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Realistic Mathematics Education (RME) includes identifying and solving problems. Besides, it is an effort to organize a case, reorganize it according to new ideas, and concretize and rediscover the case to understand it better. This research aims to determine the effect of RME-based teaching against traditional methods, develop a general opinion, and contribute to the literature. In the study, the meta-analysis method was used to synthesize the results of independent experimental studies examining RME's effect on academic achievement. The data set of the research was created in September 2022. Necessary searches were carried out within the ULAKBIM TR Index, YÖK Thesis, ERIC and Web of Science databases. As a result of these searches, 54 studies met the selection criteria to be included in the meta-analysis. The random-effects model was used in the research. As a result of the analysis, the calculated effect sizes were all positive. In the light of this finding, it has been concluded that in all studies, RME-based teaching was more effective than traditional methods on students' academic achievement in mathematics. A moderator analysis was also carried out to determine whether the effect sizes differed statistically significantly according to the variables "publication type, sample size, and educational stage." As a result of the moderator analysis, it was concluded that all moderator variables obtained from the GME-based teaching practices significantly affected the combined effect size.

The agreement between raters is examined within the scope of the concept of "inter-rater reliability". Although there are clear definitions of the concepts of agreement between raters and reliability between raters, there is no clear information about the conditions under which agreement and reliability level methods are appropriate to use. In this study, the comparison of eight different agreement coefficients used for the same purpose and the similarity of the results obtained with the G coefficient calculated within the framework of generalizability theory were examined. Within the scope of the study, it was determined that there were differences between the agreement coefficients of the evaluations made by the seven raters for 49 students over six open-ended items. As a result of the study, it was determined that the agreement coefficients differed significantly according to the method used and the level of agreement could be interpreted as low-medium-high according to the method used. In addition, as a result of the generalizability analysis, it was determined that the largest proportion of the variance components resulted from the difference between the raters and equal to 40% of the total variance between the raters. For this reason, it is recommended that researchers first examine the variance components originating from the person, item, and raters while determining the inter-rater reliability, and finally, report a few of the appropriate coefficients in case the inter-rater variance is low.

The main aim of achieving with the reliability generalization is to investigate the variability related to the reliability estimates and to try to characterize the sources of this variability. As part of the research, a reliability generalization study was carried out on the basis of Beck Depression Inventory-II to investigate potential factors contributing to the variability of the reliability of the measurement results and to examine the sources of the measurement error. Within the scope of the study, it was published in English between 2011-2019 and only 40 articles in the type of article were examined. The Kappa coefficient for the coding form was determined to be 0.93 and it was concluded that the measurement results performed for the coding form were valid and reliable. Jamovi and R programs were used in the research. When the test results regarding publication bias are evaluated in a holistic way, it is concluded that there is no publication bias related to the studies included in the research. It was thought that the heterogeneity observed by the researchers may indicate an amount of heterogeneity to be examined and moderator analyzes were performed. As a result of the moderator analysis, it was determined that any of the continuous and categorical moderator variables did not have an explanatory role regarding the variability between the reliability estimates of the inventory. In order to carry out qualified RG studies in the future, it is recommended that researchers report their reliability estimates regarding the measurement results of their studies.

Science literacy, which is included in Programme for International Student Assessment (PISA) as an assessment area, is an important research and discussion area of science education literature with all its dimensions. In this study, the clustering results of the students from 34 Organization for Economic Cooperation and Development (OECD) countries participating in the PISA 2015 test and sampled by systematic sampling method are obtained by K-Means Clustering and Two-Step Cluster Analysis using the factor scores and PISA science literacy average scores. It is thought that the study is of great importance in terms of dividing individuals into clusters according to science instruction methods and the mean of plausible values and having an idea about how each cluster is defined. As a result of the K-means cluster analysis, it was determined that the input variable with the highest level of importance in the formation of the first and third clusters in which the students with the highest scores were included was teacher-directed science instruction, and after this variable, the input variable with the highest level of importance was the perceived feedback from science teachers. Within the scope of the Two-Step Clustering Analysis, it was determined that teacher-directed science instruction has the most importance in terms of the decomposition of clusters, followed by adaptive instruction in science lessons in terms of importance level.

