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Introduction

Ensuring that a test will produce results that are valid for the intended uses, such as the placement of students into community college mathematics courses, begins during test development. When test development is a collaboration among intended users, such as the community colleges within a province, communicating to all collaborators the implications of the many decisions that must be made about content, format, scoring, and reporting is especially important.

Objectives

This paper describes and illustrates a validity argument approach to support collaborative test development through the example of Ontario’s Colleges Mathematics Assessment Program (CMAP).

Design/Methodology

For mathematics tests, Schilling and Hill (2007) have proposed a variation on Kane’s (2002, 2013) validity argument approach. The assumptions required to support the proposed use of the test results and corresponding evidence for those assumptions are organized into three categories: (1) Elemental – concerning the performance of specific test items, (2) Structural – concerning the internal structure of the test, and (3) Ecological – concerning the external structure of the test. In this paper, we use Schilling and Hill’s (2007) three categories to relate the assumptions and evidence to decisions made in developing the test.

Results

The resulting validity argument makes explicit why each test development decision is important and what types of evidence might inform or support each decision. For use with collaborators with minimal test development experience or expertise, the elements of the argument are expressed in non-technical language.

Conclusions

In one of their critiques of Kane’s validity argument approach, Schilling and Hill (2007) note the scarcity of real-world examples using an interpretive argument approach. This study provides an illustration of this approach, with a particular emphasis on the use of non-technical language to support collaborative test development.

References

Kane, M. (2002). Validating high-stakes testing programs. Educational Measurement: Issues and Practice, 21(1), 31-41.

Kane, M. (2013). Validating the interpretations and uses of test scores. Journal of Educational Measurement, 50, 1-73.

Schilling, S. G., & Hill, H. C. (2007). Assessing measures of mathematical knowledge for teaching: A validity argument approach. Measurement: Interdisciplinary Research & Perspectives, 5(2/3), 70-80.