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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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Seide, Svenja E.; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2020
The performance of statistical methods is often evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, simulations are not currently available for many practically relevant settings. We perform a simulation study for sparse networks of trials under between-trial heterogeneity and including multi-arm…
Descriptors: Bayesian Statistics, Meta Analysis, Data Analysis, Networks
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Taylor, Z. W. – Strategic Enrollment Management Quarterly, 2020
This study sought to understand the relationship between undergraduate yield and an institution's internet presence. Data were collected from 2018 "U.S. News & World Report" national university rankings, the Integrated Postsecondary Education Database (IPEDS), and summer 2018 (June-August) SEMrush data, a web metrics database housing…
Descriptors: Higher Education, College Bound Students, Student Motivation, Search Engines
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Jiang, Weijie; Pardos, Zachary A. – International Educational Data Mining Society, 2020
Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…
Descriptors: Course Descriptions, Models, Prediction, Course Selection (Students)
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Hunt-Isaak, Noah; Cherniavsky, Peter; Snyder, Mark; Rangwala, Huzefa – International Educational Data Mining Society, 2020
National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…
Descriptors: Textbooks, Surveys, Grade Prediction, Undergraduate Students
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Zehner, Fabian; Harrison, Scott; Eichmann, Beate; Deribo, Tobias; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – International Educational Data Mining Society, 2020
The "2nd Annual WPI-UMASS-UPENN EDM Data Mining Challenge" required contestants to predict efficient testtaking based on log data. In this paper, we describe our theory-driven and psychometric modeling approach. For feature engineering, we employed the Log-Normal Response Time Model for estimating latent person speed, and the Generalized…
Descriptors: Data Analysis, Competition, Classification, Prediction
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Sarah R. Morris; Sarah C. McKenzie; Miranda G. Vernon – Journal of Advanced Academics, 2025
This robust mixed-methods study examines ninth-grade advanced course placement in Arkansas, revealing disparities rooted in race and socioeconomic status. Utilizing a logit analysis for a five-year pooled sample (n = 163,616), we find persistent enrollment gaps for Black ninth-grade students after controlling for prior academic achievement,…
Descriptors: High School Students, Grade 9, Advanced Courses, Socioeconomic Status
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Hill, Stephen; Scott, Rebecca – Information Systems Education Journal, 2017
Using data from social media can be of great value to businesses and other interested parties. However, harvesting data from social media networks such as Twitter, cleaning the data, and analyzing the data can be difficult. In this article, a step-by-step approach to obtaining data via the Twitter application program interface (API) is described.…
Descriptors: Data Analysis, Data Collection, Social Media
Washington Student Achievement Council, 2023
The dataset used in this report was created by combining Bridge to Finish intervention records, provided by the United Way of King County (UWKC), with student information provided by the State Board for Community and Technical Colleges (SBCTC). The intervention records span the terms from summer 2018 through fall 2021. SBCTC data include these…
Descriptors: Higher Education, College Programs, Community Colleges, Technical Institutes
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Song, Yi; Zhu, Mengxiao; Sparks, Jesse R. – Journal of Educational Computing Research, 2023
In this research, we use a process data analysis approach to gather additional evidence about students' argumentation skills beyond their performance scores in a computer-based assessment. This game-enhanced scenario-based assessment (named Seaball) included five activities that require students to demonstrate their argumentation skills within a…
Descriptors: Data Analysis, Academic Achievement, Interaction, Performance
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Kosztyán, Zsolt Tibor; Csizmadia, Tibor; Pató, Beáta Sz.G.; Berke, Szilárd; Neumanné-Virág, Ildiko; Bencsik, Andrea – Cogent Education, 2023
The measurement of organizational satisfaction is a popular topic in organizational science; however, less attention is given to organizational happiness. There are very few measuring tools designed to evaluate organizational happiness. While the value-mediating role of higher education is indisputable, to the best of our knowledge, this is the…
Descriptors: Organizational Climate, Data Analysis, Higher Education, Foreign Countries
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Brunner, Martin; Keller, Lena; Stallasch, Sophie E.; Kretschmann, Julia; Hasl, Andrea; Preckel, Franzis; Lüdtke, Oliver; Hedges, Larry V. – Research Synthesis Methods, 2023
Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…
Descriptors: Meta Analysis, Surveys, Research Design, Educational Research
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Calvera-Isabal, Miriam; Santos, Patricia; Hoppe, H. -Ulrich; Schulten, Cleo – Comunicar: Media Education Research Journal, 2023
There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to…
Descriptors: Citizen Participation, Science and Society, Scientific and Technical Information, Web Sites
Sauder, Adrienne E.; Gilson, Cindy M. – Gifted Child Quarterly, 2023
There is a growing body of literature around digital research, specifically regarding data collection and how to pivot research designs to be more conducive to online and virtual research, but little in the way of how to analyze data remotely. In this article, we share firsthand experiences from a qualitative study utilizing Google apps, Zoom, and…
Descriptors: Academically Gifted, Gifted Education, Qualitative Research, Data Collection
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Çebi, Ayça; Araújo, Rafael D.; Brusilovsky, Peter – Journal of Research on Technology in Education, 2023
Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…
Descriptors: Individual Characteristics, Electronic Learning, Student Behavior, Learning Management Systems
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