The purpose of this study is to develop a valid and reliable scale to determine and evaluate the different dimensions of data literacy at school. The study is a quantitative descriptive survey model. The sampling for exploratory factor analysis was formed of 307 and confirmatory factor analysis 338 teachers and school administrators who are on…

This study investigated the mediated distributed leadership effects on student achievement through teacher job satisfaction and disciplinary climate in Turkish high schools. We employed school-, teacher-, and student-level datasets drawn from the 2018 PISA and TALIS datasets and performed a multilevel structural equation model (MSEM). The results…

This study aimed at understanding and investigating the lived experiences of early childhood teachers' observation practices as a professional tool. Interpretative phenomenological approach was utilized to investigate participants' experiences deeply from their lived experiences. The current study's participants consisted of five early childhood…

This paper offers guidance on employing open and creative methods for co- designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. Through innovative approaches, we aim to enhance participation in learning, research and policymaking, fostering a comprehensive…

The 2023 edition of 'Key data on teaching languages at school in Europe' depicts the main education policies related to the teaching of languages in schools in 39 European education systems. It answers questions about the number and range of foreign languages studied by students, the instruction time dedicated to foreign language teaching, the…

In this study, technology-enhanced statistical problem-solving tasks designed by pre-service teachers (PTs) were examined. The PTs designed 28 tasks. The designed tasks were analyzed within the context of the Considerations for Design and Implementation of Statistics Tasks (C-DIST) components. It was revealed that the tasks were mostly designed…

The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…

The research aims to determine the factors affecting PISA 2018 reading skills using the Random Forest and MARS methods and to compare their prediction abilities. This study used the information from 5713 students, 2838 (49.7%) male and 2875 (50.3%) female, in the PISA 2018 Turkey. The analysis shows the MARS method performed better than the Random…

This study aims to draw attention to data literacy, which is considered an important skill of the 21st century, and to provide an example activity that would incorporate it into chemistry education. The activity was designed using real data of Robert Boyle's experiment. The activity aims to examine Boyle's data in such a way to support data…

This study aimed to investigate pre-service pre-school education teachers' data representation activities in terms of their relation to real life, the appropriateness of the data that the children can collect, the conformability of the graphs required for the data representation to the children's level, and the clarity of open-ended questions…

Child sexual abuse (CSA) is not only a serious danger for children and families, but it is also a problem that concerns society economically and spiritually. The aim of this study is to examine career choices and educational problems of individuals who have experienced CSA. Participants of this study consist of 73 CSA victims. The data have been…

This study aims to perform a descriptive analysis of the websites of public and foundation universities in Türkiye to reveal the current positioning context of their units in relation to artificial intelligence (AI) ecosystems. The study was designed using a holistic multiple case study method, in which the dimensions specified in the…

In this study, it is aimed to investigate the impact of different missing data handling methods on the detection of Differential Item Functioning methods (Mantel Haenszel and Standardization methods based on Classical Test Theory and Likelihood Ratio Test method based on Item Response Theory). In this regard, on the data acquired from 1046…

This phenomologic study was carried out in order to determine how 63 pre-service chemistry teachers graduated from Chemistry Branch of Science Faculty in the pedagogical training program during 2013-2015 academic years defined the concepts of density and melting and boiling points and how they interpreted the data in micro levels. A diagnostic…

Missing data is a common problem in datasets that are obtained by administration of educational and psychological tests. It is widely known that existence of missing observations in data can lead to serious problems such as biased parameter estimates and inflation of standard errors. Most of the missing data imputation methods are focused on…