02016nas a2200193   4500008004100000245009300041210006900134300001200203490000700215520136400222653001501586653002401601653001101625653002201636100001801658700001801676700001901694856010901713       2005                        eng d00aInfeasibility in automated test assembly models: A comparison study of different methods0 aInfeasibility in automated test assembly models A comparison stu  a223-2430 v423 aSeveral techniques exist to automatically put together a test meeting a number of specifications. In an item bank, the items are stored with their characteristics. A test is constructed by selecting a set of items that fulfills the specifications set by the test assembler. Test assembly problems are often formulated in terms of a model consisting of restrictions and an objective to be maximized or minimized. A problem arises when it is impossible to construct a test from the item pool that meets all specifications, that is, when the model is not feasible. Several methods exist to handle these infeasibility problems. In this article, test assembly models resulting from two practical testing programs were reconstructed to be infeasible. These models were analyzed using methods that forced a solution (Goal Programming, Multiple-Goal Programming, Greedy Heuristic), that analyzed the causes (Relaxed and Ordered Deletion Algorithm (RODA), Integer Randomized Deletion Algorithm (IRDA), Set Covering (SC), and Item Sampling), or that analyzed the causes and used this information to force a solution (Irreducible Infeasible Set-Solver). Specialized methods such as the IRDA and the Irreducible Infeasible Set-Solver performed best. Recommendations about the use of different methods are given. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAlgorithms10aItem Content (Test)10aModels10aTest Construction1 aHuitzing, H A1 aVeldkamp, B P1 aVerschoor, A J  uhttp://iacat.org/content/infeasibility-automated-test-assembly-models-comparison-study-different-methods00538nas a2200109   4500008004100000245012100041210006900162260004000231100001600271700001900287856012200306       2004                        eng d00aOptimal testing with easy items in computerized adaptive testing (Measurement and Research Department Report 2004-2)0 aOptimal testing with easy items in computerized adaptive testing  aArnhem, The Netherlands: Cito Group1 aEggen, Theo1 aVerschoor, A J  uhttp://iacat.org/content/optimal-testing-easy-items-computerized-adaptive-testing-measurement-and-research-department