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In the learning process, students must be able to regulate themselves. This is an effort to improve the quality of student learning, especially their learning achievement. The purpose of this study is to empirically analyze the characteristics of self-regulation skills in learning mathematics. The analysis was carried out by utilizing Item Response Theory (IRT) with a Partial Credit Model (PCM). This study is a descriptive quantitative study with the subjects of the study being 123 students of grade 10 of Senior High Schools in Yogyakarta. Data collection was carried out using a questionnaire that had been developed and its item characteristics were analyzed using IRT. The independent learning scale questionnaire in mathematics consists of 16 statement items and measures 5 aspects. Based on all the questions that are feasible to be analyzed using the PCM model, it is known that there are 5 aspects that fit, namely (1) self-confidence, (2) discipline in learning, (3) active in learning, (4) responsibility, and (5) motivation in learning. This instrument can be used to measure students' self-regulation skills in learning mathematics based on their ability level.

Models are valuable tools for learning science, however, their utility would be restricted if students do not consider the nature of models, their purpose, and their implementation in the learning process. The focus of this research was to find out about the type of model and meta-modeling knowledge of second cycle high school students on physics, chemistry, and biology courses. The research sample consisted of 530 second cycle high school students who were selected through convenience sampling method to answer the modeling knowledge questionnaire. Partial credit question-answer model was used to analyze the data. Findings showed that students think primarily about objective and functional models, and abstract models (diagram or equation) are of secondary importance. Modeling knowledge and awareness of the function and objectives of models are not independent from the content area, and the type and application of models depend on the content and the course, in such a way that students use modeling in biology more to describe phenomena and in physics and chemistry for prediction and reasoning. It is suggested that in the science curriculum more attention should be paid to the model and modeling knowledge in the course's content, and the students' metacognitive skills should be developed to identify, apply, revise, and evaluate models. Science teachers should also be encouraged to consciously use modeling in the teaching process.

Test-taking strategies are discussed in the literature as an important factor affecting test scores, and are recommended to be taken into consideration regarding the validity of tests. Although studies have been conducted for more than a quarter of a century, no agreement has yet been reached as to the dimensions of test-taking strategies. The aim of this study is to develop a valid and reliable test-taking strategies scale for undergraduate and high school students who experience intensive exam periods. In the scale prepared for this purpose, we consider tests containing different item types and focus on pre-test, during-test and post-test strategies, excluding test-preparation. Two separate forms of test-taking strategies at high school (27 items) and undergraduate levels (18 items) were developed using promising measurement theories and models. Results indicated that the Person Separation Index, as a reliability index, was calculated as .88 for the high-school form and .93 for the undergraduate form. This study is significant in presenting valid and reliable tools for measuring test-taking strategies, and is considered an exemplary research that uses Partial Credit Model for Likert-type scale development.

Abstract Background Food literacy is theorised to improve diet quality, nutrition behaviours, social connectedness and food security. The definition and conceptualisation by Vidgen & Gallegos, consisting of 11 theoretical components within the four domains of planning and managing, selecting, preparing and eating, is currently the most highly cited framework. However, a valid and reliable questionnaire is needed to comprehensively measure this conceptualisation. Therefore, this study draws on existing item pools to develop a comprehensive food literacy questionnaire using item response theory. Methods Five hundred Australian adults were recruited in Study 1 to refine a food literacy item pool using principal component analysis (PCA) and item response theory (IRT) which involved detailed item analysis on targeting, responsiveness, validity and reliability. Another 500 participants were recruited in Study 2 to replicate item analysis on validity and reliability on the refined item pool, and 250 of these participants re-completed the food literacy questionnaire to determine its test–retest reliability. Results The PCA saw the 171-item pool reduced to 100-items across 19 statistical components of food literacy. After the thresholds of 26 items were combined, responses to the food literacy questionnaire had ordered thresholds (targeting), acceptable item locations ( 0.99) and test–retest (ICC 2,1 0.55–0.88) scores (reliability). Conclusions We developed a 100-item food literacy questionnaire, the IFLQ-19 to comprehensively address the Vidgen & Gallegos theoretical domains and components with good targeting, responsiveness, reliability and validity in a diverse sample of Australian adults.

