This study aimed to address quality management in the university classroom, specifically in the Department of Basic Sciences of the Dean of Civil Engineering of the Universidad Centroccidental ...Lisandro Alvarado. It was conceived under the modality of qualitative research of ethnographic type with an interpretive character. The research process involved three phases: obtaining information, in which key informants were selected from a group of four (4) teachers and three (3) students in an intentional sampling, interview techniques were applied and participant observation to record and categorize the informants' opinions. In the second phase, the analysis and interpretation of the information was done using the GLATER model, which allowed orientating it from four stages: the first stage assignment of codes and dimensions, second stage of description, third of categorization and fourth stage of interpretation. In the third and final phase the construction of a theoretical approach of the quality management based on the managerial method PDCA, proposed by the researcher, was carried out starting from the analysis of the categories and their properties. As a result of this process, the thematic categories emerged: Integral Training, Availability and Use of School Media, Dynamics of Organizational Learning and Institutional Leadership.
Data science follows a data-driven approach focused on non-hypothesised pattern discovery from data in an automatic manner (or semi-automatic). Social science areas frequently address latent ...variables, whose study is mainly guided by a deductive paradigm and requires a confirmatory scope. Both areas, data science and latent variable research, have ample development, but their combination is not mature. The objective is to develop a practical and reproducible framework for data science projects from a psychometric perspective for the study of latent variables. The framework is practical and integrative, and consists of nine steps, which guide from the construct definition, discovery and confirmed patterns (structural equation modelling and considering goodness-of-fit, reliability, validity, equity and subjects' segmentation) to the use of patterns. This last step includes three sub-steps: one for structural hypotheses contrast and two computational approaches (supervised: machine learning; and non-supervised: principal component analysis). Additionally, the framework is efficient and accessible due to its semi-automation using the R language. The framework is applied to study the relationship between class quality and student satisfaction and is consistent with the reproducible research paradigm, widely used in computational areas and recently demanded by social science.
Background: Quality care and education in the first eight years of life play a critical role in young children’s development. Despite how the importance of Early Childhood Education (ECE) has become ...more widely accepted both in the United Arab Emirates (UAE) and across the broader Middle East region, research studies related to child learning and development in ECE context and quality have been sparse. This article presents findings of the Ras Al Khaimah-based ECE research study which investigated the process and structural quality of privately owned Early Childhood Education and Care centers (ECECs).
Methods: Data were collected from all 39 licensed private ECECs operational in the emirate between 2016 and 2018 using the Early Childhood Environmental Rating Scale-Revised Edition (ECERS-R) and Classroom Assessment Scoring System
Refactoring is the maintenance process of restructuring software source code to improve its quality without changing its external behavior. Move Method Refactoring (MMR) refers to moving a method ...from one class to the class in which the method is used the most often. Manually inspecting and analyzing the source code of the system under consideration to determine the methods in need of MMR is a costly and time-consuming process. Existing techniques for identifying MMR opportunities have several limitations, such as scalability problems and being inapplicable in early development stages. Most of these techniques do not consider semantic relationships.
We introduce a measure and a corresponding model to precisely predict whether a class includes methods in need of MMR. The measure is applicable once a class has entered the early development stages without waiting for other classes to be developed.
The proposed measure considers both the cohesion and coupling aspects of methods. In addition, the measure uses structural and semantic data available within the class of interest. A statistical technique is applied to construct prediction models for classes that include methods in need of MMR. The models are applied on seven object-oriented systems to empirically evaluate their abilities to predict MMR opportunities.
The results show both that the prediction models based on the proposed measure had outstanding prediction abilities and that the measure was able to correctly detect more than 90% of the methods in need of MMR within the predicted classes.
The proposed measure and corresponding prediction models are expected to greatly assist software engineers both in locating classes that include methods in need of MMR and in identifying these methods within the predicted classes.
This study presents a global sizing design optimisation of a permanent magnet synchronous generator (PMSG) using the three-dimensional finite-element analysis (3D FEA). To build an optimal parametric ...model structure, the efficiency improvement of the PMSG is taken as the main objective, where iron and copper losses were minimised. A dual-level response surface methodology (D-RSM) with a window-zoom-in approach for a variable-speed-range analysis as a global optimisation technique is employed to find out the optimal design variables of the objective function. The D-RSM using mixed-resolution central composite design (MR-CCD), full factorial design, central composite design (CCD), and box-Behnken design are applied to optimise the geometry with very small error. Analysis of variance and multi-level RSM plots are used to check the adequacy of fit. However, the MR-CCD exceeds the range of the boundary in the design region. Hence, a modified MR-CCD is used that improves the efficiency and proposes the parameter settings to manufacture the high-class quality wind generator. The validation of the analytical and numerical fashions is successfully achieved through rigorous FEA, and the experimental verifications perfectly marked the theoretical and significance optimisation design.
