroom context effects on student achievement: implications for teacher evaluation. Journal of Personnel Evaluation in Education, 11, 57–67.CrossRefGoogle Scholar

Copyright information

© Ministry of Science and Technology, Taiwan 2015

Authors and Affiliations

  • Amelia Wenk Gotwals
    • 1
    Email author
  • Joanne Philhower
    • 1
  • Dante Cisterna
    • 2
  • Steven Bennett
    • 1
  1. 1.Michigan State UniversityEast LansingUSA
  2. 2.Facultad de EducaciónPontificia Universidad Católica de ChileMaculChile

Personalised recommendations