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Harold Doran; Testsuhiro Yamada; Ted Diaz; Emre Gonulates; Vanessa Culver – Journal of Educational Measurement, 2025
Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Malik, Ali; Wu, Mike; Vasavada, Vrinda; Song, Jinpeng; Coots, Madison; Mitchell, John; Goodman, Noah; Piech, Chris – International Educational Data Mining Society, 2021
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until…
Descriptors: Grading, Accuracy, Computer Assisted Testing, Automation
Mikheeva, Ekaterina, Ed.; Meyer, Sebastian, Ed. – International Association for the Evaluation of Educational Achievement, 2020
IEA's International Computer and Information Literacy Study (ICILS) 2018 is designed to assess how well students are prepared for study, work, and life in a digital world. The study measures international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Assisted Testing
Fraillon, Julian; Ainley, John; Schulz, Wolfram; Duckworth, Daniel; Friedman, Tim – International Association for the Evaluation of Educational Achievement, 2019
The primary purpose of International Computer and Information Literacy Study (ICILS) 2018 is to assess systematically the capacities of students to use ICT productively for a range of different purposes, in ways that go beyond a basic use of ICT. ICILS 2018 includes authentic computer-based assessments that are administered to students in their…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Attitudes
Moothedath, Shana; Chaporkar, Prasanna; Belur, Madhu N. – Perspectives in Education, 2016
In recent years, the computerised adaptive test (CAT) has gained popularity over conventional exams in evaluating student capabilities with desired accuracy. However, the key limitation of CAT is that it requires a large pool of pre-calibrated questions. In the absence of such a pre-calibrated question bank, offline exams with uncalibrated…
Descriptors: Guessing (Tests), Computer Assisted Testing, Adaptive Testing, Maximum Likelihood Statistics
Thissen, David – Journal of Educational and Behavioral Statistics, 2016
David Thissen, a professor in the Department of Psychology and Neuroscience, Quantitative Program at the University of North Carolina, has consulted and served on technical advisory committees for assessment programs that use item response theory (IRT) over the past couple decades. He has come to the conclusion that there are usually two purposes…
Descriptors: Item Response Theory, Test Construction, Testing Problems, Student Evaluation
Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G. – Applied Psychological Measurement, 2013
Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…
Descriptors: Test Construction, Test Items, Item Banks, Automation
Magis, David; Raiche, Gilles – Applied Psychological Measurement, 2011
Computerized adaptive testing (CAT) is an active current research field in psychometrics and educational measurement. However, there is very little software available to handle such adaptive tasks. The R package "catR" was developed to perform adaptive testing with as much flexibility as possible, in an attempt to provide a developmental and…
Descriptors: Adaptive Testing, Measurement, Psychometrics, Computer Assisted Testing
Tendeiro, Jorge N.; Meijer, Rob R. – Applied Psychological Measurement, 2012
This article extends the work by Armstrong and Shi on CUmulative SUM (CUSUM) person-fit methodology. The authors present new theoretical considerations concerning the use of CUSUM person-fit statistics based on likelihood ratios for the purpose of detecting cheating and random guessing by individual test takers. According to the Neyman-Pearson…
Descriptors: Cheating, Individual Testing, Adaptive Testing, Statistics
Vidotto, G.; Massidda, D.; Noventa, S. – Psicologica: International Journal of Methodology and Experimental Psychology, 2010
The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982), can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto &…
Descriptors: Interaction, Computation, Computer Assisted Testing, Computer Software
Belov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander – Applied Psychological Measurement, 2008
This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…
Descriptors: Test Items, Monte Carlo Methods, Law Schools, Adaptive Testing

Zatz, Joel L. – American Journal of Pharmaceutical Education, 1982
A method for computer grading pharmaceutical calculations exams in which students convert their answers into scientific notation and enter their solutions onto a mark sense form is described. A table is generated and then posted listing student identification numbers, exam grades, and which problems were missed. (Author/MLW)
Descriptors: Computation, Computer Assisted Testing, Computer Programs, Grading

Schnorr, Janice M. – Teacher Education and Special Education, 1989
This article reviews briefly some of the research related to the development of automaticity for recall of basic math facts, reports on a research project with six fourth- and fifth-grade students, and gives teaching suggestions for the development of automaticity. (PB)
Descriptors: Addition, Computation, Computer Assisted Instruction, Computer Assisted Testing

Gerber, Michael M.; And Others – Exceptional Children, 1994
Design details, operation, and initial field test results are reported for DynaMath, a computer-based dynamic assessment system that provides individually tailored, instructionally useful assessment of students with disabilities. DynaMath organizes and outputs student performance data, graphically shows the "zone of proximal…
Descriptors: Computation, Computer Assisted Testing, Computer Software, Curriculum Based Assessment
Johnson, Joseph G.; Busemeyer, Jerome R. – Psychological Review, 2005
Preference orderings among a set of options may depend on the elicitation method (e.g., choice or pricing); these preference reversals challenge traditional decision theories. Previous attempts to explain these reversals have relied on allowing utility of the options to change across elicitation methods by changing the decision weights, the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Decision Making, Stimulation