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Copyright of Avances en PsicologÍa Latinoamericana is the property of Colegio Mayor de Nuestra Senora del Rosario and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Scientifically based research used to inform evidence based school reform efforts has been required by the federal government in order to receive grant funding since the reenactment of No Child Left Behind (2002). Educational evaluators are thus faced with the challenge to use rigorous research designs to establish causal relationships. However, access to student-level longitudinal or comparison group data is often scarce, which significantly restricts researchers' choice of research design. Although most state departments of education have school- and district-level data available to the public, the individual student-level data that are often needed to perform appropriate statistical analyses are unavailable. This exploratory study demonstrates the process of and provides evidence that microanalytical simulation methods, conducted using Microsoft Excel, may be a useful research tool in the field of education if adequate school-level modeling information is available. These simulation methods may assist in providing greater opportunities to execute more rigorous methodological designs. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: We set out to (1) develop a learner-centered approach to pharmacotherapeutics textbook evaluation and selection and (2) describe potential differences among students and instructors in their textbook selection preferences. Design: Pharmacy practice faculty created the Textbook Evaluation and Selection Tool (TEST) to evaluate pharmacotherapeutics textbooks. Evaluator subgroups were PharmD students (third-year, fourth-year, and teaching assistants) and instructors (residents and clinical faculty). Although each evaluator used the same therapeutic topic for all four textbooks, the range of evaluators reviewed a variety of disease state topics. The Many-Facet Rasch Model (MFRM) was used to transform evaluation responses into measures of textbook preference. Results: Thirty-two participants completed 241 TEST evaluations. Regarding construct validity, the TEST rating scale functioned well, while textbooks and items clearly fit the unidimensional model. The TEST separation was 4.91, with a measurement error of 0.07 for the textbooks. The TEST reliability was 0.96. Textbook preferences varied among subgroups of students and instructors. Because the number of participants/evaluations varied among subgroups, a consensus was achieved by summating subgroup preference measures from the MFRM. Conclusion: This study fostered textbook evaluation and included student, resident, and faculty input. Using the TEST measure, differences were observed among evaluator subgroups. This inclusive decision-making design provided feedback in our pharmacotherapeutics textbook selection process. [Copyright &y& Elsevier]

This paper revisits a half-century long theoretical controversy associated with the use of magnitude estimation scaling (MES) and category rating scaling (CRS) procedures in measurement. The MES procedure in this study involved instructing participants to write a number that matched their impression of difficulty of a test item. Participants were not restricted in the range of numbers they could choose for their scale. They also had the choice of disclosing their individual scale. After the MES task was completed, participants were given a blank copy of the test to rate the perceived difficulty of each item using a researcher-imposed categorical rating scale from 1 (very easy) to 6 (very difficult). The MES and CRS data were both analyzed using Rasch Rating scale model. Additionally, the MES data were examined with Rasch Partial Credit model. Results indicate that knowing each person's scale is associated with smaller errors of measurement. [ABSTRACT FROM AUTHOR]