Identifying the impact of teacher characteristics on academic achievement has been a salient and reoccurring topic in education. We employ a twin-by-year identification strategy using matched ...teacher-student data from North Carolina to credibly estimate the impact of teacher characteristics such as experience, certification, and advanced degrees on academic achievement in math and reading. By using within-family variation the estimates from our model improve upon on earlier work by for time varying unobservable family shocks to non-schooling inputs. Our findings reveal that teacher experience and National Board certification have positive and significant effects on achievement in reading and math; however, we find inconclusive effects for advanced degrees. Notably, we show that teacher experience has the largest effects on student achievement, but our effects are smaller than the standard estimates in the literature. Overall, our estimates provide lower upper bounds for these key teacher characteristics.
Refactoring is a maintenance task that refers to the process of restructuring software source code to enhance its quality without affecting its external behavior. Inspecting and analyzing the source ...code of the system under consideration to identify the classes in need of extract subclass refactoring (ESR) is a time consuming and costly process.
This paper explores the abilities of several quality metrics considered individually and in combination to predict the classes in need of ESR.
For a given a class, this paper empirically investigates, using univariate logistic regression analysis, the abilities of 25 existing size, cohesion, and coupling metrics to predict whether the class is in need of restructuring by extracting a subclass from it. In addition, models of combined metrics based on multivariate logistic regression analysis were constructed and validated to predict the classes in need of ESR, and the best model is justifiably recommended. We explored the statistical relations between the values of the selected metrics and the decisions of the developers of six open source Java systems with respect to whether the classes require ESR.
The results indicate that there was a strong statistical relation between some of the quality metrics and the decision of whether ESR activity was required. From a statistical point of view, the recommended model of metrics has practical thresholds that lead to an outstanding classification of the classes into those that require ESR and those that do not.
The proposed model can be applied to automatically predict the classes in need of ESR and present them as suggestions to developers working to enhance the system during the maintenance phase. In addition, the model is capable of ranking the classes of the system under consideration according to their degree of need of ESR.
The work we present is the result of personal reflection on the conclusions of the works consulted; also of the experience as a teacher of adolescents and, finally, of the need to verify with the ...research, what we intuited from the professional practice. As a general objective To determine the incidence of the quality of the class in the academic results of the students of the fourth year of the José Ingenious Educational Unit. Inductive, deductive, analysis and synthesis methods were applied, the type of study is descriptive qualitative, with a type of pre-experimental design, where we apply an initial prestet and a final postet, the results show that the quality of the classes influences the performance student academic, which is reflected, more than 33% believe that their peers will get better results than them, more than 65% think that the evaluation is doing well.
El trabajo que presentamos es fruto de la reflexión sobre las conclusiones de trabajos consultados; también de la experiencia como profesor de adolescentes y, por último, de la necesidad de verificar con la investigación, lo que intuíamos desde la práctica profesional. Como objetivo general: Determinar la incidencia de la calidad de la clase en los resultados académicos de los estudiantes del cuarto año de la Unidad Educativa José Ingeniero. Se aplicaron métodos inductivos, deductivos, de análisis y síntesis, el tipo de estudio es cualitativo descriptivo, con un tipo de diseño pre-experimental, donde aplicamos un pretest inicial y un postest final, los resultados demuestran que la calidad de las clases influyen en el rendimiento académico de los estudiantes, que se refleja, más del 33% creen que sus compañeros obtendrán mejores resultados que ellos, más del 65% piensa que la evaluación la está haciendo bien.
► The paper empirically addresses whether to include or exclude special methods from cohesion measurements. ► Constructors must be included and access methods must be excluded when using cohesion ...metrics in Extract Class refactoring activity. ► Including special methods does not significantly affect the abilities of the cohesion metrics to detect faulty classes.
Class cohesion is a key attribute that is used to assess the design quality of a class, and it refers to the extent to which the attributes and methods of the class are related. Typically, classes contain special types of methods, such as constructors, destructors, and access methods. Each of these special methods has its own characteristics, which can artificially affect the class cohesion measurement. Several metrics have been proposed in the literature to indicate class cohesion during high- or low-level design phases. The impact of accounting for special methods in cohesion measurement has not been addressed for most of these metrics. This paper empirically explores the impact of including or excluding special methods on cohesion measurements that were performed using 20 existing class cohesion metrics. The empirical study applies the metrics that were considered to five open-source systems under four different scenarios, including (1) considering all special methods, (2) ignoring only constructors, (3) ignoring only access methods, and (4) ignoring all special methods. This study empirically explores the impact of including special methods in cohesion measurement for two applications of interest to software practitioners, including refactoring and predicting faulty classes. The results of the empirical studies show that the cohesion values for most of the metrics considered differ significantly across the four scenarios and that this difference significantly affects the refactoring decisions, but does not significantly affect the abilities of the metrics to predict faulty classes.
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