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Steffen Erickson – Society for Research on Educational Effectiveness, 2024
Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…
Descriptors: Structural Equation Models, Causal Models, Research Methodology, Error of Measurement
Feinstein, Osvaldo – American Journal of Evaluation, 2023
"Integrative evaluation" is an approach with two main phases: identification of plausible rival hypotheses and integration of rival hypotheses. The first phase may correspond to traditional adversary evaluation, whereas the second phase, that is not included in adversary evaluation, requires integrative thinking which can be applied when…
Descriptors: Evaluation, Integrated Activities, Intervention, Evaluators
Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2022
Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes…
Descriptors: Bayesian Statistics, Hypothesis Testing, Mediation Theory, Vignettes
Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
Mandeep K. Dhami; Ian K. Belton; Peter De Werd; Velichka Hadzhieva; Lars Wicke – Cognitive Research: Principles and Implications, 2024
We empirically examined the effectiveness of how the Analysis of Competing Hypotheses (ACH) technique structures task information to help reduce confirmation bias (Study 1) and the portrayal of intelligence analysts as suffering from such bias (Study 2). Study 1 (N = 161) showed that individuals presented with hypotheses in rows and evidence items…
Descriptors: Task Analysis, Decision Making, Credibility, Cognitive Processes
Geraci, Lisa; Kurpad, Nayantara; Tirso, Robert; Gray, Kathryn N.; Wang, Yan – Metacognition and Learning, 2023
Students often make incorrect predictions about their exam performance, with the lowest-performing students showing the greatest inaccuracies in their predictions. The reasons why low-performing students make inaccurate predictions are not fully understood. In two studies, we tested the hypothesis that low-performing students erroneously predict…
Descriptors: Prediction, Tests, Scores, Low Achievement
Gandhi, S.; Hema, G. – Journal of Educational Technology, 2019
The computer based tests are capable of putting together a lot of interactions and fascinating question types, such as simulations, online tests, and measurement of skills, rather than simply assessing by paper-pencil tests. The computerized test result has greater standardization of test administration. The aim of this study is to seek out the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Undergraduate Students, Foreign Countries
Bradley David Rogers – ProQuest LLC, 2022
Considered normative from the second half of the 20th century (Danziger, 1990), null hypothesis statistical testing (NHST) has received consistent, largely unheeded criticism. Critiques have received more attention in recent years with the recognition of the replication crisis in the social sciences and the American Statistical Society's statement…
Descriptors: Statistical Analysis, Hypothesis Testing, History, Monte Carlo Methods
Chenchen Ma; Gongjun Xu – Grantee Submission, 2022
Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models widely used in educational, psychological and social sciences. In many applications of CDMs, certain hierarchical structures among the latent attributes are assumed by researchers to characterize their dependence structure. Specifically, a directed acyclic…
Descriptors: Vertical Organization, Models, Evaluation, Statistical Analysis
Kristja´nsson, Kristja´n – British Educational Research Journal, 2021
The concept of "phronesis" enters educational discourse at various levels of engagement, and it continues to fascinate and frustrate educational theorists in equal measure. This article begins by charting the vagaries of three educational discourses on phronesis, and by eliciting insights from the recently burgeoning wisdom research…
Descriptors: Intelligence, Educational Philosophy, Hypothesis Testing, Educational Research
Levin, Joel R.; Ferron, John M.; Gafurov, Boris S. – Educational Psychology Review, 2021
Previous simulation studies of randomization tests applied in single-case educational intervention research contexts have typically focused on A-to-B phase changes in means/levels. In the present simulation study, we report the results of two multiple-baseline investigations, one targeting between-phase changes in slopes/trends and the other…
Descriptors: Educational Research, Statistical Analysis, Hypothesis Testing, Intervention
Carolin Danzer – LUMAT: International Journal on Math, Science and Technology Education, 2024
This paper's purpose is to investigate the attitude of students in mathematical discovery processes in terms of the handling of counterexamples. By understanding this attitude as a kind of scientific attitude, it consists of different aspects that become visible in the behaviour during a mathematical discovery process. Since such a process is…
Descriptors: Student Attitudes, Student Behavior, Foreign Countries, Discovery Learning
Shunji Wang; Katerina M. Marcoulides; Jiashan Tang; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…
Descriptors: Hypothesis Testing, Error of Measurement, Comparative Analysis, Monte Carlo Methods
Caspar J. Van Lissa; Eli-Boaz Clapper; Rebecca Kuiper – Research Synthesis Methods, 2024
The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…
Descriptors: Hypothesis Testing, Evaluation Methods, Replication (Evaluation), Sample Size
Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2023
Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…
Descriptors: Comparative Analysis, Hypothesis Testing, Statistical Analysis, Guidelines

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