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Karen L. Webber; Henry Y. Zheng – New Directions for Higher Education, 2024
Recently, the rise of generative AI tools such as "ChatGPT" have prompted deep and wide considerations about teaching and learning, student success, research and development, and the use of data for informed institutional decision making. In this volume, authors discuss specific concepts, considerations for use, and some specific tools…
Descriptors: Artificial Intelligence, Data Analysis, Higher Education
Francis Huang; Brian Keller – Large-scale Assessments in Education, 2025
Missing data are common with large scale assessments (LSAs). A typical approach to handling missing data with LSAs is the use of listwise deletion, despite decades of research showing that approach can be a suboptimal strategy resulting in biased estimates. In order to help researchers account for missing data, we provide a tutorial using R and…
Descriptors: Research Problems, Data Analysis, Statistical Bias, International Assessment
Sandip Sinharay; Randy E. Bennett; Michael Kane; Jesse R. Sparks – Journal of Educational Measurement, 2025
Personalized assessments are of increasing interest because of their potential to lead to more equitable decisions about the examinees. However, one obstacle to the widespread use of personalized assessments is the lack of a measurement toolkit that can be used to analyze data from these assessments. This article takes one step toward building…
Descriptors: Test Validity, Data Analysis, Advanced Placement Programs, Art
Axel Langner; Lea Sophie Hain; Nicole Graulich – Journal of Chemical Education, 2025
Often, eye-tracking researchers define areas of interest (AOIs) to analyze eye-tracking data. Although AOIs can be defined with systematic methods, researchers in organic chemistry education eye-tracking research often define them manually, as the semantic composition of the stimulus must be considered. Still, defining appropriate AOIs during data…
Descriptors: Organic Chemistry, Science Education, Eye Movements, Educational Research
Giora Alexandron; Aviram Berg; Jose A. Ruiperez-Valiente – IEEE Transactions on Learning Technologies, 2024
This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…
Descriptors: Cheating, Identification, Online Courses, Artificial Intelligence
Lee A. Coppock – Journal of Economic Education, 2025
The COVID-19 pandemic uniquely affected nearly all the subject matter in a typical principles of macroeconomics class. Fluctuations in the basic macroeconomic data in the COVID era were staggering and offer new teaching opportunities. In addition, because the recession was primarily driven by supply side shocks, the entire episode offers a unique…
Descriptors: Macroeconomics, COVID-19, Pandemics, Teaching Methods
Victoria Reyes; Elizabeth Bogumil; Levin Elias Welch – Sociological Methods & Research, 2024
Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we've collected. Although there are a few exceptions, less focus is on transparency regarding…
Descriptors: Qualitative Research, Data Analysis, Guides, Databases
Fernando Rios-Avila; Michelle Lee Maroto – Sociological Methods & Research, 2024
Quantile regression (QR) provides an alternative to linear regression (LR) that allows for the estimation of relationships across the distribution of an outcome. However, as highlighted in recent research on the motherhood penalty across the wage distribution, different procedures for conditional and unconditional quantile regression (CQR, UQR)…
Descriptors: Regression (Statistics), Research Methodology, Alternative Assessment, Models
Tina Law; Elizabeth Roberto – Sociological Methods & Research, 2025
Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of…
Descriptors: Artificial Intelligence, Visual Aids, Open Source Technology, Social Science Research
Edoardo Saccenti – Teaching Statistics: An International Journal for Teachers, 2024
Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions…
Descriptors: Factor Analysis, Data Analysis, Information Literacy, Visualization
Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
Ioana-Elena Oana; Carsten Q. Schneider – Sociological Methods & Research, 2024
The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…
Descriptors: Robustness (Statistics), Qualitative Research, Comparative Analysis, Decision Making
Jie Fang; Zhonglin Wen; Kit-Tai Hau – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…
Descriptors: Structural Equation Models, Mediation Theory, Data Analysis, Longitudinal Studies
Siobhan Reilley – Impacting Education: Journal on Transforming Professional Practice, 2024
The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…
Descriptors: Data Use, Data Collection, Data Analysis, Teacher Leadership
Representing DNA for Machine Learning Algorithms: A Primer on One-Hot, Binary, and Integer Encodings
Yash Munnalal Gupta; Satwika Nindya Kirana; Somjit Homchan – Biochemistry and Molecular Biology Education, 2025
This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…
Descriptors: Science Instruction, Teaching Methods, Genetics, Molecular Biology