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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
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
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
Matayoshi, Jeffrey; Karumbaiah, Shamya – International Educational Data Mining Society, 2021
Research studies in Educational Data Mining (EDM) often involve several variables related to student learning activities. As such, it may be necessary to run multiple statistical tests simultaneously, thereby leading to the problem of multiple comparisons. The Benjamini-Hochberg (BH) procedure is commonly used in EDM research to address this…
Descriptors: Statistical Analysis, Validity, Classification, Hypothesis Testing
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 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
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
Lit Hong Lee – International Journal on E-Learning, 2025
This study investigates the effectiveness of a modified flipped classroom that integrated with a technology-enhanced Predict-Observe-Explain strategy to improve students' self-regulated learning abilities, learning performance and science process skills in a secondary school in Hong Kong. An experimental group of modified flipped classroom (n =…
Descriptors: Independent Study, Academic Achievement, Science Process Skills, Flipped Classroom
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
Mohammed Daoudi – Discover Education, 2025
This study provides a comprehensive analysis of researchers' perspectives on AI integration across theoretical and practical research, academic publishing, and its future role, highlighting ethical considerations shaping its adoption. The methodology used a mixed approach, using a questionnaire distributed to researchers from various scientific…
Descriptors: Ethics, Artificial Intelligence, Technology Uses in Education, Scientific Research
Wong, Wing-Kwong; Chao, Tsung-Kai; Chang, Ching-Lung; Chen, Kai-Ping – International Journal of Distance Education Technologies, 2019
There has been an ongoing debate of which physical labs or virtual labs are better. To resolve this issue, a remote lab provides an online lab that can do real experiments to obtain real data from a distant physical lab. Instead of relying on a remote lab, this article suggests that students collect experimental data locally with low-cost data…
Descriptors: Foreign Countries, Science Laboratories, Data Analysis, Scaffolding (Teaching Technique)
Held, Leonhard; Matthews, Robert; Ott, Manuela; Pawel, Samuel – Research Synthesis Methods, 2022
It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…
Descriptors: Bayesian Statistics, Statistical Inference, Hypothesis Testing, Credibility
Bollig, Michael; Schnegg, Michael; Schwieger, Diego A. Menestrey – Field Methods, 2020
This article introduces ethnographic upscaling, an innovative procedure to explore and test hypotheses drawn from in-depth ethnographic findings in spatially continuous cases. The approach combines the strength of localized ethnographic descriptions with questionnaire-based regional surveys to study the distribution of ethnographic findings across…
Descriptors: Ethnography, Anthropology, Research Methodology, Hypothesis Testing
Wilson, Cristina G.; Qian, Feifei; Jerolmack, Douglas J.; Roberts, Sonia; Ham, Jonathan; Koditschek, Daniel; Shipley, Thomas F. – Cognitive Research: Principles and Implications, 2021
How do scientists generate and weight candidate queries for hypothesis testing, and how does learning from observations or experimental data impact query selection? Field sciences offer a compelling context to ask these questions because query selection and adaptation involves consideration of the spatiotemporal arrangement of data, and therefore…
Descriptors: Hypothesis Testing, Data Collection, Information Seeking, Decision Making
Kuang, Xiulin; Eysink, Tessa H. S.; de Jong, Ton – Journal of Computer Assisted Learning, 2020
Hypothesis generation is an important but difficult process for students. This study investigated the effects of providing students with support for hypothesis generation, with regard to the testability and complexity of the generated hypotheses, the quality of the subsequent inquiry learning processes and knowledge acquisition. Fifty-two…
Descriptors: Hypothesis Testing, Simulation, Inquiry, Active Learning
Thompson, W. Burt – Teaching of Psychology, 2019
When a psychologist announces a new research finding, it is often based on a rejected null hypothesis. However, if that hypothesis is true, the claim is a false alarm. Many students mistakenly believe that the probability of committing a false alarm equals alpha, the criterion for statistical significance, which is typically set at 5%. Instructors…
Descriptors: Statistical Analysis, Hypothesis Testing, Misconceptions, Data Interpretation

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