Methodological quandaries in studying process and outcomes in peer assessment

Peer assessment is very various in its implementation. Six studies of peer assessment are reviewed, four of them in higher education. A literature review is followed by five empirical studies. Strengths and weaknesses of each study are considered and issues are raised. Variables in peer assessment needing further exploration are extricated – in sample definition, specification of type of peer assessment, organisational nature of the intervention, and the measures which are used to evaluate change. It is suggested that further experimental and quasi-experimental studies are necessary to contrast one or two of these variables at a time.     

RIM: A Random Item Mixture Model to Detect Differential Item Functioning

In this paper we present a new methodology for detecting differential item functioning (DIF). We introduce a DIF model, called the random item mixture (RIM), that is based on a Rasch model with random item difficulties (besides the common random person abilities). In addition, a mixture model is assumed for the item difficulties such that the items may belong to one of two classes: a DIF or a non-DIF class. The crucial difference between the DIF class and the non-DIF class is that the item difficulties in the DIF class may differ according to the observed person groups while they are equal across the person groups for the items from the non-DIF class. Statistical inference for the RIM is carried out in a Bayesian framework. The performance of the RIM is evaluated using a simulation study in which it is compared with traditional procedures, like the likelihood ratio test, the Mantel-Haenszel procedure and the standardized p -DIF procedure. In this comparison, the RIM performs better than the other methods. Finally, the usefulness of the model is also demonstrated on a real life data set.     

Scaling: An ITEMS Module

Scaling is the process of constructing a score scale that associates numbers or other ordered indicators with the performance of examinees. Scaling typically is conducted to aid users in interpreting test results. This module describes different types of raw scores and scale scores, illustrates how to incorporate various sources of information into a score scale, and introduces vertical scaling and its related designs and methodologies as a special type of scaling. After completion of this module, the reader should be able to understand the relationship between various types of raw scores, understand the relationship between raw scores and scale scores, construct a scale with desired properties, evaluate an existing score scale, understand how content and standards information are built into a scale, and understand how vertical scales are developed and used in practice.