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Tanja Kovacic; Cormac Forkan – Irish Educational Studies, 2024
Young people who are either at risk of disengaging or disengaged from mainstream education in Ireland are often supported by what is termed 'out-of-school' or the 'alternative education' sector. A recent review of out-of-school education provision (Department of Education. 2022. "Review of Out-of-School Educational Provision." Dublin:…
Descriptors: Foreign Countries, Nontraditional Education, Inclusion, Mainstreaming
Luo, Wen; Li, Haoran; Baek, Eunkyeng; Chen, Siqi; Lam, Kwok Hap; Semma, Brandie – Review of Educational Research, 2021
Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…
Descriptors: Hierarchical Linear Modeling, Multivariate Analysis, Prediction, Research Problems
Peterson, Anna D.; Ziegler, Laura – Journal of Statistics and Data Science Education, 2021
We present an innovative activity that uses data about LEGO sets to help students self-discover multiple linear regressions. Students are guided to predict the price of a LEGO set posted on Amazon.com (Amazon price) using LEGO characteristics such as the number of pieces, the theme (i.e., product line), and the general size of the pieces. By…
Descriptors: Toys, Statistics Education, Teaching Methods, Regression (Statistics)
Luke Keele; Matthew Lenard; Lindsay Page – Annenberg Institute for School Reform at Brown University, 2021
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Cluster Grouping, Educational Environment, Outcomes of Treatment, Compliance (Psychology)
Valero-Mora, Pedro; Rodrigo, María F.; Sanchez, Mar; SanMartin, Jaime – Practical Assessment, Research & Evaluation, 2019
Missing data patterns are the combinations in which the variables with missing values occur. Exploring these patterns in multivariate data can be very useful but there are few specialized tools. The current paper presents a plot that includes relevant information for visualizing these patterns. The plot is also dynamic-interactive; so, selecting…
Descriptors: Data, Multivariate Analysis, Visual Aids, Statistical Analysis
Entwistle, Noel – Psychology of Education Review, 2019
In considering the contribution of educational psychology to an understanding of student learning, Noel Entwistle suggests the need to start by deciding the purpose of research in this field, and then consider the contributions already made, and what might be the way forward. Looking at the approaches to research used in exploring student learning…
Descriptors: Educational Psychology, Educational Research, Educational History, Measures (Individuals)
Wang, Chun; Zhang, Xue – Grantee Submission, 2019
The relations among alternative parameterizations of the binary factor analysis (FA) model and two-parameter logistic (2PL) item response theory (IRT) model have been thoroughly discussed in literature (e.g., Lord & Novick, 1968; Takane & de Leeuw, 1987; McDonald, 1999; Wirth & Edwards, 2007; Kamata & Bauer, 2008). However, the…
Descriptors: Test Items, Error of Measurement, Item Response Theory, Factor Analysis
Wang, Weiqiang; Tian, Haiyan – International Journal of Web-Based Learning and Teaching Technologies, 2023
Video observation and content analysis are used to make a "quantitative-qualitative" analysis of English teachers' teaching behavior reflected in English classroom teaching videos, and to accurately describe, analyze, and summarize the characteristics of English teachers' teaching behavior from various aspects. Based on this, this study…
Descriptors: Multivariate Analysis, Video Technology, Content Analysis, Language Teachers
Hope E. Lackey; Rachel L. Sell; Gilbert L. Nelson; Thomas A. Bryan; Amanda M. Lines; Samuel A. Bryan – Journal of Chemical Education, 2023
The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least-squares (CLS), principal component…
Descriptors: Chemistry, Data Analysis, Optics, Lighting
Sentiment and Sentence Similarity as Predictors of Integrated and Independent L2 Writing Performance
Uzun, Kutay; Ulum, Ömer Gökhan – Acuity: Journal of English Language Pedagogy, Literature and Culture, 2022
This study aimed to utilize sentiment and sentence similarity analyses, two Natural Language Processing techniques, to see if and how well they could predict L2 Writing Performance in integrated and independent task conditions. The data sources were an integrated L2 writing corpus of 185 literary analysis essays and an independent L2 writing…
Descriptors: Natural Language Processing, Second Language Learning, Second Language Instruction, Writing (Composition)
Avci, Ümmühan; Ergün, Esin – Interactive Learning Environments, 2022
The purpose of this study was to examine online students' LMS activities and the effect on their engagement, information literacy, and academic performance. The participants of the study were 65 undergraduate students enrolled to an online "Computer Literacy" course. Cluster analysis was performed on the log data gathered from LMS…
Descriptors: Electronic Learning, Distance Education, Integrated Learning Systems, Learning Activities
Park, Sunyoung; Natasha Beretvas, S. – Journal of Experimental Education, 2021
When selecting a multilevel model to fit to a dataset, it is important to choose both a model that best matches characteristics of the data's structure, but also to include the appropriate fixed and random effects parameters. For example, when researchers analyze clustered data (e.g., students nested within schools), the multilevel model can be…
Descriptors: Hierarchical Linear Modeling, Statistical Significance, Multivariate Analysis, Monte Carlo Methods
Prasertpong, Phanuwat; Charmondusit, Kitikorn; Taecharungroj, Viriya; Rawang, Wee; Suwan, Sumit; Woraphong, Seree – International Journal of Education and Practice, 2023
The main objective of this research was to study the factors influencing the science and environment of education program for blind students at the elementary level. This research used mixed methods (quantitative and qualitative approaches), specifically a questionnaire survey was conducted to better understand the current situation on Science and…
Descriptors: Science Education, Environmental Education, Blindness, Elementary School Students
Qiao, Xin; Jiao, Hong; He, Qiwei – Journal of Educational Measurement, 2023
Multiple group modeling is one of the methods to address the measurement noninvariance issue. Traditional studies on multiple group modeling have mainly focused on item responses. In computer-based assessments, joint modeling of response times and action counts with item responses helps estimate the latent speed and action levels in addition to…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Statistical Distributions
Lin, Lifeng; Chu, Haitao – Research Synthesis Methods, 2018
In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…
Descriptors: Bayesian Statistics, Multivariate Analysis, Meta Analysis, Correlation

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