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Abstract :
[en] Computerized Adaptive Testing (CAT) has greatly improved the accuracy and
efficiency of psychological testing for decades. Multistage Testing (MST) has
received much of attention recently. MST is similar to CAT such that it allows
the adaptation of the difficulty of the test to the level of ability of a test
taker. Specifically, in MST, items are interactively selected for each test
taker, but rather than selecting individual items, groups of items are selected
and the test is built in stages. Over the last decade, researchers have
investigated ways for an MST to incorporate most of the advantages from CAT and
linear testing, while minimize their disadvantages. These features include
testing efficiency and accuracy, greater control of test content, more robust
item review, as well as simplified test assembly and administration. Therefore,
MST can be an effective compromise between CAT and linear testing, embedding
features and benefits from both designs. Thus, MST becomes of more and more
interest to researchers and practitioners as technology advances.
This presentation will first provide a general overview of a multistage test
(MST) design and its important concepts and processes. It will then present the
latest development on CAT and MST using R, the mstR package. The presentation
will also illustrate how to simulate MST administrations using mstR package,
and discuss some practical issues and considerations for MST from design to
applications.