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Information value of multiple response questions [PDF]
Psihologija, 2012 Answers to Multiple Response (MR) questions carry more information than we usually utilize. Simple idea that all options of MR questions should be scored as independent test items has two major difficulties: 1) false options have item-response ...
Verbić Srđan
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Item Response Theory for Optimal Questionnaire Design
Je-LKS: Journal of E-Learning and Knowledge Society, 2013 Student assessment is one of the most critical aspects related to web-based learning systems. In this field, the use of on-line questionnaires - based on multiple-choice items - is one of the most widespread approaches.
Giuseppina Lotito, Giuseppe Pirlo
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An Extension of Testlet-Based Equating to the Polytomous Testlet Response Theory Model
Frontiers in Psychology, 2022 Educational assessments tests are often constructed using testlets because of the flexibility to test various aspects of the cognitive activities and broad content sampling.
Feifei Huang +5 more
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Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Incorporating Item Response Theory (IRT) into NLP tasks can provide valuable information about model performance and behavior. Traditionally, IRT models are learned using human response pattern (RP) data, presenting a significant bottleneck for large ...
John P. Lalor, Hao Wu, Hong Yu
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Clustering dichotomously scored items through functional k-means algorithm [PDF]
, 2016 In the educational field, it is common to analyze the probability of a correct response to a test item as a continuous function of the item parameters and the subject ability. This relation is given by the item response function.
Di Battista, Tonio; Dipartimento di Metodi Quantitativi e Teoria Economica, Università "G. d'Annunzio" Chieti-Pescara +1 more
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BMC Medical Research Methodology, 2022 Background Item response theory (IRT) methods for addressing differential item functioning (DIF) can detect group differences in responses to individual items (e.g., bias).
E. Nichols +13 more
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Item Response Models in Psychometrika and Psychometric Textbooks
Frontiers in Education, 2020 Item response theory modeling articles from 83 years of Psychometrika are sorted based on the taxonomy by Thissen and Steinberg (1986). Results from 377 research and review articles indicate that the usual unidimensional parametric item response theory ...
Seock-Ho Kim +12 more
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Extending item response theory to online homework
Physical Review Special Topics. Physics Education Research, 2014 Item response theory (IRT) becomes an increasingly important tool when analyzing “big data” gathered from online educational venues. However, the mechanism was originally developed in traditional exam settings, and several of its assumptions are ...
Gerd Kortemeyer
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Detecting Differential Item Functioning in 2PL Multistage Assessments
Psych, 2023 The detection of differential item functioning is crucial for the psychometric evaluation of multistage tests. This paper discusses five approaches presented in the literature: logistic regression, SIBTEST, analytical score-based tests, bootstrap score ...
Rudolf Debelak +3 more
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Item response theory in AI: Analysing machine learning classifiers at the instance level
Artificial Intelligence, 2019 AI systems are usually evaluated on a range of problem instances and compared to other AI systems that use different strategies. These instances are rarely independent.
Fernando Martínez-Plumed +3 more
semanticscholar +1 more source