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Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
Seaman, Michael A.; And Others – 1989
This Monte Carlo investigation provides some possible solutions to problems related to choosing multiple-comparison methods that maximize true rejections and minimize false ones. It has been argued that the traditional Bonferroni approach to multiple comparisons, which satisfies the statistician's family-wise Type I error concerns, could be…
Descriptors: Algorithms, Comparative Analysis, Error of Measurement, Monte Carlo Methods
Finch, Holmes; Huynh, Huynh – 2000
One set of approaches to the problem of clustering with dichotomous data in cluster analysis (CA) was studied. The techniques developed for clustering with binary data involve calculating distances between observations based on the variables and then applying one of the standard CA algorithms to these distances. One of the groups of distances that…
Descriptors: Algorithms, Cluster Analysis, Monte Carlo Methods, Responses
Donoghue, John R. – 1995
A Monte Carlo study compared the usefulness of six variable weighting methods for cluster analysis. Data were 100 bivariate observations from 2 subgroups, generated according to a finite normal mixture model. Subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. Of the clustering…
Descriptors: Algorithms, Cluster Analysis, Comparative Analysis, Correlation
Lau, C. Allen; Wang, Tianyou – 1999
A study was conducted to extend the sequential probability ratio testing (SPRT) procedure with the polytomous model under some practical constraints in computerized classification testing (CCT), such as methods to control item exposure rate, and to study the effects of other variables, including item information algorithms, test difficulties, item…
Descriptors: Algorithms, Computer Assisted Testing, Difficulty Level, Item Banks
Donoghue, John R. – 1994
Monte Carlo studies investigated effects of within-group covariance structure on subgroup recovery by several widely used hierarchical clustering methods. In Study 1, subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. All clustering methods were strongly affected by…
Descriptors: Algorithms, Analysis of Covariance, Cluster Analysis, Correlation
Nandakumar, Ratna – 1988
The effectiveness of Stout's procedure for assessing latent trait unidimensionality was studied. Strong empirical evidence of the utility of the statistical test in a variety of settings is provided. The procedure was modified to correct for increased bias, and a new algorithm to determine the size of assessment sub-tests was used. The following…
Descriptors: Algorithms, Latent Trait Theory, Monte Carlo Methods, Standardized Tests
Lau, C. Allen; Wang, Tianyou – 2000
This paper proposes a new Information-Time index as the basis for item selection in computerized classification testing (CCT) and investigates how this new item selection algorithm can help improve test efficiency for item pools with mixed item types. It also investigates how practical constraints such as item exposure rate control, test…
Descriptors: Algorithms, Classification, Computer Assisted Testing, Elementary Secondary Education
Chang, Shun-Wen; Twu, Bor-Yaun – 1998
This study investigated and compared the properties of five methods of item exposure control within the purview of estimating examinees' abilities in a computerized adaptive testing (CAT) context. Each of the exposure control algorithms was incorporated into the item selection procedure and the adaptive testing progressed based on the CAT design…
Descriptors: Adaptive Testing, Algorithms, Comparative Analysis, Computer Assisted Testing
Beasley, T. Mark; Leitner, Dennis W. – 1994
The use of stepwise regression has been criticized for both interpretive misunderstandings and statistical aberrations. A major statistical problem with stepwise regression and other procedures that involve multiple significance tests is the inflation of the Type I error rate. General approaches to control the family-wise error rate such as the…
Descriptors: Algorithms, Computer Simulation, Correlation, Error of Measurement