Investigating psychometric properties and dimensional structure of an educational environment measure (DREEM) using Mokken scale analysis – a pragmatic approach

BMC Medical Education

Ulf Brodin¹  Terese Stenfors¹  Per J Palmgren¹  Gunnar H Nilsson²  Roger Watson³ 

[1] Department of Learning, Informatics, Management and Ethics, Karolinska Institutet;Department of Neurobiology, Care Sciences and Society, Karolinska Institutet;Faculty of Health & Sciences, University of Hull;

关键词: Dundee ready educational environment measure;    Education;    Educational measurement;    Item response theory;    Mokken scaling;    Psychometrics;   

DOI  :  10.1186/s12909-018-1334-8

来源: DOAJ

【 摘 要 】

Abstract Background Questionnaires and surveys are used throughout medical education. Nevertheless, measuring psychological attributes such as perceptions of a phenomenon among individuals may be difficult. The aim of this paper is to introduce the basic principles of Mokken scale analysis (MSA) as a method for the analysis of questionnaire data and to empirically apply MSA to a real-data example. Methods MSA provides a set of statistical tools for exploring the relationship between items and latent traits. MSA is a scaling method of item selection algorithms used to partition an array of items into scales. It employs various methods to probe the assumptions of two nonparametric item response theory models: the monotone homogeneity model and the double monotonicity model. The background and theoretical framework underlying MSA are outlined in the paper. MSA for polytomous items was applied to a real-life data example of 222 undergraduate students who had completed a 50-item self-administered inventory measuring the educational environment, the Dundee Ready Educational Measure (DREEM). Results A pragmatic and parsimonious approach to exploring questionnaires and surveys from an item response theory (IRT) perspective is outlined. The use of MSA to explore the psychometric properties of the Swedish version of the DREEM failed to yield strong support for the scalability and dimensional structure of the instrument. Conclusions MSA, a class of simple nonparametric IRT models – for which estimates can be easily obtained and whose fit to data is relatively easily investigated – was introduced, presented, and tested. Our real-data example suggests that the psychometric properties of DREEM are not adequately supported. Thus, the empirical application depicted a potential and feasible approach whereby MSA could be used as a valuable method for exploring the behavior of scaled items in response to varying levels of a latent trait in medical education research.

【 授权许可】

Unknown