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David Williamson Shaffer; Yeyu Wang; Andrew Ruis – Journal of Learning Analytics, 2025
Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…
Descriptors: Learning Processes, Learning Analytics, Models, Data
Martyna Daria Swiatczak; Michael Baumgartner – Sociological Methods & Research, 2025
In this paper, we investigate the conditions under which data imbalances, a common data characteristic that occurs when factor values are unevenly distributed, are problematic for the performance of Coincidence Analysis (CNA). We further examine how such imbalances relate to fragmentation and noise in data. We show that even extreme data…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Statistical Distributions
Paul A. Jewsbury; Yue Jia; Eugenio J. Gonzalez – Large-scale Assessments in Education, 2024
Large-scale assessments are rich sources of data that can inform a diverse range of research questions related to educational policy and practice. For this reason, datasets from large-scale assessments are available to enable secondary analysts to replicate and extend published reports of assessment results. These datasets include multiple imputed…
Descriptors: Measurement, Data Analysis, Achievement, Statistical Analysis
Frank Lee; Alex Algarra – Information Systems Education Journal, 2025
This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…
Descriptors: Labor Turnover, Data Analysis, Natural Language Processing, Employees
Gülsah Kemer – Counselor Education and Supervision, 2025
Supervision models are fundamental to our supervision practices and criticized for lacking empirical support. As a data-driven approach based on research with expert supervisors, Cohesive Model of Supervision unifies existing models' central premises in a meaningful manner and emphasizes the understated areas of supervision practice.
Descriptors: Counselor Training, Supervision, Models, Data Analysis
Erica J. Powell Wrencher – Michigan Journal of Community Service Learning, 2025
This paper discusses the "how" of conducting participatory research that engages youth as participants and, more importantly, as co-researchers. In collaboration with four community co-researchers, this arts-based inquiry engaged 14 young Black people ranging in age from seven to fifteen years around their definitions of joy. Using a…
Descriptors: Participatory Research, Youth, Researchers, African Americans
Yongseok Lee; Walter L. Leite; Audrey J. Leroux – Journal of Experimental Education, 2024
In the current study, we compare propensity score (PS) matching methods for data with a cross-classified structure, where each individual is clustered within more than one group, but the groups are not hierarchically organized. Through a Monte Carlo simulation study, we compared sequential cluster matching (SCM), preferential within cluster…
Descriptors: Comparative Analysis, Data Analysis, Groups, Classification
Chen Qiu; Michael R. Peabody; Kelly D. Bradley – Measurement: Interdisciplinary Research and Perspectives, 2024
It is meaningful to create a comprehensive score to extract information from mass continuous data when they measure the same latent concept. Therefore, this study adopts the logic of psychometrics to conduct scales on continuous data under the Rasch models. This study also explores the effect of different data discretization methods on scale…
Descriptors: Models, Measurement Techniques, Benchmarking, Algorithms
Zara Ersozlu; Sona Taheri; Inge Koch – Education and Information Technologies, 2024
Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML…
Descriptors: Artificial Intelligence, Educational Research, Data Analysis, Methods
Stella Y. Kim; Sungyeun Kim – Educational Measurement: Issues and Practice, 2025
This study presents several multivariate Generalizability theory designs for analyzing automatic item-generated (AIG) based test forms. The study used real data to illustrate the analysis procedure and discuss practical considerations. We collected the data from two groups of students, each group receiving a different form generated by AIG. A…
Descriptors: Generalizability Theory, Automation, Test Items, Students
Zack J. Damon; Michael E. Ellis – Sport Management Education Journal, 2025
Sport analytics remains a growing area in the sport industry. As such, the demand for skills and knowledge in this area has grown. This demand includes off-field data, such as marketing trends, as well as financial data related to sport organizations. There has been a trickle-down effect in sport management (and other) education programs to teach…
Descriptors: Athletics, Data Collection, Data Analysis, Coding
James R. Wolf – Information Systems Education Journal, 2025
This paper introduces the LEGO® Database, a large natural dataset that can be used to teach Structured Query Language (SQL) and relational database concepts. This dataset is well-suited for introductory and advanced database assignments and end-of-semester group projects. The data is freely available from Kaggle.com and contains eight tables with…
Descriptors: Higher Education, Databases, Data Analysis, Web Sites
Megan Schwartz – MDRC, 2025
This supplement contains additional information for the report, "Support for the Journey Home: An Impact Study of the Returning Citizens Stimulus Program." The Returning Citizens Stimulus (RCS) program was a pilot program for reentry cash support and aimed to help people quickly reach stability in their lives outside of prison and reduce…
Descriptors: Institutionalized Persons, Recidivism, Financial Support, Pilot Projects
Mahmoud Abdasalam; Ahmad Alzubi; Kolawole Iyiola – Education and Information Technologies, 2025
This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…
Descriptors: Grades (Scholastic), Prediction, Accuracy, Artificial Intelligence
Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2023
Integrative data analyses have recently been shown to be an effective tool for researchers interested in synthesizing datasets from multiple studies in order to draw statistical or substantive conclusions. The actual process of integrating the different datasets depends on the availability of some common measures or items reflecting the same…
Descriptors: Data Analysis, Synthesis, Test Items, Simulation