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Direct linkGregory 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
Beechey, Timothy – Journal of Speech, Language, and Hearing Research, 2023
Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…
Descriptors: Hypothesis Testing, Multivariate Analysis, Data Analysis, Statistical Inference
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Download full textMcCarthy, Richard V.; Ceccucci, Wendy; McCarthy, Mary; Sugurmar, Nirmalkumar – Information Systems Education Journal, 2021
This case is designed to be used in business analytics courses; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People's United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize…
Descriptors: Business Administration Education, Data Analysis, Prediction, Crime
Exploring Core Ideas of Procedural Understanding in Scientific Inquiry Using Educational Data Mining
Arnold, Julia C.; Mühling, Andreas; Kremer, Kerstin – Research in Science & Technological Education, 2023
Background: Scientific thinking is an essential learning goal of science education and it can be fostered by inquiry learning. One important prerequisite for scientific thinking is procedural understanding. Procedural understanding is the knowledge about specific steps in scientific inquiry (e.g. formulating hypotheses, measuring dependent and…
Descriptors: Science Process Skills, Inquiry, Active Learning, Science Education
Haynes-Brown, Tashane K. – Journal of Mixed Methods Research, 2023
The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the…
Descriptors: Theories, Models, Mixed Methods Research, Teacher Attitudes
Kubsch, Marcus; Stamer, Insa; Steiner, Mara; Neumann, Knut; Parchmann, Ilka – Practical Assessment, Research & Evaluation, 2021
In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community…
Descriptors: Data Analysis, Bayesian Statistics, Educational Research, Science Education
Yu, Chong Ho; Lee, Hyun Seo; Lara, Emily; Gan, Siyan – Practical Assessment, Research & Evaluation, 2018
Big data analytics are prevalent in fields like business, engineering, public health, and the physical sciences, but social scientists are slower than their peers in other fields in adopting this new methodology. One major reason for this is that traditional statistical procedures are typically not suitable for the analysis of large and complex…
Descriptors: Data Analysis, Social Sciences, Social Science Research, Models
Wiens, Stefan; Nilsson, Mats E. – Educational and Psychological Measurement, 2017
Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful…
Descriptors: Data Analysis, Effect Size, Computation, Statistical Analysis
Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Grice, James W.; Yepez, Maria; Wilson, Nicole L.; Shoda, Yuichi – Educational and Psychological Measurement, 2017
An alternative to null hypothesis significance testing is presented and discussed. This approach, referred to as observation-oriented modeling, is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. In terms of analysis, this novel approach complements traditional methods…
Descriptors: Hypothesis Testing, Models, Observation, Statistical Inference
Blaine, Bruce Evan – Scholarship and Practice of Undergraduate Research, 2019
Reproducibility crises have arisen in psychology and other behavioral sciences, spurring efforts to ensure research findings are credible and replicable. Although reforms are occurring at professional levels in terms of new publication parameters and open science initiatives, the credibility and reproducibility of undergraduate research deserves…
Descriptors: Undergraduate Students, Student Research, Behavioral Science Research, Research Methodology
Gardner, Josh; Brooks, Christopher – Journal of Learning Analytics, 2018
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…
Descriptors: Prediction, Models, Evaluation, Evaluation Methods
Erin C. Yang; Robby Divine; Christine S. Kang; Sidney Chan; Elijah Arenas; Zoe Subol; Peter Tinker; Hayden Manninen; Alicia Feichtenbiner; Talal Mustafa; Julia Hallowell; Isiac Orr; Hugh Haddox; Brian Koepnick; Jacob O'Connor; Ian C. Haydon; Karla-Luise Herpoldt; Kandise Van Wormer; Celine Abell; David Baker; Alena Khmelinskaia; Neil P. King – Journal of Chemical Education, 2022
Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work-study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and…
Descriptors: Undergraduate Students, Teaching Methods, COVID-19, Pandemics
Grinshpun, Vadim – International Journal of Environmental and Science Education, 2016
Importance: The article raises a point of visual representation of big data, recently considered to be demanded for many scientific and real-life applications, and analyzes particulars for visualization of multi-dimensional data, giving examples of the visual analytics-related problems. Objectives: The purpose of this paper is to study application…
Descriptors: Data Analysis, Visualization, Graphs, Charts
