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Author: Ragip Terzi
Publisher:
ISBN:
Category : Cognition
Languages : en
Pages : 91
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Book Description
Author: Ragip Terzi
Publisher:
ISBN:
Category : Cognition
Languages : en
Pages : 91
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Book Description
Author: Ruchi Jain Sachdeva
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The analysis of the fraction subtraction dataset found 15% of the q-entries had enough evidence to reject the Null hypothesis. This clearly indicates that the test finds misfit in the original expert designed Q-matrix.
Author: Lokman Akbay
Publisher:
ISBN:
Category :
Languages : en
Pages : 115
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Book Description
Many cognitive diagnosis model (CDM) examples assume independent cognitive skills; however, cognitive skills need not be investigated in isolation (Kuhn, 2011; Tatsuoka, 1995). Kuhn (2001) argues that some preliminary knowledge can be the foundation for more sophisticated knowledge or skills. When this type of hierarchical relationships among the attributes are not taken into account, estimation results of the conventional CDMs may be biased or less accurate. Hence, this dissertation investigates the change in the degree of accuracy and precision in the item parameter estimates and correct attribute classification rates of different estimation approaches based on modi cation of either the Q-matrix or prior distribution. Modi fication of the prior distribution and the Q-matrix depend on the assumed hierarchical structure, as such, identifying the correct hierarchical structure is of the essence. To address the subjectivity in the conventional methods for attribute structure identification (i.e., expert opinions via content analysis and verbal data analyses such as interviews and think-aloud protocols), this dissertation proposes a likelihood-ratio test based exhaustive empirical search for identifying hierarchical structures. It further suggests a likelihood-approach for selection of the most accurate hierarchical structure when multiple candidates are present. Furthermore, implementation of the CDMs requires construction of a Q-matrix to indicate the associations between test items and attributes required for successful completion of the items (de la Torre, 2008; Chiu, 2013). Q-matrix construction heavily depends on content expert opinions, as such this subjective process may result in misspecifications in the Q-matrix. Up to date, several parametric and nonparametric Q-matrix validation methods have been proposed to address the misspeci fications that may emerge due to fallible judgments of experts in Q-matrix construction (Chiu, 2013). Yet, although they have been examined under various conditions, none of these methods was tested under hierarchical attribute structures. Therefore, this dissertation further investigates the reciprocal impact of misspeci fied Q-matrix and hierarchical structure on hierarchy identification and Q-matrix validation. The results showed that structured prior distribution led to the most accurate and precise item parameter estimation, and highest correct examinee classification. When an unstructured prior was employed, impact of structured Q-matrix was different for compensatory and noncompensatory CDMs. Furthermore, study results showed that likelihood-based exhaustive search was promising in identification/validation of hierarchical attribute structure. Lastly, results indicated that performance of Q-matrix validation methods might not be as high when they are used as is under hierarchical attribute structures.
Author: Kikumi K. Tatsuoka
Publisher: Routledge
ISBN: 1135681325
Category : Education
Languages : en
Pages : 369
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Book Description
This book introduces a new methodology for the analysis of test results. Free from ambiguous interpretations, the results truly demonstrate an individual’s progress. The methodology is ideal for highlighting patterns derived from test scores used in evaluating progress. Dr. Tatsuoka introduces readers to the Rule Space Method (RSM), a technique that transforms unobservable knowledge and skill variables into observable and measurable attributes. RSM converts item response patterns into attribute mastery probabilities. RSM is the only up-to-date methodology that can handle large scale assessment for tests such as the SAT and PSAT. PSAT used the results from this methodology to create cognitively diagnostic scoring reports. In this capacity, RSM helps teachers understand what scores mean by helping them ascertain an individual’s cognitive strengths and weaknesses. For example, two students may have the exact same score, but for different reasons. One student might excel at processing grammatically complex texts but miss the main idea of the prose, while another excels at understanding the global message. Such knowledge helps teachers customize a student’s education to his or her cognitive abilities. RSM is also used for medical diagnoses, genetics research, and to help classify music into various states of emotions for treating mental problems. The book opens with an overview of cognitive assessment research and nonparametric and parametric person-fit statistics. The Q-matrix theory is then introduced followed by the Rule Space method. Various properties of attribute mastery probabilities are then introduced along with the reliability theory of attributes and its connection to classical and item response theory. The book concludes with a discussion of how the construct validity of a test can be clarified with the Rule Space method. Intended for researchers and graduate students in quantitative, educational, and cognitive psychology, this book also appeals to those in computer science, neuroscience, medicine, and mathematics. The book is appropriate for advanced courses on cognometrics, latent class structures, and advanced psychometrics as well as statistical pattern recognition and classification courses taught in statistics and/or math departments.
