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Peer reviewed
Direct linkShero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
Pardo-Guerra, Juan Pablo; Pahwa, Prithviraj – Sociological Methods & Research, 2022
This paper considers the adoption of computational techniques within research designs modeled after the extended case method. Echoing calls to augment the power of contemporary researchers through the adoption of computational text analysis methods, we offer a framework for thinking about how such techniques can be integrated into…
Descriptors: Case Studies, Research Design, Marketing, Social Science Research
Download full textKrumm, Andrew; Everson, Howard T.; Neisler, Julie – Journal of Learning Analytics, 2022
This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…
Descriptors: Learning Management Systems, Data Analysis, Electronic Learning, Student Behavior
Imamoglu, Mehmet; Erbas, Cagdas; Dikmen, Cemal Hakan – Online Submission, 2022
The purpose of this study was to examine the studies related to augmented reality applications in sports science and to discuss the results based on this. Articles selected for analysis were found through searches journals in the Web of Science database from 1975 to 2018 were examined and searched using the keywords ("physical education"…
Descriptors: Trend Analysis, Educational Trends, Simulated Environment, Physical Education
Ziying Li; A. Corinne Huggins-Manley; Walter L. Leite; M. David Miller; Eric A. Wright – Educational and Psychological Measurement, 2022
The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…
Descriptors: Sequential Approach, Item Response Theory, Data, Simulation
Li Feng; Eleanor W. Close; Cynthia J. Luxford; Jiwoo An Pierson; Alice Olmstead; Jieon Shim; Venkata Sowjanya Koka; Heather C. Galloway – Research in Higher Education, 2025
Evidence-based and student-centered instructional methods hold the promise of transforming undergraduate STEM education and simultaneously solving the dual challenge of STEM workforce needs and inequities within STEM. The Learning Assistant (LA) Model was created to reform curriculum, recruit teachers, and inform discipline-based education…
Descriptors: STEM Education, School Holding Power, Graduation Rate, Data Analysis
Crystal Villa; Rikki Marzan – International Journal of Education in Mathematics, Science and Technology, 2025
To address the disconnect and bridge the gap between mathematics and science education, we developed interdisciplinary lessons and real-world applications by integrating Algebra 1 and Biology in a collaborative cohort model. We aim to improve student engagement, knowledge transfer, and performance on assessments in both disciplines. The…
Descriptors: Mathematics Education, Science Education, Interdisciplinary Approach, Algebra
Melody W. Young; Noah D. Chernik; Stratos J. Kantounis; Matthew J. Cannata; James Q. Virga; Reuben N. Jacobson; Jon A. Gustafson; Aleksandra S. Ratkiewicz; Enkhjin Batbayar; Badamkhand Monhochir; Binderiya Munkhbat; Minjin Bolortsetseg; Carol Weintraub; Stan Silverman; Gabby Guilhon; Edwin Dickinson; Michael C. Granatosky – Anatomical Sciences Education, 2025
Access to high-quality outreach programs is crucial for preparing students for STEM careers, yet traditional classrooms often lack diverse, hands-on learning opportunities, particularly in anatomy and evolutionary biology. We present "Are You Stronger Than a Lemur?"--an interactive STEM activity that introduces K-12 students to…
Descriptors: STEM Education, Outreach Programs, Anatomy, Biomechanics
Bakhshinategh, Behdad; Zaiane, Osmar R.; ElAtia, Samira; Ipperciel, Donald – Education and Information Technologies, 2018
Educational Data Mining (EDM) is the field of using data mining techniques in educational environments. There exist various methods and applications in EDM which can follow both applied research objectives such as improving and enhancing learning quality, as well as pure research objectives, which tend to improve our understanding of the learning…
Descriptors: Educational Environment, Surveys, Comparative Analysis, Data Analysis
Ioannou, Marios – Mathematics Education Research Journal, 2018
This study analyses learning aspects of undergraduate mathematics students' first encounter with the subgroup test, using the commognitive theoretical framework. It focuses on students' difficulties as these are related to the object-level and metalevel mathematical learning in group theory, and, when possible, highlights any commognitive…
Descriptors: Undergraduate Students, Mathematics Instruction, Models, Data Analysis
Scott, Marcus W. – ProQuest LLC, 2018
One way that examinees can gain an unfair advantage on a test is by having prior access to the test questions and their answers, known as preknowledge. Determining which examinees had preknowledge can be a difficult task. Sometimes, the compromised test content that examinees use to get preknowledge has mistakes in the answer key. Examinees who…
Descriptors: Cheating, Answer Keys, Tests, Identification
Savi, Alexander O.; Deonovic, Benjamin E.; Bolsinova, Maria; van der Maas, Han L. J.; Maris, Gunter K. J. – Journal of Educational Data Mining, 2021
In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…
Descriptors: Learning Processes, Cognitive Processes, Error Patterns, Models
Decuypere, Mathias; Landri, Paolo – Critical Studies in Education, 2021
University rankings have become commonplace in higher education. Traditional quantified rankings do not merely measure educational performance: they equally grant status, enforce competition between institutions, and are emblematic for the ongoing capitalization of higher education. Drawing on the field of Science and Technology Studies, this…
Descriptors: Universities, Institutional Evaluation, Educational Quality, Institutional Characteristics
Bridges, Eileen – Journal of Marketing Education, 2021
This article looks back over the past two decades to describe how teaching of undergraduate marketing research has (or has not) changed. Sweeping changes in technology and society have certainly affected how marketing research is designed and implemented--but how has this affected teaching of this important topic? Although the purpose of marketing…
Descriptors: Marketing, Undergraduate Students, Educational Change, Teaching Methods
McFadden, Rory R.; Viskupic, Karen; Egger, Anne E. – Journal of Geoscience Education, 2021
Quantitative literacy is a foundational component of success in STEM disciplines and in life. Quantitative concepts and data-rich activities in undergraduate geoscience courses can strengthen geoscience majors' understanding of geologic phenomena and prepare them for future careers and graduate school, and provide real-world context to apply…
Descriptors: Earth Science, College Science, College Faculty, Mathematics Skills
