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Aligning teacher assessments and teacher learning through a teacher learning progression

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Abstract

This theoretical piece discusses the concept of a teacher learning progression in an attempt to integrate teacher learning and assessment. From the authors’ perspective, the main features of the teacher learning progression are the longitudinal understanding of teacher knowledge and practice, and the opportunity to align teacher evaluations’ formative and summative purposes. Criteria to assess existing teacher learning progressions are proposed and used to examine examples of teacher assessment systems implemented in different parts of the world. The concept of teacher learning progression has national and international implications for teacher training, for teaching assessment and for the design and implementation of educational policies.

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Notes

  1. Cut scores vary by state as do passing rates, and to date state cut scores range from 35 to 41. For details, see Stanford Center for Assessment, Learning, and Equity (SCALE), 2018.

  2. In addition to the Danielson’s framework, teacher assessments have included estimates of teacher value-added based on student performance on standardized tests (Millman, 1997). Value-added measures aim at capturing teacher-specific contribution to the learning process of students taking into consideration variables outside of teachers’ control such as students’ sociodemographic characteristics (Blazar et al. 2016; Close et al. 2020; Harris and McCaffrey 2010). Because of that, value- added measures (teacher effect) are considered fairer than other measures based exclusively on students’ performance level (McCaffrey et al. 2004). The discussion presented in this article, however, will not refer to estimates of teacher effects as they are not linked directly either to a concrete model nor to an operationalization of what teachers should know and be able to do. There is no theory behind the analysis of value-added models in terms of what the standard teacher should achieve and how, nor there are descriptions regarding their progress over time. In that sense, the value-added evaluations provide limited formative information. Furthermore, value-added measures have been criticized because the scales used are often not vertically scaled and narrowly assess basic skill (Darling-Hammond 2012), because of measurement error (Hill 2009), the difficulty to attribute learning gains to multiple teacher present in the classroom or to teachers who are only partially involved (Isenberg and Hock 2011), and the instability of their estimation (Newton et al., 2012). In addition, Rothstein (2010) reports that short-term value-added estimates are weakly related to teachers’ long-run effects. Additionally, the assumption of random assignment of teachers to schools and classrooms and the random assignment of children to schools seldom holds true (Rothstein 2010).

  3. This conceptualization of curriculum content is then seen as the justification for the structure of the typical “standardized test” which is called “domain testing.” In domain testing, the aim is to estimate the proportion of a domain of items related to a concept that a student would get right in an ideal situation at a given point in time—hence, it is fundamentally a cross-sectional perspective. In fact, the student is only given a sample of that domain, and then the true proportion is seen as being estimated by the proportion correct in the sample. In the case of complicated school domains such as “maths” the domain is usually two-level—the coarser level being the overall domain—“maths”—and the finer level being composed of a domain for each of the sub-topics in that particular math curriculum (such as number, geometry, etc.). As the subject changes from year to year (say grade 5 to grade 6), the cross-sectional domain definition changes to map the expected student changes with time. Thus, the different domains for each grade can be seen as a series of cross-sectional perspectives.

  4. They include explaining the material, eliciting student thinking, technology use, recognizing pattern of thinking, generating class conditions for learning, providing feedback and communication with parents and peers. They were developed based on the work of Grossman et al. (2009), and Ball and Forzani (2010).

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Acknowledgements

This research was conducted in part thanks to the support of Conicyt through Project Fondecyt 1160871 and Millenium Nucleous “Experience of Students in Chile´s Higher Education: Expectations and Realities.” We thank the research assistance of Alicia Ibáñez.

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  1. Pontificia Universidad Católica de Chile, Santiago, Chile

    Maria Veronica Santelices

  2. University of California, Berkeley, USA

    Mark Wilson

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Veronica Santelices, M., Wilson, M. Aligning teacher assessments and teacher learning through a teacher learning progression. Educ Asse Eval Acc 34, 509–532 (2022). https://doi.org/10.1007/s11092-022-09388-w

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