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Showing 1 to 15 of 35 results Save | Export
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Ormerod, Christopher; Lottridge, Susan; Harris, Amy E.; Patel, Milan; van Wamelen, Paul; Kodeswaran, Balaji; Woolf, Sharon; Young, Mackenzie – International Journal of Artificial Intelligence in Education, 2023
We introduce a short answer scoring engine made up of an ensemble of deep neural networks and a Latent Semantic Analysis-based model to score short constructed responses for a large suite of questions from a national assessment program. We evaluate the performance of the engine and show that the engine achieves above-human-level performance on a…
Descriptors: Computer Assisted Testing, Scoring, Artificial Intelligence, Semantics
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Missaoui, Siwar; Maalel, Ahmed – Education and Information Technologies, 2021
A student's profile defines the best way a student chooses to learn. It comprises information on student's characteristics such as background knowledge, learning style preference, goals, personality etc. The foremost challenge that the students experience in learning system is that they are unable to bring back relevant information based on their…
Descriptors: Profiles, Models, Computer Games, Cognitive Style
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Hoogland, Kees; Tout, Dave – ZDM: The International Journal on Mathematics Education, 2018
In recent decades, technology has influenced various aspects of assessment in mathematics education: (1) supporting the assessment of higher-order thinking skills in mathematics, (2) representing authentic problems from the world around us to use and apply mathematical knowledge and skills, and (3) making the delivery of tests and the analysis of…
Descriptors: Computer Assisted Testing, At Risk Persons, Mathematics Education, Thinking Skills
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Lin, Chuan-Ju – Educational and Psychological Measurement, 2011
This study compares four item selection criteria for a two-category computerized classification testing: (1) Fisher information (FI), (2) Kullback-Leibler information (KLI), (3) weighted log-odds ratio (WLOR), and (4) mutual information (MI), with respect to the efficiency and accuracy of classification decision using the sequential probability…
Descriptors: Computer Assisted Testing, Adaptive Testing, Selection, Test Items
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Jiao, Hong; Liu, Junhui; Haynie, Kathleen; Woo, Ada; Gorham, Jerry – Educational and Psychological Measurement, 2012
This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test…
Descriptors: Test Items, Computer Assisted Testing, Measures (Individuals), Scoring
Barnett, Elisabeth A.; Reddy, Vikash – Center for the Analysis of Postsecondary Readiness, 2017
Many postsecondary institutions, and community colleges in particular, require that students demonstrate specified levels of literacy and numeracy before taking college-level courses. Typically, students have been assessed using two widely available tests--ACCUPLACER and Compass. However, placement testing practice is beginning to change for three…
Descriptors: Student Placement, College Entrance Examinations, Educational Practices, Computer Assisted Testing
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Laszlo, Sarah; Stites, Mallory; Federmeier, Kara D. – Language and Cognitive Processes, 2012
A growing body of evidence suggests that semantic access is obligatory. Several studies have demonstrated that brain activity associated with semantic processing, measured in the N400 component of the event-related brain potential (ERP), is elicited even by meaningless, orthographically illegal strings, suggesting that semantic access is not gated…
Descriptors: Semantics, Brain Hemisphere Functions, Diagnostic Tests, Language Processing
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Eggen, Theo J. H. M. – Educational Research and Evaluation, 2011
If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…
Descriptors: Test Length, Adaptive Testing, Classification, Item Analysis
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Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David – Language Testing, 2012
This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…
Descriptors: Scoring, Classification, Weighted Scores, Comparative Analysis
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Wang, Wen-Chung; Liu, Chen-Wei – Educational and Psychological Measurement, 2011
The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree-disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut…
Descriptors: Computer Assisted Testing, Adaptive Testing, Classification, Item Response Theory
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Thompson, Nathan A. – Practical Assessment, Research & Evaluation, 2011
Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Classification, Probability
Laborda, Jesus Garcia; Bakieva, Margarita; Gonzalez-Such, Jose; Pavon, Ana Sevilla – Online Submission, 2010
Since the Spanish Educational system is changing and promoting the use of online tests, it was necessary to study the transformation of test items in the "Spanish University Entrance Examination" (IB P.A.U.) to diminish the effect of test delivery changes (through its computerization) in order to affect the least the current model. The…
Descriptors: Foreign Countries, College Entrance Examinations, Computer Assisted Testing, Test Items
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Riley, Barth B.; Dennis, Michael L.; Conrad, Kendon J. – Applied Psychological Measurement, 2010
This simulation study sought to compare four different computerized adaptive testing (CAT) content-balancing procedures designed for use in a multidimensional assessment with respect to measurement precision, symptom severity classification, validity of clinical diagnostic recommendations, and sensitivity to atypical responding. The four…
Descriptors: Simulation, Computer Assisted Testing, Adaptive Testing, Comparative Analysis
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Thompson, Nathan A. – Educational and Psychological Measurement, 2009
Several alternatives for item selection algorithms based on item response theory in computerized classification testing (CCT) have been suggested, with no conclusive evidence on the substantial superiority of a single method. It is argued that the lack of sizable effect is because some of the methods actually assess items very similarly through…
Descriptors: Item Response Theory, Psychoeducational Methods, Cutting Scores, Simulation
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Finkelman, Matthew David – Applied Psychological Measurement, 2010
In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…
Descriptors: Mastery Tests, Computer Assisted Testing, Adaptive Testing, Test Length
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