Rater Errors among Peer-Assessors: Applying the Many-Facet Rasch Measurement Model

Many-Facet Rasch Measurement

This chapter provides an introductory overview of many-facet Rasch measurement (MFRM). Broadly speaking, MFRM refers to a class of measurement models that extend the basic Rasch model by incorporating more variables (or facets) than the two that are typically included in a test (i.e., examinees and items), such as raters, scoring criteria, and tasks. Throughout the chapter, a sample of rating d...

Introduction to Many-Facet Rasch Measurement - Preamble

Detecting and measuring rater effects using many-facet Rasch measurement: part I.

The purpose of this two-part paper is to introduce researchers to the many-facet Rasch measurement (MFRM) approach for detecting and measuring rater effects. The researcher will learn how to use the Facets (Linacre, 2001) computer program to study five effects: leniency/severity, central tendency, randomness, halo, and differential leniency/severity. Part 1 of the paper provides critical backgr...

Analysis of rater severity on written expression exam using Many Faceted Rasch Measurement

This paper describes how a Many Faceted Rasch Measurement (MFRM) approach can be applied to performance assessment focusing on rater analysis. The article provides an introduction to MFRM, a description of MFRM analysis procedures, and an example to illustrate how to examine the effects of various sources of variability on test takers’ performance on a writing test by means of a MFRM analysis. ...

A Many-facet Rasch Model to Detect Halo Effect in Three Types of Raters

Raters play a central role in rater-mediated assessment, and rater variability manifested in various forms including rater errors contributes to construct-irrelevant variance which can adversely affect an examinee’s test score. Halo effect as a subcomponent of rater errors is one of the most pervasive errors which, if not detected, can result in obscuring an examinee’s score and threatening val...

a many-facet rasch measurement of bias among farsi-native speaking raters toward essays written by non-native speakers of farsi

in this study, we investigated the errors native speakers of farsi commit when rating the esl essays, using a many-facet rasch measurement approach. to that end, two native speakers of farsi rated 56 essays which 28 male and female advanced language learners learning farsi as a second language at persian language centre at imam khomeini international university in qazvin, iran wrote on two topi...