Margaret E. Bell

Formulation of a Structural Equation Model for the Evaluation of Curriculum

Program evaluation has made several advances in recent years. Among the new developments are improved quasi-experimental designs for use in field settings (Cook & Campbell, 1979) and sophisticated statistical techniques such as analysis of covariance. Other developments, however, are in response to the need to replace the experimental/control group paradigm with evaluations that identify the merits and characteristics of the curriculum under study. Expressed first in the sixties (Cronbach, 1963), the practice of course comparisons was identified as inappropriate for decisions about course effectiveness. First, an experiment at best compares the present version of one course with the present version of another course (Cronbach, 1963). Furthermore, two courses in the same subject often differ in content topics that are included and degree of emphasis on common content (Cronbach & Snow, 1977). As an alternative to course comparisons, Cronbach (1963) identified two major purposes for curriculum evaluation: (a) to understand the ways in which a course or program produces its effects and to describe the parameters that alter or otherwise influence course effectiveness, and (b) to provide insights into educational learning. That is, evaluations should accomplish more than reporting on the program characteristics related to effectiveness. In addition, evaluation studies should provide information that contributes to the development of future

The Influence of Sex and Race on the Test Scores of Research Subjects Exposed to Research Purpose Information

Summary The study looked at the different reactions of subgroups within a sample of undergraduates to different research purpose information. In the sample there were 80 males and 206 females, 43 blacks and 243 whites. Ss were assigned to one of three treatment groups which received (a) positive information which indicated high scores on the dependent variables were desirable; (b) neutral information which provided no expectation; or (c) negative information which indicated low scores were desirable. The results indicated that there were significant differences on the positive and negative treatments between males and females and also between blacks and whites. The data suggest that information about the expected outcomes of a research study will affect different subgroups in a population, causing significant changes in the data.

Structural Equation Modeling: An Alternative to Traditional Validation Techniques

Validation of the sequencing of objectives is an important step in structural design. Prior statistical techniques, such as the reproducibility coefficient, have yielded only summary information. In contrast, structural equation modeling provides both goodness-of-fit indices and effect coefficients for links or paths between time-ordered events, i.e., objectives. Discussed here is the application of structural equation modeling to a set of objectives in a senior-level cardiovascular nursing course. Consistent with the theory-based requirement of structural equation modeling, the objectives were developed using Robert Gagnés conditions of learning. Also discussed is the use of “t” values, which indicate statistical significance of the paths, for testing instructional links in the learning model.

COMMON FACTORS IN SEX AND RACE DISCRIMINATION

The attitudes of white males, white females, black males, and black females toward changing roles for women and blacks were determined using a Likert scale. Principal components factor analysis with varimax rotations was used to identify items that loaded at least .40 on the factors. Significant differences at the .001 level (df — 3/82) were found for the total instrument, Factor I, Factor II, and the subscales on role change for blacks and females. The strongest bias was expressed by blacks on the total scale and Factor I (Changes in the Status Quo) and by white females on role change for blacks and Factor II (Strategies for Equalization).

Research Purpose Information and Affective Instrument Scores.

Research studies have indicated that when subjects are given cues or information about the purpose of a research study the scores on a psychological measure tend to increase in a positive direction. In this study 100 undergraduate students were assigned to one of three treatment groups. The first group received information stating that high scores on the Minnesota Teacher Attitude Inventory (MTAI) revealed a potentially successful teacher. The second group obtained neutral information. The third group was told that high scores on the MTAI resulted in potentially poor teachers. The results indicated that both positive and negative information increased the scores of subjects on the MTAI and suggested that the validity of the MTAI might be compromised.