By applying educational data mining methods to big data related to large-scale exams, functional relationships are discovered in a basic sense and hidden pattern(s) can be revealed. Within the scope of the research, to show how the self-organizing map (SOM) method can be used in terms of educational data mining, how SOM differs from other clustering methods in terms of visual outputs (map) and how to interpret the outputs, and it is aimed to give information about how effective the variables are in grouping individuals into groups according to the answers given to the items. In this study, students of OECD countries participating in the 2015 PISA were modeled using SOM and the outputs of the created model were examined. In this respect, the study can be accepted as a descriptive survey model. According to the results of the analysis, outputs were obtained for the educational process of the data set, the state of neurons, neighborhood distance, code vectors, heat maps, the number of clusters and the distribution of the number of students to countries and clusters. At the same time, it was determined that 4 clusters were formed according to the analysis results, and the most effective variables in clustering by examining the heat maps were perceived feedback from science teachers, teacher-directed science instruction, average of plausible values in science, enquiry based science instruction and adaptive instruction in science lessons. Researchers who want to clearly determine the effectiveness of the input variables in cluster analysis can be advised to use SOM.

This study aims to compare the results of the factor analysis performed with Frequentist and Bayesian approaches. The number of sub-dimensions of the measurement tool obtained from different methods, the variation of the items in the sub-dimensions, and the fit statistics' differentiation were examined. 778 students constitute the study sample. "Buss and Perry Aggression Questionnaire"-short form was used in the study. The results obtained from Bayesian factor analysis and maximum likelihood, minimum residuals, principal axis factoring, ordinary least squares, weighted least squares, generalized least squares factor extraction methods, which are frequentist factor analysis methods, were compared. As a result of the study, the number of factors obtained from different factor extraction methods was the same, and the measurement tool had a four-dimensional structure. The analyses were performed in R, and JASP the factor loading cut-off was set as 0.40. As a result of study, Bayesian approach also yields valid results in terms of factor analysis, similar to the frequentist approach. Bayesian factor analysis method allowed to keep the measurement tool's structure, and there is no need to remove items from the measurement tool. So the researchers were recommended to include the Bayesian factor analysis in their studies.

This study examines meta-analysis studies published in the field of educational sciences from 2010-2019, in journals indexed within the scope of the TÜBITAK ULAKBIM TR Directory. Of the 163 studies scanned, 26 meta-analysis studies that meet the inclusion criteria constitute the sample of this content analysis study. Within this research, a meta-analysis control form (MACF) developed by the researchers was used. The coding made by each of the two researchers has been considered, and it is concluded that the coherence between the codings was is sufficient (82%). The results of this research indicate that the most obvious problems in meta-analysis studies are: not establishing hypotheses; not calculating reliability between encoders; not using a flow chart (in terms of traceability); the use of commercial software in the analysis; not combining effect sizes on a common metric; use of the failsafe N in determining publication bias; evaluation of I[superscript 2] on the basis of categories; and decision making according to the result of the heterogeneity test in model determination. It is thought that the current study will contribute methodologically to the avoidance of errors in future meta-analysis studies.

In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science self-efficacy, and weekly science learning time that have been covered in PISA 2015, whereas students' Science Literacy level was defined as the output variable. The amount of explained variance and the statistics about the correct classification ratios were used in the comparison of the normalization methods discussed in the study. The dataset was analyzed in Matlab2017b software and both prediction and classification algorithms were used in the study. According to the findings of the study, adjusted min-max normalization method yielded better results in terms of the amount of explained variance in different sample sizes compared to other normalization methods; no significant difference was found in correct classification rates according to the normalization method of the data, which lacked normal distribution and the possibility of overfitting should be taken into consideration when working with small samples in the modelling process of artificial neural network. In addition, it was also found that sample size had a significant effect on both classification and prediction analyzes performed with artificial neural network methods. As a result of the study, it was concluded that with a sample size over 1000, more consistent results can be obtained in the studies performed with artificial neural networks in the field of education.

Purpose: The objective of this study is to develop the Inventory of Motive of Preference for Conventional Paper-And-Pencil Tests and to evaluate students' motives for preferring written tests, short-answer tests, true/false tests or multiple-choice tests. This will add a measurement tool to the literature with valid and reliable results to help determine why students prefer certain exam types and their level of preference. Research Methods: In this study, a screening research design was employed during the data collection and the analysis phases. Findings: Cronbach's alpha coefficients were calculated for reliability and it was concluded that the inventory was reliable. First, the exploratory factor analysis was conducted; this was followed by a second confirmatory factor analysis and finally a content validity study to determine the construct validity. A total of 14 items, including 11 items according to the results of the exploratory factor analysis, 1 item based on expert opinion and 2 items according to the results of the confirmatory factor analysis were removed from the survey form of the inventory, resulting in a final form containing 20 items. It was observed that the content validity values of each item in every subtest were sufficient. Implications for Research and Practice: The study results showed that this inventory was an appropriate instrument for evaluating high school students' preference for paper-and-pencil tests. An inventory developed under the scope of this study may be used to determine the factors predicting the examination type preference levels of students by using different samples. These results may be used when deciding the actions to be taken.

