Academic journal article Exceptional Children

Paradigmatic Distinctions between Instructionally Relevant Measurement Models

Academic journal article Exceptional Children

Paradigmatic Distinctions between Instructionally Relevant Measurement Models

Article excerpt

Paradigmatic Distinctions Between Instructionally Relevant Measurement Models

Developing accurate, feasible measurement systems to enhance instructional decision making represents a long-standisng goal of educational research, development, and practice. The notion of adjusting student programs in response to student performance data is a basic principle of effective teachidng (e.g., Eubanks & Levine, 1983; Goodman, 1985; Hoffman & Rutherford, 1984; Rieth, Polsgrove, & Semmel, 1981). Research on teacher planning (e.g., Peterson & Clark, 1978) suggests that teachers enhance student achievement when they accurately assess student knowledge and responsively adapt instruction.

Historically, informal methods, such as classroom ooservation of pupil performance, student response to teacher questioning, and scores on daily assignments, have dominated teacher assessment practice (see Mirkin & Potter, 1982; Salmon-Cox, 1981). Developed within the framework of behavioral psychology during the 1960s, more formal measurement systems were designed to enhance instructional planning. These measurement systems, such as Individually Guided Education (Klausmeier & Ripple, 1971), Individually Prescribed Instruction (Glaser, 1966), and Precision Teaching (White & Haring, 1980), required specification of behavioral objectives and carefully aligned, criterion-referenced assessment.

In the past decade, curriculum-based assessment has become a widely used, related education term. As defined by Tucker (1987), curriculum-based assessment incorporates three key features: Test stimuli are drawn from students' curricula; repeated testings occur across time; and the assessment information is used to formulate instructional decisions. This definition is straightforward; it clearly establishes the salient features shared by all forms of curriculum-based assessment. Yet, despite this clarity about the commonalities across types of curriculum-based assessment, confusion persists about important distinctions among the many variants of curriculum-based assessment.

The purpose of this paper is to identify two major models of instructionally relevant measurement, into which most forms of curriculum-based assessment can be categorized. We refer to the first model, which is highly related to the behaviorally oriented measurement systems of the 1960s, as specific subskill mastery measurement. Most current curriculum-based assessment systems fall into the mastery measurement model. The second model, which we term general outcome measurement, represents a new approach to instructionally relevant measurement. Developed over the past decade, curriculum-based measurement (CBM) (Deno, 1985; Fuchs, 1986; Shinn, 1989) is an example of general outcome measurement.

In this article, we first provide background and rationale for the development of general outcome measurement. Second, we explain the predominant model, specific subskill mastery measurement, by presenting a case study and describing the model's distinguishing features. Next, we illustrate general outcome measurement with a CBM case study and review the distinguishing features of this alternative approach. Finally, we discuss how measuring general outcome indicators can bridge traditional and contemporary assessment paradigms to form an innovative approach to the use of measurement for instructional planning.

BACKGROUND AND RATIONALE FOR

GENERAL OUTCOME MEASUREMENT

The purpose of developing a model for measuring general outcome indicators was to provide teachers with reliable, valid, and efficient procedures for obtaining student performance data to evaluate their instructional programs. The need to develop a general outcome measurement model arose from our earlier experience with the curriculum-based assessment procedures originally recommended within the Data-Based Program Modification (DBPM) moodel (Deno & Mirkin, 1977). …

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