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• W231448966 abstract "Despite its widespread use in evaluation data analysis, Null Hypothesis Testing (NHST) has come under persistent criticism resulting in calls for its rethinking, and even possible elimination (Carver, 1978, 1993; Hunter, 1997; Rozeboom, 1960; Schmidt, 1996; Schmidt & Hunter, 1997). As a result, a consensus is beginning emerge that testing, with its strange backward logic and slippery terminology, is generally not well understood by practitioners (Zuckerman, Hodgins, Zuckerman, & Rosenthal, 1993). Critics also claim that tests are overused in a mindless and mechanistic way and interpreted in ways which cannot be supported (Rozeboom, 1997). Others (Cortina & Dunlap, 1997; Frick, 1996; Macdonald, 2002) maintain it is important have a grasp of tests because they are so commonly reported in evaluation and research reports. They conclude that tests have some value and should be rethought rather than eliminated. A real-life example may help illustrate the tension in the testing debate.Amanda teaches two basic writing classes, and this semester she tried an innovation in one class but not the other. Both of the classes are fairly similar, and Amanda used the same end-of-semester test in both classes. She thought the class in which she used the innovation would score higher on the test. After the final compositions were scored, Amanda found that her innovation class did, in fact, score higher than the other class. A friend told her do a statistical test on the scores between the two classes. A manda wasn't sure what it would show, but she conducted a Mest. Her results were t = 4.349, df= 9, p To understand what Amanda wants know, one must first become acquainted with tests, which are a family of statistical procedures for determining the probability or likelihood of achieving certain results. Because these statistical procedures involve a comparison between the actual scores and a hypothesized relationship, they are often referred as Null Hypothesis Testing; (Huberty & Pike, 1999). A null hypothesis states that there is no relationship between the results. NHST is commonly used in studies which report score data (cf., Boylan, Bliss, & Bonham, 1997).Saxon and Boylan issue a call to strengthen developmental education research and make it more accessible (2003, p. 2). Among the types of research they consider appropriate is that which uses control group methodology. This paper responds their suggestion and tries make NHST, an important tool in control group methodology, more accessible. The purpose of this paper is explain NHST, state what tests can and cannot tell us, and make practical recommendations for their use. This paper is not a step-by-step procedure for conducting a test. For that, see general statistical textbooks such as Sirkin (1999, p. 217). Nor does this paper promote quantitative data at the expense of qualitative data. The following questions will be discussed:1. What does the term significance mean?2. What is a test?3. What does a test tell us?4. What does a test not tell us?5. What recommendations can we make for using and interpreting NHST?What Does the Term Significance Mean?In ordinary language, indicates meaning or importance. In evaluation and assessment, however, because of the ambiguity of language, we have be more specific when we talk about evaluation results. Substantive or practical can be used describe any research finding that is useful or that can have an effect on our practice. This is ajudgment call, and thus there is no cut and dried test for substantive (Vogt, 1999, p. …" @default.
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• W231448966 date "2004-04-01" @default.
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• W231448966 title "Research in Practice: Understanding Significance Testing Program Evaluation" @default.
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