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Christopher M. Loan – ProQuest LLC, 2024
Simulations were conducted to establish best practice in hyperparameter optimization and accounting for clustering in Generalized Linear Mixed-Effects Model Trees (GLMM trees). Using data-driven best practices, the relationship between a 9th Grade On-Track to Graduate (9G-OTG) indicator and observed high school graduation within four years was…
Descriptors: Data Analysis, Simulation, Longitudinal Studies, Hierarchical Linear Modeling
Kyle T. Turner; George Engelhard Jr. – Journal of Experimental Education, 2024
The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…
Descriptors: Data Analysis, Multivariate Analysis, Individual Characteristics, Behavior
Kaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Large-scale Assessments in Education, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
David Kaplan; Jianshen Chen; Weicong Lyu; Sinan Yavuz – Grantee Submission, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
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
Brandin Conrath; Amy Voss Farris; Scott McDonald – Journal of Science Education and Technology, 2025
The changing landscape of geoscience learning has initiated growing interest in engaging science learners with climate data. One approach to teaching climate is the application of broadly accessible digital science curricula, which often include data tools such as visualizations, data representations, and simulations embedded within digital…
Descriptors: Earth Science, Wildlife, Science Education, Climate
Dvir, Michal; Ben-Zvi, Dani – British Journal of Educational Technology, 2022
In today's information age, developing data science competencies has become vital to fostering responsible citizenry. However, the actual techniques learners need to become proficient in are still somewhat "in-construction", as the relatively new field of data science is constantly expanding to meet new data-related demands. Data science…
Descriptors: Middle School Students, Data, Data Analysis, Interdisciplinary Approach
Cui, Ying; Guo, Qi; Leighton, Jacqueline P.; Chu, Man-Wai – International Journal of Testing, 2020
This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…
Descriptors: Inferences, Artificial Intelligence, Data Analysis, Computer Assisted Testing
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
Large-scale assessments (LSAs) use Mislevy's "plausible value" (PV) approach to relate student proficiency to noncognitive variables administered in a background questionnaire. This method requires background variables to be completely observed, a requirement that is seldom fulfilled. In this article, we evaluate and compare the…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Statistical Inference
Teig, Nani; Scherer, Ronny; Kjaernsli, Marit – Journal of Research in Science Teaching, 2020
Previous research has demonstrated the potential of examining log-file data from computer-based assessments to understand student interactions with complex inquiry tasks. Rather than solely providing information about what has been achieved or the accuracy of student responses ("product data"), students' log files offer additional…
Descriptors: Science Process Skills, Thinking Skills, Inquiry, Simulation
Marks, Peter E. L.; Babcock, Ben; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N. – International Journal of Behavioral Development, 2019
In peer nomination research, individuals who do not provide nominations (nonparticipants) are often included on rosters as potential nominees. This can present ethical questions regarding informed consent, but psychometric consequences of excluding nonparticipants from rosters are unknown. In this investigation, Study 1 simulated both random and…
Descriptors: Peer Groups, Adolescents, Grade 7, Grade 8
Sole, Marla A. – Mathematics Teacher, 2015
Every day, people use data to make decisions that affect their personal and professional lives, trusting that the data are correct. Many times, however, the data are inaccurate, as a result of a flaw in the design or methodology of the survey used to collect the data. Researchers agree that only questions that are clearly worded, unambiguous, free…
Descriptors: Test Construction, Surveys, Student Participation, Design
Rantala, Jukka; Manninen, Marika; van den Berg, Marko – Journal of Curriculum Studies, 2016
In 2011, the Finnish National Board of Education assessed the learning outcomes of history with a study whose results raised doubts about the fulfilment of the goals of history education. This article seeks to expand awareness about Finnish adolescents' understanding of historical empathy. The study assessed twenty-two 16-17-year-old high school…
Descriptors: Foreign Countries, High School Students, Adolescents, Empathy
Babcock, Steven L.; Warny, Sophie – Science Activities: Classroom Projects and Curriculum Ideas, 2014
This activity introduces the science of "forensic palynology": the use of microscopic pollen and spores (also called "palynomorphs") to solve criminal cases. Plants produce large amounts of pollen or spores during reproductive cycles. Because of their chemical resistance, small size, and morphology, pollen and spores can be…
Descriptors: Science Instruction, Science Activities, Crime, Plants (Botany)