Author: F. Gregory Ashby
Publisher: Cambridge University Press
ISBN: 1108905099
Category : Psychology
Languages : en
Pages : 575
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Book Description
The field of mathematical psychology began in the 1950s and includes both psychological theorizing, in which mathematics plays a key role, and applied mathematics motivated by substantive problems in psychology. Central to its success was the publication of the first Handbook of Mathematical Psychology in the 1960s. The psychological sciences have since expanded to include new areas of research, and significant advances have been made both in traditional psychological domains and in the applications of the computational sciences to psychology. Upholding the rigor of the original Handbook, the New Handbook of Mathematical Psychology reflects the current state of the field by exploring the mathematical and computational foundations of new developments over the last half-century. The third volume provides up-to-date, foundational chapters on early vision, psychophysics and scaling, multisensory integration, learning and memory, cognitive control, approximate Bayesian computation, and encoding models in neuroimaging.
Author: Nathan Daniel Minchen
Publisher:
ISBN:
Category :
Languages : en
Pages : 120
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Book Description
At present, many cognitive diagnosis models (CDMs) have been developed for dichotomous response, several of which have been extended to handle polytomous response. CDMs to handle continuous response, however, have not been extensively explored beyond the recently proposed continuous deterministic inputs, noisy ``and" gate (C-DINA) model and its generalized version. The studies that comprise this dissertation aim to extend model development in the context of continuous response and to address several key issues that arise from its use in CDM. In the first study, a hierarchical framework is employed for using response time to improve examinee ability estimation and classification accuracy. Under this framework, response time and response accuracy are construed as arising from separate continuous, possibly correlated, unidimensional latent variables. A higher-order attribute specification is used to link the general ability to the probability of mastering certain attributes. Results show that both examinee classifications and higher-order ability estimation can be improved by using response time. A real data example is included to demonstrate the viability of the method. In the second study, a new item selection algorithm is presented for computerized adaptive testing applications that use continuous response CDMs. The algorithm uses the Jensen-Shannon divergence, which quantifies the total degree of dissimilarity in a set of two or more probability distributions, as an item selection algorithm. Results demonstrate that the method typically outperforms random item administration with respect to both classification accuracy and test efficiency. A real data example shows that an existing test could be shortened considerably while still producing a high level of classification agreement with the original. In the final study, a new Q-matrix validation procedure is proposed for continuous response CDMs. The method presented is designed to work with a generalized continuous response model, and is based on a weighted least squares regression. The simulation study shows that the method performs increasingly well as item quality increases. The method was also applied to an existing dataset, with results confirming most of the entries in the existing Q-matrix.
Author: Paul De Bièvre
Publisher: Springer Science & Business Media
ISBN: 3540270345
Category : Science
Languages : en
Pages : 176
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Book Description
The validation of analytical methods is based on the characterisation of a measurement procedure (selectivity, sensitivity, repeatability, reproducibility). This volume collects 31 outstanding papers on the topic, mostly published in the period 2000-2003 in the journal "Accreditation and Quality Assurance." They provide the latest understanding, and possibly the rationale why it is important to integrate the concept of validation into the standard procedures of every analytical laboratory. In addition, this anthology considers the benefits to both: the analytical laboratory and the user of the measurement results.
