A comparison between different ways to assess demands-abilities fit in higher education: Empirical results and recommendations for research practice.

Researchers studying person-environment fit can choose between various measurement approaches. Even though these measures are distinctly different, they often get used interchangeably, which makes interpreting the results of person-environment fit studies difficult. In the present article, we contrast the most commonly used measurement approaches for person-environment fit in higher education and compare them in terms of explained variance. We obtained data on the fit as well as subjective and objective study-related outcomes of N = 595 university students. We analyzed the fit between the demands of the study program and the abilities of the student, using the algebraic, squared and absolute difference score, response surface analysis (RSA), and direct fit as measurement approaches. Our results indicate that RSA explains the most variance for objective outcomes, and that direct fit explains the most variance for subjective outcomes. We hope that this contribution will help researchers distinguish the different measurement approaches of demands-abilities fit (and ultimately person-environment fit) and use them accordingly.

Assessing Distinctiveness in Multidimensional Instruments Without Access to Raw Data - A Manifest Fornell-Larcker Criterion.

The assessment of an instrument's conceptual framework as prerequisite for conducting further analyses has been advocated for decades. Multidimensional instruments posit several components that are each expected to be homogeneous but distinct from each other. However, validity evidence supporting the proposed internal structure is often missing. This leaves researchers and practitioners who are interested in a certain instrument in a precarious situation: Before starting their own data collection, they do not know whether dimensions adequately discriminate from each other and thus whether they can have confidence in any interpretation of these dimensions. Adapting the Fornell-Larcker criterion, we propose estimating distinctiveness between dimensions by using nothing but the most commonly reported statistics: Cronbach's alpha and the correlation matrix between the manifest composite scores of the dimensions in question. A simulation study demonstrates the usefulness of this "manifest Fornell-Larcker criterion" in providing an easily assessable method for vetting existing instruments, whereas a systematic literature review shows the necessity to do so even for instruments published in well-received journals.