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…

It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…

In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community…

In this research, we aimed to investigate the visual-cognitive behaviours of a sample of 106 children in Year 3 (8.8 ± 0.3 years) while completing a mathematics bar-graph task. Eye movements were recorded while children completed the task and the patterns of eye movements were explored using machine learning approaches. Two different techniques of…

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…

This chapter addresses students' data interpretation, a key NGSS inquiry practice, with which students have several different types of difficulties. In this work, we unpack the difficulties associated with data interpretation from those associated with warranting claims. We do this within the context of Inq-ITS (Inquiry Intelligent Tutoring…

In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…

In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…

As expectations of the economic impact of educational attainment are soaring (Hanushek & Woessmann, 2009) and conjectures about successful national educational reforms (Mourshed, Chijioke, & Barber, 2010) are welcomed by educational policy-makers in many countries, a careful assessment of the empirical evidence for these kinds of claims is…

Discussions of the foundations of perceptual inference have often centered on 2 governing principles, the likelihood principle and the simplicity principle. Historically, these principles have usually been seen as opposed, but contemporary statistical (e.g., Bayesian) theory tends to see them as consistent, because for a variety of reasons simpler…

During the 2009-2010 school year, Marzano Research Laboratory (MRL) was commissioned by Promethean Ltd. to conduct a second year evaluation study of the effects of Promethean ActivClassroom on student academic achievement. This report describes the findings from the second year study along with aggregate findings from the first and second year…

The Bayesian inferential process is modified for use in an aggregate meta-analytic evaluation. Compared with the average effect size meta-analytic approach, the Bayesian approach was more sensitive, more consistent and more powerful. This approach is recommended when primary data are not available and when all evaluations involve comparisons of…

Many educators and researchers are trying to define statistical literacy for the 21st century. Kimura, a Japanese science educator, has suggested that a key task of statistical literacy is the ability to extract qualitative information from quantitative information, and/or to create new information from qualitative and quantitative information.…