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Su, Hsu-Lin; Chen, Po-Hsi – Educational and Psychological Measurement, 2023
The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant's factor pattern. Thus, in this study, we proposed three analysis procedures…
Descriptors: Data Analysis, Correlation, Classification, Factor Structure
Vahid Roshanaei; Bahman Naderi; Opher Baron; Dmitry Krass – INFORMS Transactions on Education, 2024
We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…
Descriptors: Spreadsheets, Interaction, Classification, Computation
Maxi Schulz; Malte Kramer; Oliver Kuss; Tim Mathes – Research Synthesis Methods, 2024
In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…
Descriptors: Meta Analysis, Data Analysis, Research Methodology, Research Problems
David Bruns-Smith; Oliver Dukes; Avi Feller; Elizabeth L. Ogburn – Grantee Submission, 2024
We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular "doubly robust" or "de-biased machine learning estimators" combine outcome modeling with balancing weights -- weights that achieve covariate balance directly in lieu of estimating and…
Descriptors: Regression (Statistics), Weighted Scores, Data Analysis, Robustness (Statistics)
Michael DeBuse; Dallin Clayton; Brooks Butler; Sean Warnick – International Journal of Artificial Intelligence in Education, 2024
This work considers group discussion data, as recorded in video conferencing settings, and demonstrates the ability to use readily available computational tools to glean important information characterizing the dynamics of the group discussion. In particular, our toolbox reveals a number of important characteristics of a discussion, including who…
Descriptors: Discussion (Teaching Technique), Discussion Groups, Group Dynamics, Group Discussion
Salomé Do; Étienne Ollion; Rubing Shen – Sociological Methods & Research, 2024
The last decade witnessed a spectacular rise in the volume of available textual data. With this new abundance came the question of how to analyze it. In the social sciences, scholars mostly resorted to two well-established approaches, human annotation on sampled data on the one hand (either performed by the researcher, or outsourced to…
Descriptors: Computation, Social Sciences, Natural Language Processing, Artificial Intelligence
Jiang, Shiyan; Qian, Yingxiao; Tang, Hengtao; Yalcinkaya, Rabia; Rosé, Carolyn P.; Chao, Jie; Finzer, William – Education and Information Technologies, 2023
As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Artificial Intelligence
El Kadiri Boutchich, Driss – Journal of Education, 2023
This work aims to elaborate a governance composite index for research laboratories in public university. This index is composed by an indicator of responsible liberalism associating effectiveness and ethics, to which are added an organizational management indicator and a strategic management indicator. To achieve the above aim, several methods are…
Descriptors: Educational Research, Laboratories, Governance, Universities
Savaiano, Mackenzie E.; Shanahan Bazis, Pamela; Hebert, Michael; Rodgers, Derek B.; Bosilevac, Madison; Leutzinger, Bridget; Thompson, Madison – Journal of Visual Impairment & Blindness, 2022
Introduction and Methods: We do not have an accurate count of the number of teachers of students with visual impairments working in the field, and it is a difficult number to estimate. As part of a national survey, states were contacted to estimate how many teachers of students with visual impairments are working in the United States and compared…
Descriptors: Visual Impairments, Computation, Data Analysis, Students
S. Mabungane; S. Ramroop; H. Mwambi – African Journal of Research in Mathematics, Science and Technology Education, 2023
The issue of missing data raises concerns in all statistical and educational research. In this study, we focus on missing data in school-based assessment data generated by progressed high school learners (those who did not meet the promotional requirements for their current grades but were allowed to move to the next grade because of policy…
Descriptors: Data Analysis, Research Problems, High School Students, Student Promotion
Marcoulides, Katerina M. – International Journal of Behavioral Development, 2021
The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is…
Descriptors: Growth Models, Computation, Mathematics, Longitudinal Studies
Turner, Simon Lee; Korevaar, Elizabeth; Cumpston, Miranda S.; Kanukula, Raju; Forbes, Andrew B.; McKenzie, Joanne E. – Research Synthesis Methods, 2023
Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis. While publications of ITS rarely provide…
Descriptors: Quasiexperimental Design, Graphs, Accuracy, Computation
Yong-Woon Choi; In-gyu Go; Yeong-Jae Gil – International Journal of Technology and Design Education, 2024
The purpose of this study is to derive a correlation between the technological thinking disposition and the computational thinking ability of gifted students in Korea. The correlation between each element was analyzed by looking at the sub-elements of computational thinking according to the components of technological thinking disposition. The…
Descriptors: Thinking Skills, Mental Computation, Gifted, Correlation
Cross-Classified Item Response Theory Modeling with an Application to Student Evaluation of Teaching
Sijia Huang; Li Cai – Journal of Educational and Behavioral Statistics, 2024
The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…
Descriptors: Classification, Data Collection, Data Analysis, Item Response Theory
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