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Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Endler Marcel Borges – Journal of Chemical Education, 2023
An understanding of statistical concepts is necessary for a chemist with a complete education. Here, statistical tests were taught using the R Commander and the Factoshiny packages. These packages run on R software and have a graphical user interface (GUI), which allows students to do statistical tests quickly and easily. These packages were…
Descriptors: Statistics Education, Programming Languages, Chemistry, Science Instruction
Abdullah Alamer; Florian Schuberth; Jörg Henseler – Studies in Second Language Acquisition, 2024
Researchers in second language (L2) and education domain use different statistical methods to assess their constructs of interest. Many L2 constructs emerge from elements/parts, i.e., the elements "define" and "form" the construct and not the other way around. These constructs are referred to as emergent variables (also called…
Descriptors: Factor Analysis, Factor Structure, Second Language Learning, Language Research
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
Guler, Gul; Cikrikci, Rahime Nukhet – International Journal of Assessment Tools in Education, 2022
The purpose of this study was to investigate the Type I Error findings and power rates of the methods used to determine dimensionality in unidimensional and bidimensional psychological constructs for various conditions (characteristic of the distribution, sample size, length of the test, and interdimensional correlation) and to examine the joint…
Descriptors: Comparative Analysis, Error of Measurement, Decision Making, Factor Analysis
PaaBen, Benjamin; Dywel, Malwina; Fleckenstein, Melanie; Pinkwart, Niels – International Educational Data Mining Society, 2022
Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…
Descriptors: Item Response Theory, Test Items, Item Analysis, Inferences
Maher, Carolyn; Schazmann, Benjamin; Gornushkin, Igor B.; Rurack, Knut; Gojani, Ardian B. – Journal of Chemical Education, 2021
Laser-induced breakdown spectroscopy (LIBS) and principal component analysis (PCA) are frequently used for analytical purposes in research and industry, but they seldom are part of the chemistry curriculum or laboratory exercises. This case study paper describes the combined application of LIBS and PCA during a research internship for an…
Descriptors: Factor Analysis, Case Studies, Internship Programs, Undergraduate Students
Merz, G. Russell; Ward, Jamie; Qrunfleh, Sufian; Gibson, Bud – Higher Education, Skills and Work-based Learning, 2022
Purpose: The purpose of this paper is to describe the role and characteristics of the summer internship program (Digital Summer Clinic) delivered by Eastern Michigan University. The authors report the results of an exploratory study of interns participating in the Digital Summer Clinic over a five-year time period. The study captures and analyzes…
Descriptors: Marketing, Internship Programs, Natural Language Processing, Computer Software
Çevik, Mustafa; Tabaru-Örnek, Gizem – International Online Journal of Education and Teaching, 2020
In this study, it was aimed to compare the predictions of the academic achievement of the artificial neural networks (ANN) run in MATLAB and SPSS software and to determine the factors related to their academic achievement. Sample consisted of 465 students who were studying at Grade 4 in primary schools in the Central Anatolian Region of Turkey in…
Descriptors: Comparative Analysis, Academic Achievement, Computer Software, Prediction
Malmberg, Lars-Erik – International Journal of Research & Method in Education, 2020
With a growing interest in research on educational processes, there is a need to overview suitable latent variable models for students' learning experiences in real-time. This tutorial provides an introduction to intraindividual (multilevel) structural equation models (ISEM) for the analysis of process data (e.g. intensive longitudinal,…
Descriptors: Structural Equation Models, Learning Experience, Educational Research, Personal Autonomy
Sidou, Lais Feltrin; Borges, Endler Marcel – Journal of Chemical Education, 2020
Principal component analysis (PCA) is one of the most important and powerful methods in chemometrics as well as in a wealth of other areas. Running a PCA results in two main elements, the score plot and the loading plot; the score plot provides the location of the samples, and the loading plot indicates correlations among variables, the trends in…
Descriptors: Factor Analysis, Chemistry, Science Instruction, Teaching Methods
Yüksel, H. Gülru; Mercanoglu, H. Güldem; Yilmaz, M. Betül – Computer Assisted Language Learning, 2022
Growing research suggests that digital flashcards may facilitate students' technical vocabulary learning efforts. The primary purpose of this quasi-experimental study was to compare the effect of digital flashcards (DFs) and wordlists on learning technical vocabulary as well as to explore students' perceptions regarding the use of DFs. Using…
Descriptors: Educational Technology, Language Tests, Vocabulary Development, Comparative Analysis
Demir Kaymak, Zeliha; Akgün, Özcan Erkan – Malaysian Online Journal of Educational Technology, 2019
The purpose of this research is to investigate the effects of using cloud computing technologies, study type and task difficulty on cognitive load and students' performance. The research was conducted as 2x2x2 complex mixed design. The two experiment groups are the first factor of design. In the first experiment group students used non…
Descriptors: Cognitive Ability, Computer Software, Task Analysis, Difficulty Level
Baglin, James – Practical Assessment, Research & Evaluation, 2014
Exploratory factor analysis (EFA) methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many…
Descriptors: Factor Analysis, Data, Likert Scales, Computer Software
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