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Shin, Jinnie; Gierl, Mark J. – International Journal of Testing, 2022
Over the last five years, tremendous strides have been made in advancing the AIG methodology required to produce items in diverse content areas. However, the one content area where enormous problems remain unsolved is language arts, generally, and reading comprehension, more specifically. While reading comprehension test items can be created using…
Descriptors: Reading Comprehension, Test Construction, Test Items, Natural Language Processing
Diao, Qi; van der Linden, Wim J. – Applied Psychological Measurement, 2013
Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using…
Descriptors: Automation, Test Construction, Test Format, Item Banks
van der Linden, Wim J.; Diao, Qi – Journal of Educational Measurement, 2011
In automated test assembly (ATA), the methodology of mixed-integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different…
Descriptors: Test Items, Test Format, Test Construction, Item Banks
Graf, Edith Aurora – ETS Research Report Series, 2008
Quantitative item models are item structures that may be expressed in terms of mathematical variables and constraints. An item model may be developed as a computer program from which large numbers of items are automatically generated. Item models can be used to produce large numbers of items for use in traditional, large-scale assessments. But…
Descriptors: Test Items, Models, Diagnostic Tests, Statistical Analysis
Martinez, Michael E.; And Others – 1990
Large-scale testing is dominated by the multiple-choice question format. Widespread use of the format is due, in part, to the ease with which multiple-choice items can be scored automatically. This paper examines automatic scoring procedures for an alternative item type: figural response. Figural response items call for the completion or…
Descriptors: Automation, Computer Assisted Testing, Educational Technology, Multiple Choice Tests
Peer reviewedMartinez, Michael E.; Bennett, Randy Elliot – Applied Measurement in Education, 1992
New developments in the use of automatically scorable constructed response item types for large-scale assessment are reviewed for five domains: (1) mathematical reasoning; (2) algebra problem solving; (3) computer science; (4) architecture; and (5) natural language. Ways in which these technologies are likely to shape testing are considered. (SLD)
Descriptors: Algebra, Architecture, Automation, Computer Science
Embretson, Susan E. – Measurement: Interdisciplinary Research and Perspectives, 2004
The last century was marked by dazzling changes in many areas, such as technology and communications. Predictions into the second century of testing are seemingly difficult in such a context. Yet, looking back to the turn of the last century, Kirkpatrick (1900), in his American Psychological Association presidential address, presented fundamental…
Descriptors: Ability, Testing, Futures (of Society), Psychometrics
Leuba, Richard J. – Engineering Education, 1986
Promotes the use of machine-scored tests in basic engineering science classes. Discusses some principles and practices of machine-scored testing. Provides several example test items. Argues that such tests can be used to enhance basic understanding of concepts and problem solving skills. (TW)
Descriptors: Automation, College Science, Engineering Education, Evaluation Methods

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