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Abulela, Mohammed A. A.; Rios, Joseph A. – Applied Measurement in Education, 2022
When there are no personal consequences associated with test performance for examinees, rapid guessing (RG) is a concern and can differ between subgroups. To date, the impact of differential RG on item-level measurement invariance has received minimal attention. To that end, a simulation study was conducted to examine the robustness of the…
Descriptors: Comparative Analysis, Robustness (Statistics), Nonparametric Statistics, Item Analysis
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Aksu, Gokhan; Reyhanlioglu Keceoglu, Cigdem – Eurasian Journal of Educational Research, 2019
Purpose: In this study, Logistic Regression (LR), CHAID (Chi-squared Automatic Interaction Detection) analysis and data mining methods are used to investigate the variables that predict the mathematics success of the students. Research Methods: In this study, a quantitative research design was employed during the data collection and the analysis…
Descriptors: Regression (Statistics), Data Collection, Information Retrieval, Predictor Variables
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Bulut, Okan; Yavuz, Hatice Cigdem – International Journal of Assessment Tools in Education, 2019
Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…
Descriptors: Data Analysis, Educational Research, Educational Researchers, Computer Software
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Finch, W. Holmes; Marchant, Gregory J. – Online Submission, 2017
A recursive partitioning model approach in the form of classification and regression trees (CART) was used with 2012 PISA data for five countries (Canada, Finland, Germany, Singapore-China, and the Unites States). The objective of the study was to determine demographic and educational variables that differentiated between low SES student that were…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
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Özkan, Metin; Balci, Suphi; Kayan, Selman; Is, Engin – International Education Studies, 2018
The objective of the study was to make a comparison among the two countries according to the level of sufficiency of educational resources and to determine the accuracy level at which variables related to educational resources can classify the schools on the basis of countries. Relational survey model was used. The sample group of the study was…
Descriptors: Educational Resources, Educational Quality, Comparative Analysis, Comparative Education
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Depren, Serpil Kilic – Journal of Baltic Science Education, 2018
Turkey is ranked at the 54th out of 72 countries in terms of science achievement in the Programme for International Student Assessment (PISA) survey conducted in 2015, which is a very big disappointment for that country. The aim of this research was to determine factors affecting Turkish students' science achievements in order to identify the…
Descriptors: Foreign Countries, Prediction, Science Achievement, Multivariate Analysis
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Güzeller, Cem Oktay; Eser, Mehmet Taha; Aksu, Gökhan – International Journal of Progressive Education, 2016
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…
Descriptors: Foreign Countries, Mathematics Achievement, Secondary School Students, Grade 10
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Rutkowski, Leslie – Applied Measurement in Education, 2014
Large-scale assessment programs such as the National Assessment of Educational Progress (NAEP), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA) use a sophisticated assessment administration design called matrix sampling that minimizes the testing burden on individual…
Descriptors: Measurement, Testing, Item Sampling, Computation
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Simonová, Natalie; Soukup, Petr – British Journal of Sociology of Education, 2015
The main objective of this paper is to show to what extent and why students with the same academic aptitude but different social backgrounds have different odds of entering university. For our analysis, we separated primary and secondary factors of social origin in the formation of educational inequalities. The results show that the primary and…
Descriptors: Foreign Countries, Academic Aspiration, Social Differences, Cultural Capital
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Cooper, Kristy S. – American Educational Research Journal, 2014
This case study analyzes how and why student engagement differs across 581 classes in one diverse high school. Factor analyses of surveys with 1,132 students suggest three types of engaging teaching practices--connective instruction, academic rigor, and lively teaching. Multilevel regression analyses reveal that connective instruction predicts…
Descriptors: Teaching Methods, High School Students, Learner Engagement, Regression (Statistics)
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Alivernini, F.; Manganelli, S. – International Journal of Science Education, 2015
A huge gap in science literacy is between students who do not show the competencies that are necessary to participate effectively in life situations related to science and technology and students who have the skills which would give them the potential to create new technology. The objective of this paper is to identify, for 25 countries, distinct…
Descriptors: Scientific Literacy, Cross Cultural Studies, Student Characteristics, Scores