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.…

The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students' expectations before and after their laboratory courses and experiences. Although the MLLI has been used in various studies and laboratory environments to investigate students' cognitive and affective laboratory expectations, the authors of the instrument…

The present guide provides a practical guide to conducting latent profile analysis (LPA) in the Mplus software system. This guide is intended for researchers familiar with some latent variable modeling but not LPA specifically. A general procedure for conducting LPA is provided in six steps: (a) data inspection, (b) iterative evaluation of models,…

The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…

The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…

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…

Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…

In this article, A. Adrienne Walker introduces the concept of person fit to education stakeholders as a source of evidence to inform the trustworthiness of a test score for interpretation and use (validity). Person fit analyses are used in educational measurement research to explore the degree to which a person's test score can be interpreted as a…

Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can…

When good model-data fit is observed, the Many-Facet Rasch (MFR) model acts as a linking and equating model that can be used to estimate student achievement, item difficulties, and rater severity on the same linear continuum. Given sufficient connectivity among the facets, the MFR model provides estimates of student achievement that are equated to…

Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student…

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…