Background: The Schizophrenia Coping Oral Health Profile and Index (SCOOHPI) scale studies the coping strategies of schizophrenic patients with regard to oral health. The structural validity of this scale is studied has been studied using factor analyses. In this article, we study the unidimensionality of the SCOOHPI scale to use it as an index. Methods: We studied the internal consistency of the items of the SCOOHPI scale. Then, we studied the construct validity. The unidimensionality of the SCOOHPI scale was studied by the partial credit model. Results: The data used in this study come from five hospitals, and the total number of individuals participating in this study is 96, of which 72% are men and 59% are smokers. The SCOOHPI scale has good internal consistency (α = 0.84). The validity of divergence was checked by the absence of correlation between the SCOOHPI scale and the GOHAI (General Oral Health Assessment Index) scale. The unidimensionality of the SCOOHPI scale with data smoothing was demonstrated by the partial credit model. Conclusion: In this study, we completed the study of the psychometric validation of the SCOOHPI. The SCOOHPI scale can then contribute to improving evaluation of the coping strategies of schizophrenic patients with regard to oral health.

This study aims to reveal: (1) the characteristics of diagnostic test items used in mathematics subject of the first grade of senior high school (SHS); (2) the degree of errors from several types of students’ errors in answering mathematics test; and (3) the dominant factor causing the students to make mistakes in answering mathematics test. This study used a quantitative approach involving the first graders of eight SHSs in Mataram as the population. The sample was collected by a proportionate random sampling technique, consisting of 350 students for preliminary field testing and 450 students for main field testing. The research instrument was a mathematics diagnostic test, questionnaire, and interview guidelines. The results show that: (1) the diagnostic test instrument meets the qualitative and quantitative content validity, proves empirically fit with Partial Credit Model (PCM), has reliability index of 0.92 (high category), and all items in the diagnostic test instrument are categorized in moderate difficulty; (2) misrepresentation becomes dominant errors if compared with misconceptions, the counting errors, and procedural errors. The errors dominant in the topic domain are Inequalities Linear System Two Variables if compared with Rational and Irrational Inequality One Variable, Equations and Inequalities of Absolute Value, and Linear Equations System Three Variables; and (3) most of the students do not understand how to solve the problem of inequality, determining factor quadratic equations, determining the members of the set completion, problems concerning graphs, and problems that require the capability of language interpretation into the mathematics model.

The purpose of this study is to develop and evaluate two diagnostic classification models (DCMs) for scoring ordinal item data. We first applied the proposed models to an operational dataset and compared their performance to an epitome of current polytomous DCMs in which the ordered data structure is ignored. Findings suggest that the much more parsimonious models that we proposed performed similarly to the current polytomous DCMs and offered useful item-level information in addition to option-level information. We then performed a small simulation study using the applied study condition and demonstrated that the proposed models can provide unbiased parameter estimates and correctly classify individuals. In practice, the proposed models can accommodate much smaller sample sizes than current polytomous DCMs and thus prove useful in many small-scale testing scenarios.

The Graded Response Model (GRM) and the Partial Credit Model (PCM) of Item Response Theory (IRT) were applied in the item analysis of a scale that evaluates psychology students's beliefs about the usefulness of mathematics. The scale comprises 8 items in polytomous response format (6-point Likert-type). The sample was made up by 1875 students of the Psychology school of the University of Buenos Aires. All analyses based on IRT were performed by operating the MULTILOG software. The parameters estimation was carried out trough Marginal Maximum Likelihood procedures. Previously, the unidimensionality assumption required by the models was confirmed. The GRM showed better fit indexes than PCM and higher Test Information Function. The findings provide validity evidences based on the internal structure of scale.

Este trabajo describe el uso del Modelo de Crédito Parcial (MCP) para medir Alfabetización Económica en niños, a través de ítems de Elección Múltiple Ordenada (EMO). Elaboramos ítems EMO basados en un modelo piagetano que propone tres niveles progresivos en el desarrollo de conceptos y razonamiento sobre la economía. En el formato EMO, cada una de las posibles alternativas de respuesta estuvo ligada a una etapa cognitiva de desarrollo del pensamiento económico propuesta por la teoría. Los ítems fueron administrados a 1035 niños, entre 10 a 15 años de edad, y calibrados utilizando el MCP. Los resultados muestran tanto la utilidad de los ítems EMO como la eficiencia del MCP como herramientas para puntuar, analizar e interpretar evaluaciones diagnósticas construidas en un marco de referencia piagetano.This paper describes the use of the Partial Credit Model (PCM) to measure Economic Literacy in children, with Ordered Multiple-Choice Items (OMC). We developed OMC items based on a Piagetian model that proposes three progressive levels in the development of concepts and reasoning about the economy. In OMC format, each of the possible answer choices was linked to a cognitive stage of economical thinking proposed by the theory. The items were administered to 1035 children, ages 10 to 15 years, and calibrated using the PCM. The results show both the utility of OMC items and the efficiency of PCM as tools for the score, analysis, and interpretation of diagnostic assessments constructed in a Piagetian framework.

Item response theory (IRT) models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.