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Schweizer, Karl; Gold, Andreas; Krampen, Dorothea – Educational and Psychological Measurement, 2023
In modeling missing data, the missing data latent variable of the confirmatory factor model accounts for systematic variation associated with missing data so that replacement of what is missing is not required. This study aimed at extending the modeling missing data approach to tetrachoric correlations as input and at exploring the consequences of…
Descriptors: Data, Models, Factor Analysis, Correlation
Lisa Haake; Sebastian Wallot; Monika Tschense; Joachim Grabowski – Reading and Writing: An Interdisciplinary Journal, 2024
Recurrence quantification analysis (RQA) is a time-series analysis method that uses autocorrelation properties of typing data to detect regularities within the writing process. The following paper first gives a detailed introduction to RQA and its application to time series data. We then apply RQA to keystroke logging data of first and foreign…
Descriptors: Writing (Composition), Keyboarding (Data Entry), Word Processing, Writing Processes
Maya Murad; KC Collins – Canadian Journal of Learning and Technology, 2024
Procrastination is a prevalent issue among university students and leads to long-term negative impacts on academic performance as well as mental health and quality of life. This paper investigated StudyTracker, a self-tracking digital application (app) that we developed for university students to use to track their study sessions. The app provided…
Descriptors: Computer Oriented Programs, Attention, Self Management, Data Collection
Ian Hardy; Vicente Reyes; Louise G. Phillips; M. Obaidul Hamid – Journal of Education Policy, 2024
Data infrastructures exist in a variety of formats. This article draws on the insights of senior personnel involved in developing a new data dashboard in one state jurisdiction in Australia. While literature on dashboards often focuses on the teachers and learners influenced by them, there is less attention to those involved in their development…
Descriptors: Learning Analytics, Learning Processes, Learning Management Systems, Computer Software
Su, Hsu-Lin; Chen, Po-Hsi – Educational and Psychological Measurement, 2023
The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant's factor pattern. Thus, in this study, we proposed three analysis procedures…
Descriptors: Data Analysis, Correlation, Classification, Factor Structure
Sotoudeh, Ramina; DiMaggio, Paul – Sociological Methods & Research, 2023
Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…
Descriptors: Algorithms, Simulation, Prediction, Correlation
Sefton-Green, Julian; Pangrazio, Luci – Educational Philosophy and Theory, 2022
Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…
Descriptors: Data Analysis, Governance, Educational Philosophy, Barriers
Jamal Kay B. Rogers; Tamara Cher R. Mercado; Ronald S. Decano – Journal of Education and Learning (EduLearn), 2025
Poor academic performance remains among the most concerning educational issues, especially in higher education and online learning. To address the concern, institutions like the University of Southeastern Philippines (USeP) leverage educational data mining (EDM) techniques to generate relevant information from learning management systems (LMS)…
Descriptors: Foreign Countries, Learning Management Systems, Academic Achievement, Data Analysis
Paiva Barbosa, Victor; Bastos Silveira, Bruna; Amorim dos Santos, Juliana; Monteiro, Mylene Martins; Coletta, Ricardo D.; De Luca Canto, Graziela; Stefani, Cristine Miron; Guerra, Eliete Neves Silva – Research Synthesis Methods, 2023
Systematic reviews (SRs) of preclinical studies are marked with poor methodological quality. In vitro studies lack assessment tools to improve the quality of preclinical research. This methodological study aimed to identify, collect, and analyze SRs based on cell culture studies to highlight the current appraisal tools utilized to support the…
Descriptors: Cytology, Research, Research Methodology, Correlation
Ho, Andrew D. – AERA Open, 2020
The Stanford Education Data Archive (SEDA) launched in 2016 to provide nationally comparable, publicly available test score data for U.S. public school districts. I introduce a special collection of six articles that each use SEDA to lend their questions and findings a national scope. Together, these articles demonstrate a range of uses of SEDA…
Descriptors: Archives, Scores, Public Schools, School Districts
Butuner, Resul; Calp, M. Hanefi – International Journal of Assessment Tools in Education, 2022
Many institutions in the field of education have been involved in distance education with the learning management system. In this context, there has been a rapid increase in data in the e-learning process as a result of the development of technology and the widespread use of the internet. This increase is in the size of large data. Today, big data…
Descriptors: Distance Education, Academic Achievement, Data Collection, Data Analysis
Petersson, Jöran; Sayers, Judy; Andrews, Paul – International Journal of Research & Method in Education, 2023
Measures of association, which typically require pairwise data, are widespread in many aspects of educational research. However, due to the need to reduce their content to equal numbers of units of analysis, they are rarely found in the analysis of textbooks. In this paper, we present two methods for overcoming this limitation, one through the use…
Descriptors: Textbooks, Textbook Content, Content Analysis, Mathematics Education
Oleson, Jacob J.; Jones, Michelle A.; Jorgensen, Erik J.; Wu, Yu-Hsiang – Journal of Speech, Language, and Hearing Research, 2022
Purpose: The analysis of Ecological Momentary Assessment (EMA) data can be difficult to conceptualize due to the complexity of how the data are collected. The goal of this tutorial is to provide an overview of statistical considerations for analyzing observational data arising from EMA studies. Method: EMA data are collected in a variety of ways,…
Descriptors: Experience, Surveys, Measurement Techniques, Statistical Analysis
Van der Mierden, Stevie; Spineli, Loukia Maria; Talbot, Steven R.; Yiannakou, Christina; Zentrich, Eva; Weegh, Nora; Struve, Birgitta; Zur Brügge, Talke Friederike; Bleich, André; Leenaars, Cathalijn H. C. – Research Synthesis Methods, 2021
Systematic reviews with meta-analyses are powerful tools that can answer research questions based on data from published studies. Ideally, all relevant data is directly available in the text or tables, but often it is only presented in graphs. In those cases, the data can be extracted from graphs, but this potentially introduces errors. Here, we…
Descriptors: Graphs, Meta Analysis, Data, Correlation
Kane Meissel; Esther S. Yao – Practical Assessment, Research & Evaluation, 2024
Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…
Descriptors: Computer Software, Programming Languages, Effect Size, Correlation