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Tang, Xiaodan; Karabatsos, George; Chen, Haiqin – Applied Measurement in Education, 2020
In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…
Descriptors: Item Response Theory, Test Items, Models, Computation
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Lozano, José H.; Revuelta, Javier – Applied Measurement in Education, 2021
The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…
Descriptors: Bayesian Statistics, Computation, Learning, Testing
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Schweizer, Karl; Troche, Stefan – Educational and Psychological Measurement, 2018
In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of…
Descriptors: Investigations, Difficulty Level, Factor Analysis, Models
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Zhang, Zhidong – International Education Studies, 2018
This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…
Descriptors: Algebra, Bayesian Statistics, Scores, Mathematics Achievement
Ostrow, Korinn; Donnelly, Christopher; Adjei, Seth; Heffernan, Neil – Grantee Submission, 2015
Student modeling within intelligent tutoring systems is a task largely driven by binary models that predict student knowledge or next problem correctness (i.e., Knowledge Tracing (KT)). However, using a binary construct for student assessment often causes researchers to overlook the feedback innate to these platforms. The present study considers a…
Descriptors: Intelligent Tutoring Systems, Models, Difficulty Level, Scores
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van Lieshout, Ernest C. D. M.; Xenidou-Dervou, Iro – Educational Studies in Mathematics, 2018
At the start of mathematics education children are often presented with addition and subtraction problems in the form of pictures. They are asked to solve the problems by filling in corresponding number sentences. One type of problem concerns the representation of an increase or a decrease in a depicted amount. A decrease is, however, more…
Descriptors: Mathematics Instruction, Cognitive Processes, Difficulty Level, Addition
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Sunawan; Xiong, Junmei – Turkish Online Journal of Educational Technology - TOJET, 2017
The present study tested the influence of control belief, learning disorientation, and academic emotions on cognitive load in two types of concept-map structures within hypermedia learning environment. Four hundred and eighty-five students were randomly assigned to two groups: 245 students in the hierarchical group and 240 students in the…
Descriptors: Cognitive Processes, Difficulty Level, Beliefs, Psychological Patterns
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Schiffl, Iris – Universal Journal of Educational Research, 2016
Science standards have been a topic in educational research in Austria for about ten years now. Starting in 2005, competency structure models have been developed for junior and senior classes of different school types. After evaluating these models, prototypic tasks were created to point out the meaning of the models to teachers. At the moment,…
Descriptors: Science Education, Standards, Foreign Countries, Models
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El Masri, Yasmine H.; Ferrara, Steve; Foltz, Peter W.; Baird, Jo-Anne – Curriculum Journal, 2017
Predicting item difficulty is highly important in education for both teachers and item writers. Despite identifying a large number of explanatory variables, predicting item difficulty remains a challenge in educational assessment with empirical attempts rarely exceeding 25% of variance explained. This paper analyses 216 science items of key stage…
Descriptors: Predictor Variables, Test Items, Difficulty Level, Test Construction
Tang, Steven; Gogel, Hannah; McBride, Elizabeth; Pardos, Zachary A. – International Educational Data Mining Society, 2015
Online adaptive tutoring systems are increasingly being used in classrooms as a way to provide guided learning for students. Such tutors have the potential to provide tailored feedback based on specific student needs and misunderstandings. Bayesian knowledge tracing (BKT) is used to model student knowledge when knowledge is assumed to be changing…
Descriptors: Intelligent Tutoring Systems, Difficulty Level, Bayesian Statistics, Models
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Bejar, Isaac I.; Deane, Paul D.; Flor, Michael; Chen, Jing – ETS Research Report Series, 2017
The report is the first systematic evaluation of the sentence equivalence item type introduced by the "GRE"® revised General Test. We adopt a validity framework to guide our investigation based on Kane's approach to validation whereby a hierarchy of inferences that should be documented to support score meaning and interpretation is…
Descriptors: College Entrance Examinations, Graduate Study, Generalization, Inferences
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San Martin, Ernesto; Rolin, Jean-Marie; Castro, Luis M. – Psychometrika, 2013
In this paper, we study the identification of a particular case of the 3PL model, namely when the discrimination parameters are all constant and equal to 1. We term this model, 1PL-G model. The identification analysis is performed under three different specifications. The first specification considers the abilities as unknown parameters. It is…
Descriptors: Item Response Theory, Models, Identification, Statistical Analysis
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Goldhammer, Frank; Martens, Thomas; Lüdtke, Oliver – Large-scale Assessments in Education, 2017
Background: A potential problem of low-stakes large-scale assessments such as the Programme for the International Assessment of Adult Competencies (PIAAC) is low test-taking engagement. The present study pursued two goals in order to better understand conditioning factors of test-taking disengagement: First, a model-based approach was used to…
Descriptors: Student Evaluation, International Assessment, Adults, Competence
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Huang, Xiaoxia – Interactive Learning Environments, 2017
Previous research has indicated the disconnect between example-based research focusing on worked examples (WEs) and that focusing on modeling examples. The purpose of this study was to examine and compare the effect of four different types of examples from the two separate lines of research, including standard WEs, erroneous WEs, expert (masterly)…
Descriptors: Teaching Methods, Problem Solving, Academic Achievement, Cognitive Processes
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Moore, Jacob; Williams, Christopher B.; North, Christopher; Johri, Aditya; Paretti, Marie – Advances in Engineering Education, 2015
Traditional instructional materials such as textbooks contain significant educational content, but the navigational mechanisms to access that content are limited and, more importantly, not designed with learning in mind. To address this gap, we present the Adaptive Map, a novel organization and navigation tool designed to help students better…
Descriptors: Concept Mapping, Concept Formation, Comprehension, Expertise
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