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Carioti, Desiré; Stucchi, Natale Adolfo; Toneatto, Carlo; Masia, Marta Franca; Del Monte, Milena; Stefanelli, Silvia; Travellini, Simona; Marcelli, Antonella; Tettamanti, Marco; Vernice, Mirta; Guasti, Maria Teresa; Berlingeri, Manuela – Annals of Dyslexia, 2023
In this study, we validated the "ReadFree tool", a computerised battery of 12 visual and auditory tasks developed to identify poor readers also in minority-language children (MLC). We tested the task-specific discriminant power on 142 Italian-monolingual participants (8-13 years old) divided into monolingual poor readers (N = 37) and…
Descriptors: Language Minorities, Task Analysis, Italian, Monolingualism
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
Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
Nydick, Steven W. – Journal of Educational and Behavioral Statistics, 2014
The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has…
Descriptors: Probability, Item Response Theory, Models, Classification
Kobayashi, Yuichiro; Abe, Mariko – Journal of Pan-Pacific Association of Applied Linguistics, 2016
The purpose of the present study is to assess second language (L2) spoken English using automated scoring techniques. Automated scoring aims to classify a large set of learners' oral performance data into a small number of discrete oral proficiency levels. In automated scoring, objectively measurable features such as the frequencies of lexical and…
Descriptors: Second Language Learning, Computer Assisted Testing, Scoring, Automation
Hsu, Chia-Ling; Wang, Wen-Chung; Chen, Shu-Ying – Applied Psychological Measurement, 2013
Interest in developing computerized adaptive testing (CAT) under cognitive diagnosis models (CDMs) has increased recently. CAT algorithms that use a fixed-length termination rule frequently lead to different degrees of measurement precision for different examinees. Fixed precision, in which the examinees receive the same degree of measurement…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Diagnostic Tests
Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien – Applied Psychological Measurement, 2013
The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…
Descriptors: Computer Assisted Testing, Adaptive Testing, Models, Bayesian Statistics
Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling – Educational and Psychological Measurement, 2015
When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…
Descriptors: Test Items, Item Response Theory, Research Methodology, Decision Making
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
Gierl, Mark J.; Lai, Hollis – International Journal of Testing, 2012
Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…
Descriptors: Foreign Countries, Psychometrics, Test Construction, Test Items
Vaughn, Aaron J.; Hoza, Betsy – Journal of Emotional and Behavioral Disorders, 2013
The current study examined the incremental utility of rating scales, a structured diagnostic interview, and multiple informants in a comprehensive assessment of attention-deficit/hyperactivity disorder (ADHD). The sample included 185 children with ADHD (M[subscript age] = 9.22, SD = 0.95) and 82 children without ADHD (M[subscript age] = 9.24, SD =…
Descriptors: Attention Deficit Hyperactivity Disorder, Behavior Rating Scales, Clinical Diagnosis, Parent Attitudes
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
Rudner, Lawrence M.; Guo, Fanmin – Journal of Applied Testing Technology, 2011
This study investigates measurement decision theory (MDT) as an underlying model for computer adaptive testing when the goal is to classify examinees into one of a finite number of groups. The first analysis compares MDT with a popular item response theory model and finds little difference in terms of the percentage of correct classifications. The…
Descriptors: Adaptive Testing, Instructional Systems, Item Response Theory, Computer Assisted Testing
La Heij, Wido; Boelens, Harrie; Kuipers, Jan-Rouke – Language and Cognitive Processes, 2010
Cascade models of word production assume that during lexical access all activated concepts activate their names. In line with this view, it has been shown that naming an object's colour is facilitated when colour name and object name are phonologically related (e.g., "blue" and "blouse"). Prevor and Diamond's (2005) recent observation that…
Descriptors: Competition, Language Acquisition, Cognitive Processes, Models
Du, Chan – American Journal of Business Education, 2011
This paper examines whether a blended course that introduces lower-level education online learned by students before they come into class and after class online assignments and online discussions enhances student performance for an introductory principles of accounting course over the period 2009-2010. The blended course design includes (1)…
Descriptors: Accounting, Conventional Instruction, Blended Learning, Classification
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