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Joao M. Souto-Maior; Kenneth A. Shores; Rachel E. Fish – Annenberg Institute for School Reform at Brown University, 2025
Whether selection processes contribute to group-level disparities or merely reflect pre-existing inequalities is an important societal question. In the context of observational data, researchers, concerned about omitted-variable bias, assess selection-contributing inequality via a kitchen-sink approach, comparing selection outcomes of…
Descriptors: Control Groups, Predictor Variables, Correlation, Selection Criteria
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Ahmadi, Mohammad; Dileepan, Parthasarati; Wheatley, Kathleen K. – Journal of Education for Business, 2016
This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…
Descriptors: Strategic Planning, Data, Data Analysis, Statistical Analysis
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Ay, Sule; Sahin, Seyma; Okmen, Burcu; Incirci, Ayhan – Journal of Education and Practice, 2016
It was aimed in this study to reveal the general tendency of studies in the field of education by examining the papers in the high-impact A-class SSCI journals, to which qualified papers are accepted from all around the world, in terms of their dependent-independent variables, sample or study groups, research designs, data collection instruments,…
Descriptors: Content Analysis, Journal Articles, Educational Research, Predictor Variables
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Wise, Alyssa Friend; Shaffer, David Williamson – Journal of Learning Analytics, 2015
It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…
Descriptors: Learning Theories, Predictor Variables, Data, Data Analysis
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Karatas, Serçin; Yilmaz, Ayse Bagriacik; Dikmen, Cemal Hakan; Ermis, Ugur Ferhat; Gürbüz, Onur – Quarterly Review of Distance Education, 2017
The aim of this study is to determine the trend concerning interaction in distance education between the years 2011 and 2015. According to this aim, 544 articles in the databases of EBSCO, Scopus, and Web of Science were examined. The examination has been conducted on the basis of various variables including year, country, number of authors,…
Descriptors: Distance Education, Trend Analysis, Interaction, Qualitative Research
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Demirer, Veysel; Erbas, Cagdas – Turkish Online Journal of Distance Education, 2016
This study aims to review studies on virtual learning environments in Turkey through the content analysis method. 63 studies consisting of thesis, articles and proceedings published in Turkish and English between 1996-2014 years were analyzed. It was observed that "Second Life" was mostly preferred as the virtual learning environment.…
Descriptors: Foreign Countries, Virtual Classrooms, Electronic Learning, Educational Trends
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Ohle, Annika; Boone, William J.; Fischer, Hans E. – International Journal of Science and Mathematics Education, 2015
Decreasing student interest and achievement during the transition from elementary to secondary school is an international problem, especially in science education. The question of what factors influence this decline has been a widely discussed topic. This study focuses on investigating the relationship of elementary school teachers' content…
Descriptors: Science Teachers, Elementary School Teachers, Physics, Pedagogical Content Knowledge
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Osler, James Edward – Journal on School Educational Technology, 2013
This monograph provides an active discourse on the novel field of "Educational Science" and how it conducts in-depth research investigations first presented in an article by the author in the i-managers "Journal of Mathematics." Educational Science uses the innovative Total Transformative Trichotomy-Squared [Tri-Squared] Test…
Descriptors: Psychometrics, Qualitative Research, Statistical Analysis, Inquiry
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Cox, Bradley E.; McIntosh, Kadian; Reason, Robert D.; Terenzini, Patrick T. – Review of Higher Education, 2014
Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…
Descriptors: Data Analysis, Statistical Inference, Research Problems, Computation
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Papamitsiou, Zacharoula; Economides, Anastasios A. – Educational Technology & Society, 2014
This paper aims to provide the reader with a comprehensive background for understanding current knowledge on Learning Analytics (LA) and Educational Data Mining (EDM) and its impact on adaptive learning. It constitutes an overview of empirical evidence behind key objectives of the potential adoption of LA/EDM in generic educational strategic…
Descriptors: Data Analysis, Data Collection, Educational Research, Learning Processes
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Rockinson-Szapkiw, Amanda J.; Bray, Oliver R., Jr.; Spaulding, Lucinda S. – Journal of College Student Retention: Research, Theory & Practice, 2014
This study examines how GRE scores can be used to better understand Education doctoral candidates' methodology choices for the dissertation as well as their persistence behaviors. Candidates' of one online doctoral education program were examined. Results of a MANOVA suggested that there is no difference in GRE scores based on doctoral candidates'…
Descriptors: Predictive Validity, Doctoral Programs, College Entrance Examinations, Success
Pigott, Therese D.; Williams, Ryan T.; Polanin, Joshua R.; Wu-Bohanon, Meng-Jia – Society for Research on Educational Effectiveness, 2012
The purpose of this research to investigate the heterogeneity of per-pupil expenditure (PPE) slope estimates in predicting student achievement. The research question guiding this project is: how does the measured relationship between per-pupil expenditure vary across studies that use different models? In concert with SREE's 2012 conference mission…
Descriptors: Productivity, Expenditures, Academic Achievement, Regression (Statistics)
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Osler, James Edward; Waden, Carl – Journal on School Educational Technology, 2013
This paper discusses the implementation of the Tri-Squared Test as one of many advanced statistical measures used to verify and validate the outcomes of an initial study on academic professional's perspectives on the use, success, and viability of 9th Grade Freshman Academies, Centers, and Center Models. The initial research investigation…
Descriptors: At Risk Students, Statistical Analysis, School Holding Power, Academic Achievement
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Kim, Su-Young; Kim, Jee-Seon – Structural Equation Modeling: A Multidisciplinary Journal, 2012
This article investigates three types of stage-sequential growth mixture models in the structural equation modeling framework for the analysis of multiple-phase longitudinal data. These models can be important tools for situations in which a single-phase growth mixture model produces distorted results and can allow researchers to better understand…
Descriptors: Structural Equation Models, Data Analysis, Research Methodology, Longitudinal Studies
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Lee, In Heok – Career and Technical Education Research, 2012
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…
Descriptors: Vocational Education, Data Collection, Maximum Likelihood Statistics, Educational Research
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