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Cosemans, Tim; Rosseel, Yves; Gelper, Sarah – Educational and Psychological Measurement, 2022
Exploratory graph analysis (EGA) is a commonly applied technique intended to help social scientists discover latent variables. Yet, the results can be influenced by the methodological decisions the researcher makes along the way. In this article, we focus on the choice regarding the number of factors to retain: We compare the performance of the…
Descriptors: Social Science Research, Research Methodology, Graphs, Factor Analysis
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Kuhnke, Janet L.; Jack-Malik, Sandra – LEARNing Landscapes, 2022
This paper showcases how a reflexive practice, that includes arts-based activities, deepened understandings experienced by a doctoral student of psychology while completing the data analysis section of a metasynthesis. The metasynthesis focused on qualitative studies, examining the mental and spiritual care of persons living with diabetic foot…
Descriptors: Reflection, Art Activities, Doctoral Students, Student Research
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Grenci, Richard T. – Decision Sciences Journal of Innovative Education, 2022
This article presents a project that uses a business context to introduce students to a multiphase approach to analytics while relying primarily on an introductory Excel course for prerequisite knowledge. A range of analytics techniques--including Excel Pivot tables and charts, regression trend lines, and linear programming--are combined into an…
Descriptors: Data Analysis, Computer Software, Business Administration Education, Decision Making
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Khajonmote, Withamon; Chinsook, Kittipong; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jansawang, Natchanok; Jantakoon, Thada – Journal of Education and Learning, 2022
The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…
Descriptors: MOOCs, Data Collection, Student Behavior, Computer Software
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Hussain, Asif; Khan, Muzammil; Ullah, Kifayat – Education and Information Technologies, 2022
Educational institutions are creating a considerable amount of data regarding students, faculty and related organs. This data is an essential asset for academic institutions as it has valuable insights, knowledge and intelligence for the policymakers. Students are the fundamental entities and primary source of data creation in any educational…
Descriptors: Data Analysis, Artificial Intelligence, Prediction, Academic Achievement
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Deeva, Galina; De Smedt, Johannes; De Weerdt, Jochen – IEEE Transactions on Learning Technologies, 2022
Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…
Descriptors: Electronic Learning, MOOCs, Dropouts, Prediction
Complete College America, 2022
"Beyond Good Intentions" provides a guide for states to craft equity-driven policies that are specific, actionable, measurable and well funded. It outlines four major steps states should take when considering and creating new policy: (1) Examine the Data to Set the Goal for the Policy: Specific types of data to consider when identifying…
Descriptors: State Policy, Educational Policy, Equal Education, Data
Matthew John Davidson – ProQuest LLC, 2022
Digitally-based assessments create opportunities for collecting moment to moment information about how students are responding to assessment items. This information, called log or process data, has long been regarded as a vast and valuable source of data about student performance. Despite repeated assurances of its vastness and value, process data…
Descriptors: Data Use, Psychometrics, Item Response Theory, Test Items
Ziqian Xu – Grantee Submission, 2022
With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…
Descriptors: Research Problems, Bayesian Statistics, Structural Equation Models, Data Analysis
Nicholas Branson – ProQuest LLC, 2022
Higher education institutions in the United States face an urgent need to use evidence of their students' outcomes to inform improvements and increase educational attainment. Data about student outcomes are abundant and professionals who interpret and report the data are commonplace today. Yet, the higher education landscape continues to be…
Descriptors: Outcomes of Education, Communications, Communication Strategies, Data
Children's Bureau, Office of the Administration for Children & Families, 2022
The National Youth in Transition Database (NYTD) snapshots offer a glimpse of National and State trends for young people who are receiving Independent Living Services through state child welfare programs. This Outcomes Data Snapshot shows statistical trends about who those young people are, their experiences and outcomes for those both in care and…
Descriptors: Late Adolescents, Transitional Programs, Foster Care, Educational Attainment
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Mustafa Polat – FIRE: Forum for International Research in Education, 2022
Education has been one of the areas most affected by the consequences of the COVID-19 pandemic since December 2019. This bibliometric review presents "the big picture" of the knowledge production on educational research conducted between January 1, 2020, and October 31, 2021. For this purpose, the current status of the related knowledge…
Descriptors: COVID-19, Pandemics, Educational Research, Knowledge Base for Teaching
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Pope, Alexis S.; Davies, Susan – Strategic Enrollment Management Quarterly, 2020
As the competition for student enrollment has increased over the past several years, the pressure on the enrollment manager has increased proportionally. Managing enrollment expectations for institutional stakeholders requires effective communication, leadership, and the sharing of data with effective context. This article provides guidance on how…
Descriptors: Enrollment Management, College Administration, Administrators, Stakeholders
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Ferreira, Giselle Martins dos Santos; Rosado, Luiz Alexandre da Silva; Lemgruber, Márcio Silveira; Carvalho, Jaciara de Sá – Learning, Media and Technology, 2020
This article discusses issues concerning the spread of data-driven educational technologies in Brazil. Here, as elsewhere, educational technology continues to be promoted optimistically as the bearer of a panacea for historically-rooted social problems. Whilst some of these technologies have indeed contributed to important widening-participation…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Innovation
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Gray, Cameron C.; Perkins, Dave; Ritsos, Panagiotis D. – Assessment & Evaluation in Higher Education, 2020
The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…
Descriptors: Educational Research, Data Collection, Data Analysis, Visual Aids
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