Examinando por Autor "Sorrel, Miguel A."

Mostrando 1 - 5 de 5
  • Miniatura
    Publicación
    Exploring Approaches for Estimating Parameters in Cognitive Diagnosis Models with Small Sample Sizes
    (MDPI, 2023-04-27) Sorrel, Miguel A.; Escudero, Scarlett; Nájera, Pablo; Vázquez Lira, Ramsés; Schames Kreitchmann, Rodrigo
    Cognitive diagnostic models (CDMs) are increasingly being used in various assessment contexts to identify cognitive processes and provide tailored feedback. However, the most commonly used estimation method for CDMs, marginal maximum likelihood estimation with Expectation–Maximization (MMLE-EM), can present difficulties when sample sizes are small. This study compares the results of different estimation methods for CDMs under varying sample sizes using simulated and empirical data. The methods compared include MMLE-EM, Bayes modal, Markov chain Monte Carlo, a non-parametric method, and a parsimonious parametric model such as Restricted DINA. We varied the sample size, and assessed the bias in the estimation of item parameters, the precision in attribute classification, the bias in the reliability estimate, and computational cost. The findings suggest that alternative estimation methods are preferred over MMLE-EM under low sample-size conditions, whereas comparable results are obtained under large sample-size conditions. Practitioners should consider using alternative estimation methods when working with small samples to obtain more accurate estimates of CDM parameters. This study aims to maximize the potential of CDMs by providing guidance on the estimation of the parameters.
  • Miniatura
    Publicación
    FoCo: una aplicación Shiny para la evaluación formativa usando modelos de diagnóstico cognitivo
    (Colegio Oficial de la Psicología de Madrid, 2023-05-03) Sanz, Susana; Nájera, Pablo; Moreno, José David; Sorrel, Miguel A.; Schames Kreitchmann, Rodrigo; Martínez Huertas, José Ángel
    La combinación de evaluaciones formativas y sumativas podría mejorar la evaluación. El modelado de diagnóstico cognitivo (MDC) se ha propuesto para diagnosticar fortalezas y debilidades de estudiantes en la evaluación formativa. Sin embargo, ningún software permite implementarlo fácilmente. Así, se ha desarrollado FoCo (https://foco.shinyapps.io/FoCo/), permitiendo realizar análisis MDC y teoría clásica de tests. Se analizaron respuestas de 86 estudiantes de grado a un examen de métodos de investigación, diagnosticándose sus fortalezas y necesidades en cuanto a su dominio de los contenidos de la asignatura y las tres primeras competencias de la taxonomía de Bloom y se analizó la validez de los resultados. El análisis ha sido informativo, ya que para estudiantes con puntuaciones similares ha sido posible detectar diferentes fortalezas y debilidades. Además, se encontró que estos atributos predicen criterios relevantes. Se espera que FoCo facilite el uso de MDC en contextos educativos.
  • Miniatura
    Publicación
    Improving reliability estimation in cognitive diagnosis modeling
    (Springer, 2023-10-01) Torre, Jimmy de la; Sorrel, Miguel A.; Nájera, Pablo; Abad, Francisco; Schames Kreitchmann, Rodrigo
    Cognitive diagnosis models (CDMs) are used in educational, clinical, or personnel selection settings to classify respondents with respect to discrete attributes, identifying strengths and needs, and thus allowing to provide tailored training/treatment. As in any assessment, an accurate reliability estimation is crucial for valid score interpretations. In this sense, most CDM reliability indices are based on the posterior probabilities of the estimated attribute profiles. These posteriors are traditionally computed using point estimates for the model parameters as approximations to their populational values. If the uncertainty around these parameters is unaccounted for, the posteriors may be overly peaked, deriving into overestimated reliabilities. This article presents a multiple imputation (MI) procedure to integrate out the model parameters in the estimation of the posterior distributions, thus correcting the reliability estimation. A simulation study was conducted to compare the MI procedure with the traditional reliability estimation. Five factors were manipulated: the attribute structure, the CDM model (DINA and G-DINA), test length, sample size, and item quality. Additionally, an illustration using the Examination for the Certificate of Proficiency in English data was analyzed. The effect of sample size was studied by sampling subsets of subjects from the complete data. In both studies, the traditional reliability estimation systematically provided overestimated reliabilities, whereas the MI procedure offered more accurate results. Accordingly, practitioners in small educational or clinical settings should be aware that the reliability estimation using model parameter point estimates may be positively biased. R codes for the MI procedure are made available
  • Miniatura
    Publicación
    It Must have been Burnout: Prevalence and Related Factors among Spanish PhD Students
    (Cambridge University Press, 2023-07-23) Sorrel, Miguel A.; Arconada, María; Martínez Huertas, José Ángel
    Recent studies in different countries indicate that PhD students are more vulnerable to psychological disorders compared to the general population. No such data are available for the Spanish population. This study addresses this issue by studying prevalence rates and factors related to a common response to prolonged stress such as burnout syndrome. Burnout, emotional abilities, resilience, satisfaction with the dissertation advisor, and sociodemographic data were collected from 305 PhD students. The results indicated that the burnout rates are high in this group, especially for the emotional exhaustion dimension. Different linear regression models explained between 14% and 41% of the overall burnout scores variance and its dimensions. The psychological variables and the satisfaction with the dissertation advisor were the most relevant predictors. Consistent with what has been found in other countries, the evidence found indicates that the mental state of PhD students in Spain is alarming. The results of this study have important implications for the design and implementation of interventions to alleviate this problem.
  • Miniatura
    Publicación
    On bank assembly and block selection in multidimensional forced-choice adaptive assessments
    (SAGE, 2023-04-01) Sorrel, Miguel A.; Abad, Francisco; Schames Kreitchmann, Rodrigo::virtual::4386::600; Schames Kreitchmann, Rodrigo; Schames Kreitchmann, Rodrigo; Schames Kreitchmann, Rodrigo
    Multidimensional forced-choice (FC) questionnaires have been consistently found to reduce the effects of socially desirable responding and faking in non-cognitive assessments. Although FC has been considered problematic for providing ipsative scores under the classical test theory, IRT models enable the estimation of non-ipsative scores from FC responses. However, while some authors indicate that blocks composed of opposite-keyed items are necessary to retrieve normative scores, others suggest that these blocks may be less robust to faking, thus impairing the assessment validity. Accordingly, this article presents a simulation study to investigate whether it is possible to retrieve normative scores using only positively keyed items in pairwise FC computerized adaptive testing (CAT). Specifically, a simulation study addressed the effect of 1) different bank assembly (with a randomly assembled bank, an optimally assembled bank, and blocks assembled on-the-fly considering every possible pair of items), and 2) block selection rules (i.e., T, and Bayesian D and A-rules) over the estimate accuracy and ipsativity and overlap rates. Moreover, different questionnaire lengths (30 and 60) and trait structures (independent or positively correlated) were studied, and a non-adaptive questionnaire was included as baseline in each condition. In general, very good trait estimates were retrieved, despite using only positively keyed items. Although the best trait accuracy and lowest ipsativity were found using the Bayesian A-rule with questionnaires assembled on-the-fly, the T-rule under this method led to the worst results. This points out to the importance of considering both aspects when designing FC CAT.