This study attempts to determine the factors affecting the mathematics achievement of students in Turkey based on data from the Programme for International Student Assessment 2012 and the correct classification ratio of the established model. The study used mathematics achievement as a dependent variable while sex, having a study room, preparation for mathematics exams, completing homework on time, interest in mathematics, enjoying mathematics and enjoying reading about mathematics were used as independent variables. The study sample consisted of 4478 students participating in PISA 2012. Probit regression analysis was used to analyse the data. According to the findings, it was determined that there was a positive interaction between the dependent variable and all the independent variables except regularly completing homework and that the correct classification ratio of the model was 58 (44%).

The Social Appearance Anxiety Scale (SAAS) is one of the self-report scales that measure the anxiety that occurs when people form a negative body image about their body and appearance. This study provides a reliability generalization about the internal consistency estimates of the Social Appearance Anxiety Scale, which consists of 16 items and a single factor developed by Hart et al. (2008). As a result of the search in the identified databases, 96 studies were found. In 4 of these studies, the scale was not used, 23 did not report the reliability coefficient and 1 study could not be accessed. Reliability generalization study was conducted with 68 studies including the reliability coefficient of the relevant scale. It was concluded that the average reliability coefficient was .937 [.930 - .943]. As a result of moderator analyses, it was concluded that there was a statistically significant difference in Cronbach's alpha coefficient according to the subcategories of "language of the scale" and "country of the participants" variables, but there was no statistically significant difference according to the subcategories of "language of the article", "sample type" and "field of study" variables and "average age" variable. With this study, it was concluded that it would not be appropriate to generalize, that is, to use reliability induction, since the reliability coefficients of the Social Appearance Anxiety Scale obtained in different languages and different countries differ. It is recommended that the authors calculate reliability estimates for the data sets they have and report the reliability coefficients obtained. [ABSTRACT FROM AUTHOR]

The main purpose of the current study was to examine the relationship between marital satisfaction and life satisfaction through meta-analysis method. A total of 6163 studies were identified as a result of the literature scanning and accordingly examined on the basis of their titles and abstracts. Ultimately, results of 19 studies were included to analysis. The findings obtained from analyses were examined and it was determined that there is a significant difference in all subgroups regarding the relationship between marital satisfaction and life satisfaction. Output of REM analysis showed that the pooled effect size of the relationship between marital satisfaction and life satisfaction is moderate (0.46). Considering the screening process within the scope of this study, it can be concluded that there are too many poor reporting practices regarding the studies. [ABSTRACT FROM AUTHOR]

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Copyright of Mersin University Journal of the Faculty of Education / Mersin Üniversitesi Eğitim Fakültesi Dergisi is the property of Mersin University Faculty of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: The pediatric voice handicap index (pVHI) is a widely used proxy-reported outcome measure. However, its reliability values are subject to variability across studies. Accordingly, the objective of this study is to analyze the mean reliability estimation and stratified alpha coefficient of the pVHI. Another aim of the study is to determine if differences in reliability values can be linked to the specific research characteristics., Study Design: This is a meta-analytic reliability generalization study., Methods: Two researchers used Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria to review five databases (Scopus, Web of Science, YÖKTEZ, Ulakbim, and PUBMED) for publications published between 2007 and 2022 that used pVHI. A meta-analysis was then conducted on 12 papers that fit the predetermined inclusion criteria to ascertain the total effect size of the Cronbach's alpha coefficient of pVHI scores. The reliability coefficients of pVHI were computed utilizing Cochran Q, I 2 , and the lower and upper bounds of mean reliability. Additionally, moderator analyses were employed to examine the heterogeneity among studies., Results: The computed mean reliability value was approximately 0.916 [0.8840, 0.9401] which is within the acceptable range (>0.70). Furthermore, the mean stratified Cronbach's alpha coefficient was found to be roughly 0.95. The heterogeneity statistics indicated that the reliability estimations for each study varied significantly (Q ∼ (df = 11) ∼ = 163.6172, P < 0.0001; I 2 = 93.90%)., Conclusions: Results indicate that pVHI yields sufficiently reliable outcomes. Furthermore, the reliability of the pVHI remained consistent regardless of index language, participant group (healthy, dysphonic, or both), or continent of origin. These results improve the clinical value and utility of pVHI by providing further evidence of its reliability., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)