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The perceived impact of mattering is quite accepted in higher education yet has not been well measured with diverse college students. This article describes the development and validation of the College Mattering Inventory with community college and university students. Results and implications for faculty and student affairs professionals are discussed.

A currently popular procedure in empirical factor analytic studies is to use unities in the main diagonal as communality estimates, extract all factors with eigenvalues of 1.0 or higher, and rotate these factors by varimax. This procedure and others are applied to several previously published correlation matrices and some artificial matrices. This procedure results in the retention of too many factors, unrealistic elevation of the amount of common factor variance analyzed, and distortions in the conclusions drawn from the factor analytic investigation. Ways of avoiding these difficulties, are discussed.

When the United States Congress passed the Individuals with Disabilities Education Improvement Act in 2004 (IDEIA 2004), local educational agencies (LEA) were permitted to use a Response-to-Intervention (RTI) approach for identifying children with possible learning disabilities for special education. Furthermore, IDEIA 2004 no longer required LEAs to establish an IQ-achievement discrepancy for determining a Specific Learning Disability (SLD). Although federal law no longer mandates the need for an IQachievement discrepancy for determining an SLD, most school psychologists continue to employ this approach for the assessment of children at-risk for SLD. Furthermore, some researchers suggest that although the IQ-achievement discrepancy model may not be the best approach for identifying children at-risk for SLD, school psychologists should continue to use intelligence tests as part of the assessment process. The current paper (a) provides a brief review of the IQ-achievement discrepancy model, (b) reviews concerns of using intelligence tests within a RTI framework, and (c) reviews some of the major criticisms regarding the IQ-achievement discrepancy model.

In choice behavior, researchers have noticed that humans have a preference for some probabilities, Most researchers in the past 40 yr. have been unable to account for the nonlinearity of this behavior. The convex shape of nonlinear subjective probabilities has been experimentally confirmed by every investigator from Preston and Baratta through Edwards, Handa, and Kahneman and Tversky. What has been lacking is a clear analysis of why the probabilities have a convex shape. Here, it is argued that Keynes provided a logical explanation and a mathematical formula for this phenomenon in 1921. Had researchers not overlooked this important work, the body of knowledge on choice behavior might be more advanced.