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Grant, Lyle K.; Courtoreille, Marni – Psychological Record, 2007
This study is a comparison of 2 versions of an Internet-based tutorial that teaches the behavior-analysis concept of positive reinforcement. A fixed-item group of students studied a version of the tutorial that included 14 interactive examples and nonexamples of the concept. A response-sensitive group of students studied a different version of the…
Descriptors: Control Groups, Positive Reinforcement, Web Based Instruction, Comparative Analysis
Hol, A. Michiel; Vorst, Harrie C. M.; Mellenbergh, Gideon J. – Applied Psychological Measurement, 2007
In a randomized experiment (n = 515), a computerized and a computerized adaptive test (CAT) are compared. The item pool consists of 24 polytomous motivation items. Although items are carefully selected, calibration data show that Samejima's graded response model did not fit the data optimally. A simulation study is done to assess possible…
Descriptors: Student Motivation, Simulation, Adaptive Testing, Computer Assisted Testing
ERIC Clearinghouse on Tests, Measurement, and Evaluation, Princeton, NJ. – 1983
This brief overview notes that an adaptive test differs from standardized achievement tests in that it does not consist of a certain set of items that are administered to a group of examinees. Instead, the test is individualized for each examinee. The items administered to the examinee are selected from a large pool of items on the basis of the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Latent Trait Theory
Anderson, Richard Ivan – 1980
Features of a probabilistic testing system that has been implemented on the "cerl" PLATO computer system are described. The key feature of the system is the manner in which an examinee responds to each test item; the examinee distributes probabilities among the alternatives of each item by positioning a small square on or within an…
Descriptors: Computer Assisted Testing, Data Collection, Feedback, Probability
Leung, Chi-Keung; Chang, Hua-Hua; Hau, Kit-Tai – 2001
The multistage alpha-stratified computerized adaptive testing (CAT) design advocated a new philosophy of pool management and item selection using low discriminating items first. It has been demonstrated through simulation studies to be effective both in reducing item overlap rate and enhancing pool utilization with certain pool types. Based on…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – 2003
This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has been administered. Predictions from the model are…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Linear Programming
van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R. – 2000
Item scores that do not fit an assumed item response theory model may cause the latent trait value to be estimated inaccurately. For computerized adaptive tests (CAT) with dichotomous items, several person-fit statistics for detecting nonfitting item score patterns have been proposed. Both for paper-and-pencil (P&P) test and CATs, detection of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Goodness of Fit, Item Response Theory
Zhu, Daming; Fan, Meichu – 1999
The convention for selecting starting points (that is, initial items) on a computerized adaptive test (CAT) is to choose as starting points items of medium difficulty for all examinees. Selecting a starting point based on prior information about an individual's ability was first suggested many years ago, but has been believed unimportant provided…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level
Peer reviewedPotenza, Maria T.; Stocking, Martha L. – Journal of Educational Measurement, 1997
Common strategies for dealing with flawed items in conventional testing, grounded in principles of fairness to examinees, are re-examined in the context of adaptive testing. The additional strategy of retesting from a pool cleansed of flawed items is found, through a Monte Carlo study, to bring about no practical improvement. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Monte Carlo Methods
Peer reviewedKingsbury, G. Gage; Zara, Anthony R. – Applied Measurement in Education, 1991
This simulation investigated two procedures that reduce differences between paper-and-pencil testing and computerized adaptive testing (CAT) by making CAT content sensitive. Results indicate that the price in terms of additional test items of using constrained CAT for content balancing is much smaller than that of using testlets. (SLD)
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Computer Simulation
Peer reviewedO'Neill, Thomas; Lunz, Mary E.; Thiede, Keith – Journal of Applied Measurement, 2000
Studied item exposure in a computerized adaptive test when the item selection algorithm presents examinees with questions they were asked in a previous test administration. Results with 178 repeat examinees on a medical technologists' test indicate that the combined use of an adaptive algorithm to select items and latent trait theory to estimate…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Response Theory
Peer reviewedBennett, Randy Elliot; Morley, Mary; Quardt, Dennis – Applied Psychological Measurement, 2000
Describes three open-ended response types that could broaden the conception of mathematical problem solving used in computerized admissions tests: (1) mathematical expression (ME); (2) generating examples (GE); and (3) and graphical modeling (GM). Illustrates how combining ME, GE, and GM can form extended constructed response problems. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Constructed Response, Mathematics Tests
Peer reviewedvan der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – Applied Psychological Measurement, 1999
Proposes an item-selection algorithm for neutralizing the differential effects of time limits on computerized adaptive test scores. Uses a statistical model for distributions of examinees' response times on items in a bank that is updated each time an item is administered. Demonstrates the method using an item bank from the Armed Services…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Peer reviewedStocking, Martha L. – Applied Psychological Measurement, 1997
Investigated three models that permit restricted examinee control over revising previous answers in the context of adaptive testing, using simulation. Two models permitting item revisions worked well in preserving test fairness and accuracy, and one model may preserve some cognitive processing styles developed by examinees for a linear testing…
Descriptors: Adaptive Testing, Cognitive Processes, Comparative Analysis, Computer Assisted Testing
Sawaki, Yasuyo; Stricker, Lawrence; Oranje, Andreas – ETS Research Report Series, 2008
The present study investigated the factor structure of a field trial sample of the Test of English as a Foreign Language™ Internet-based test (TOEFL® iBT). An item-level confirmatory factor analysis (CFA) was conducted for a polychoric correlation matrix of items on a test form completed by 2,720 participants in the 2003-2004 TOEFL iBT Field…
Descriptors: Factor Structure, Computer Assisted Testing, Multitrait Multimethod Techniques, Scores

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