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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
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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
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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
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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
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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
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Kuvar, Vishal; Flynn, Lauren; Allen, Laura; Mills, Caitlin – International Educational Data Mining Society, 2023
Computer-mediated social learning contexts have become increasingly popular over the last few years; yet existing models of students' cognitive-affective states have been slower to adopt dyadic interaction data for predictions. Here, we explore the possibility of capitalizing on the inherently social component of collaborative learning by using…
Descriptors: Computer Mediated Communication, Trust (Psychology), Socialization, Keyboarding (Data Entry)
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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
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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
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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
Ahsan, Md. Nazmul; Emran, M. Shahe; Jiang, Hanchen; Han, Qingyang; Shilpi, Forhad – World Bank, 2023
This paper presents credible and comparable evidence on intergenerational educational mobility in 53 developing countries using sibling correlation as a measure, and data from 230 waves of Demographic and Health Surveys. It is the first paper to provide estimates of sibling correlation in schooling for a large number of developing countries using…
Descriptors: Developing Nations, Educational Mobility, Generational Differences, Siblings
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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
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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
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Hadis Anahideh; Nazanin Nezami; Abolfazl Asudeh – Grantee Submission, 2025
It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…
Descriptors: Correlation, Measurement Techniques, Guidelines, Semantics
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Penaloza, Roberto V.; Berends, Mark – Sociological Methods & Research, 2022
To measure "treatment" effects, social science researchers typically rely on nonexperimental data. In education, school and teacher effects on students are often measured through value-added models (VAMs) that are not fully understood. We propose a framework that relates to the education production function in its most flexible form and…
Descriptors: Data, Value Added Models, Error of Measurement, Correlation
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Schouten, Rianne Margaretha; Vink, Gerko – Sociological Methods & Research, 2021
Missing data in scientific research go hand in hand with assumptions about the nature of the missingness. When dealing with missing values, a set of beliefs has to be formulated about the extent to which the observed data may also hold for the missing parts of the data. It is vital that the validity of these missingness assumptions is verified,…
Descriptors: Data, Validity, Beliefs, Statistical Analysis
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