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Direct linkHacer Karamese – ProQuest LLC, 2022
Multistage adaptive testing (MST) has become popular in the testing industry because the research has shown that it combines the advantages of both linear tests and item-level computer adaptive testing (CAT). The previous research efforts primarily focused on MST design issues such as panel design, module length, test length, distribution of test…
Descriptors: Adaptive Testing, Scoring, Computer Assisted Testing, Design
Peer reviewedStark, Stephen; Chernyshenko, Oleksandr S. – International Journal of Testing, 2011
This article delves into a relatively unexplored area of measurement by focusing on adaptive testing with unidimensional pairwise preference items. The use of such tests is becoming more common in applied non-cognitive assessment because research suggests that this format may help to reduce certain types of rater error and response sets commonly…
Descriptors: Test Length, Simulation, Adaptive Testing, Item Analysis
Download full textGeorgiadou, Elissavet; Triantafillou, Evangelos; Economides, Anastasios A. – Journal of Technology, Learning, and Assessment, 2007
Since researchers acknowledged the several advantages of computerized adaptive testing (CAT) over traditional linear test administration, the issue of item exposure control has received increased attention. Due to CAT's underlying philosophy, particular items in the item pool may be presented too often and become overexposed, while other items are…
Descriptors: Adaptive Testing, Computer Assisted Testing, Scoring, Test Items
Li, Yuan H.; Schafer, William D. – Applied Psychological Measurement, 2005
Under a multidimensional item response theory (MIRT) computerized adaptive testing (CAT) testing scenario, a trait estimate (theta) in one dimension will provide clues for subsequently seeking a solution in other dimensions. This feature may enhance the efficiency of MIRT CAT's item selection and its scoring algorithms compared with its…
Descriptors: Adaptive Testing, Item Banks, Computation, Psychological Studies
Tatsuoka, Kikumi K. – 1982
This study introduced a probabilistic model utilizing item response theory (IRT) for dealing with a variety of misconceptions. The model can be used for evaluating the transition behavior of error types, advancement of learning stages, or the stability and persistence of particular misconceptions. Moreover, it apparently can be used for relating…
Descriptors: Adaptive Testing, Elementary Secondary Education, Error Patterns, Evaluation Methods
Rizavi, Saba; Way, Walter D.; Davey, Tim; Herbert, Erin – Educational Testing Service, 2004
Item parameter estimates vary for a variety of reasons, including estimation error, characteristics of the examinee samples, and context effects (e.g., item location effects, section location effects, etc.). Although we expect variation based on theory, there is reason to believe that observed variation in item parameter estimates exceeds what…
Descriptors: Adaptive Testing, Test Items, Computation, Context Effect
