scholarly journals The impact of teacher attitudes and beliefs about large-scale assessment on the use of provincial data for instructional change

2016 ◽  
Vol 24 ◽  
pp. 109 ◽  
Author(s):  
Derek T. Copp

In the quest to improve measured educational outcomes national governments across the OECD and beyond have instituted large-scale assessment (LSA) policies in their public schools. Controversy almost universally follows the implementation of such testing, related to such topics as: a) the uncertain quality of the tests themselves as psychometrics measures; b) the uses to which the data can and should be put; c) the unintended consequences of test-preparation activities and resulting score inflation; and d) the effects of high-stakes tests on students. Debates of this nature naturally involve and impact the attitudes and opinions of teachers related to their collection and use of these data. This paper examines the impact of these attitudes using both the qualitative and quantitative data from a large-scale research study on Canadian provincial assessment. Data were collected from nation-wide teacher surveys as well as interviews with teachers, administrators and district-level staff. Results show that teacher attitudes about these assessments are strongly correlated to classroom-level instructional change. Three attitudinal factors have significant effects on teaching (to) the provincial curricula, yet none significantly affects the use of less constructive instructional strategies also known as ‘teaching to the test.’ Specifically, the belief that large-scale assessment data have more appropriate uses and the belief that these data could lead to school improvement were significant factors in facilitating change. The implications of these findings are profound in that large-scale assessment policy cannot succeed even by its own standards without more buy in from teaching professionals.

2017 ◽  
Vol 25 ◽  
pp. 115
Author(s):  
Derek T. Copp

Large-scale assessment (LSA) is a tool used by education authorities for several purposes, including the promotion of teacher-based instructional change. In Canada, all 10 provinces engage in large-scale testing across several grade levels and subjects, and also have the common expectation that the results data will be used to improve instruction in classrooms. Yet despite agreement between ministries that instructional change based on LSA results is a positive development and employs data-based decision making at its heart, there remain significant differences in the kinds of incentives written into assessment policies in Canada. It is also true that implementation of the policies is less than uniform between schools and school divisions. Using mixed methods (survey data and follow-up interviews), this study examines which policy factors have the most significant impact on teacher decisions regarding the use of data. The findings indicate that highly incentivized policies correlate well to instructional change including aspects of both teaching (to) the curriculum as well as teaching to the test. Since the latter will be examined as a neither an educationally defensible practice nor a stated policy goal, the statement that ‘incentives work’ does not fully capture the nature of these impacts.


2020 ◽  
pp. 107699862097855
Author(s):  
Takashi Yamashita ◽  
Thomas J. Smith ◽  
Phyllis A. Cummins

In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Mplus. Concise overview and key unique aspects of large-scale assessment data from the 2012/2014 Program for International Assessment of Adult Competencies (PIAAC) are described. Using commonly-used statistical software including SAS and R, a simple macro program and syntax are developed to streamline the data preparation process. Then, two examples of structural equation models are demonstrated using Mplus. The suggested data preparation and analytic approaches can be immediately applicable to existing large-scale assessment data.


2018 ◽  
Vol 167 ◽  
pp. 32-48 ◽  
Author(s):  
Stefa Hirsch ◽  
Katharina Lambert ◽  
Karien Coppens ◽  
Korbinian Moeller

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Tyler H. Matta ◽  
Leslie Rutkowski ◽  
David Rutkowski ◽  
Yuan-Ling Liaw

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