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Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
Semih Sait Yilmaz; Ayse Collins; Seyid Amjad Ali – European Journal of Education, 2024
In response to the COVID-19 pandemic, an abrupt wave of digitisation and online migration swept the higher education institutions around the globe. In the aftermath of this digital transformation which endures as the legacy of the pandemic, what lacks in knowledge is how effective the anti-COVID measures were in maintaining quality education.…
Descriptors: Foreign Countries, Artificial Intelligence, Higher Education, COVID-19
Turhan, Nihan Sölpük – Educational Research and Reviews, 2020
Statistical tests have been an important tool for interpreting the results of research correctly. The factors that influence the determination of the statistical test are research purpose, hypothesis and data. Today, statistical tests are used more frequently, and they aim to analyze whether statistical tests are used in accordance with research.…
Descriptors: Statistical Analysis, Data Interpretation, Goodness of Fit, Methods
AlWahaibi, Ibrahim Said Humaid; AlHadabi, Dawood Abdul Malik Yahya AlHadabi; AlKharusi, Hussain Ali Talib – Cypriot Journal of Educational Sciences, 2020
The present study aimed at clarifying the various shortcomings of the Cohen's criteria for the interpretation of the values of the practical significance indicators. The hypothetical data were used for two experimental and control groups and calculating the paired-samples t-test. To clarify the inadequacy of Cohen's criteria in interpreting…
Descriptors: Statistical Analysis, Statistical Significance, Equations (Mathematics), Computation
Hoekstra, R.; Vugteveen, J.; Warrens, M. J.; Kruyen, P. M. – International Journal of Social Research Methodology, 2019
Cronbach's alpha is the most frequently used measure to investigate the reliability of measurement instruments. Despite its frequent use, many warn for misinterpretations of alpha. These claims about regular misunderstandings, however, are not based on empirical data. To understand how common such beliefs are, we conducted a survey study to test…
Descriptors: Statistical Analysis, Researchers, Beliefs, Knowledge Level
Jones, Thomas J.; Ehlers, Todd A. – Journal of Geoscience Education, 2021
The need for geoscience students to develop a quantitative skillset is ever increasing. However, this can be difficult to implement in university-style lecture courses in a way that is both manageable for the instructor and does not involve lengthy, potentially repetitive, question sheets for the students. Here, a method for teaching dimensional…
Descriptors: Earth Science, Science Experiments, Graduate Students, College Science
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
Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
Ozmen, Zeynep Medine; Guven, Bulent; Kurak, Yasin – Eurasian Journal of Educational Research, 2020
Purpose: Previous research focused on graphical skills of the students, which remains a gap that exists, and there has not been comprehensive research on students' graphical literacy abilities. The present study aims to picture graphical literacy levels of the 8th grade students concerning the "reading," "interpreting,"…
Descriptors: Middle School Students, Grade 8, Knowledge Level, Graphs
He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne – Practical Assessment, Research & Evaluation, 2018
In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…
Descriptors: Institutional Research, Regression (Statistics), Statistical Analysis, Data Analysis
Schweig, Jonathan; McEachin, Andrew; Kuhfeld, Megan; Mariano, Louis T.; Diliberti, Melissa Kay – RAND Corporation, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Jonathan Schweig; Andrew McEachin; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Bi, Henry H. – Assessment & Evaluation in Higher Education, 2018
There are no absolute standards regarding what teaching evaluation ratings are satisfactory. It is also problematic to compare teaching evaluation ratings with the average or with a cutoff number to determine whether they are adequate. In this paper, we use average and standard deviation charts (X[overbar]-S charts), which are based on the theory…
Descriptors: Robustness (Statistics), Data Interpretation, Rating Scales, Computation
Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
Yang, Yang – International Journal of Adult Vocational Education and Technology, 2016
Q methodology is a method to systematically study subjective matters such as thoughts and beliefs on any given topic. Q methodology can be used for both theory building and theory testing. The purpose of this paper was to give a brief overview of Q methodology to readers with various backgrounds. This paper discussed several advantages of Q…
Descriptors: Q Methodology, Mixed Methods Research, Qualitative Research, Statistical Analysis