Author: Marie Wiberg
Publisher: Springer Nature
ISBN: 3031045726
Category : Mathematics
Languages : en
Pages : 329
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Book Description
The volume represents presentations given at the 86th annual meeting of the Psychometric Society, held virtually on July 19–23, 2021. About 500 individuals contributed paper presentations, symposiums, poster presentations, pre-conference workshops, keynote presentations, and invited presentations. Since the 77th meeting, Springer has published the conference proceedings volume from this annual meeting to allow presenters to share their work and ideas with the wider research community, while still undergoing a thorough review process. This proceedings covers a diverse set of psychometric topics, including item response theory, Bayesian models, reliability, longitudinal measures, and cognitive diagnostic models.
Author: Wenchao Ma
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
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Book Description
Cognitive diagnosis models (CDMs) have received increasing attention in recent years. The goal of CDMs is to classify examinees into different latent classes with unique attribute patterns indicating mastery or nonmastery on a set of skills or attributes of interest. Although a large number of CDMs can be found in the literature, most of them are developed for dichotomous response data. This dissertation proposes a general cognitive diagnosis model for a special type of polytomously scored items, where item categories are attained in a sequential manner, and explicitly associated with some attributes. The conditional probability of answering a category correctly given that the previous categories have been performed successfully is defined as emph{processing function}, and modeled using the generalized deterministic inputs, noisy ``and'' gate (G-DINA; de la Torre, 2011) model. The resulting model is referred to as the emph{sequential} G-DINA model. To relate response categories to attributes, a category-level Q-matrix is used. When the attribute and category association is specified a priori, the proposed model has the flexibility to allow different cognitive processes (e.g., conjunctive, disjunctive) to be modeled at different steps within a single item. This model can be extended for items, where categories cannot be explicitly linked to attributes, and for items with unordered categories. Item parameters of the proposed model are estimated using the marginal maximum likelihood estimation via expectation-maximization algorithm. Like the traditional Q-matrix, the category-level Q-matrix is most likely to be developed by experts, and thus tends to be subjective. In this dissertation, a Q-matrix validation procedure is developed for the sequential G-DINA model to empirically identify and correct misspecifications in the category-level Q-matrix. This validation method is implemented in a stepwise manner based on the Wald test and an item discrimination index. Simulation studies are conducted to evaluate the performance of the proposed procedure in terms of the true positive and false positive rates. A condensation rule is an important component for most CDMs, including the sequential G-DINA model, in that it specifies how the latent attributes are employed simultaneously to make a manifest item response. Although the G-DINA model has been used as the processing function, it is important to empirically determine whether the G-DINA model can be further constrained according to the cognitive processes involved in each step. In this dissertation, the performance of the Wald test and the likelihood ratio test are examined in determining the appropriate condensation rule for each step. More specifically, a simulation study is used to evaluate the Type I error and power of these hypothesis tests concerning whether the DINA model, DINO model, and extit{A}-CDM can be used in place of the G-DINA model as the processing function for the steps that involved more than one attribute. Taken together, this dissertation develops a set of psychometric tools including statistical models and procedures for graded response data. These tools can facilitate the use of constructed-response items, which are typically scored polytomously, in cognitively diagnostic assessments. The performance of the proposed models and procedures are examined using both Monte Carlo simulation studies and real data.
Author: Jack P.C. Kleijnen
Publisher: Springer Science & Business Media
ISBN: 0387718133
Category : Mathematics
Languages : en
Pages : 229
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Book Description
Simulation is a widely used methodology in all Applied Science disciplines. This textbook focuses on this crucial phase in the overall process of applying simulation, and includes the best of both classic and modern methods of simulation experimentation. This book will be the standard reference book on the topic for both researchers and sophisticated practitioners, and it will be used as a textbook in courses or seminars focusing on this topic.
