As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…

The advent of data science has led to statistics education researchers re-thinking and expanding their ideas about tools for teaching statistical modeling, such as the use of code-driven tools at the secondary school level. Methods for statistical inference, such as the randomization test, are typically taught within secondary school classrooms…

Data-art inquiry is an arts-integrated approach to data literacy learning that reflects the multidisciplinary nature of data literacy not often taught in school contexts. By layering critical reflection over conventional data inquiry processes, and by supporting creative expression about data, data-art inquiry can support students' informal…

New strategies come along all the time, but these strategies matter little if educators are not sure why they are using them or what the desired outcome is. Quality literacy instruction should be rooted in effective foundational practices. Text-dependent questions offer a foundation for literacy practices that support students' comprehension,…

Staggered adoption of policies by different units at different times creates promising opportunities for observational causal inference. Estimation remains challenging, however, and common regression methods can give misleading results. A promising alternative is the synthetic control method (SCM), which finds a weighted average of control units…

Teacher shortages and attrition are problems of international concern. One of the most frequent reasons for teachers leaving the profession is a lack of job satisfaction. Accordingly, in this study we have adopted a causal inference machine learning approach to identify practical interventions for improving overall levels of job satisfaction. We…

We describe an activity that introduces students to population modelling, enables them to use estimates obtained from a sample to infer back to the population, and understands how the findings are translatable via penguins and their poo!

Upon hearing a scalar adjective in a definite referring expression such as "the big…," listeners typically make anticipatory eye movements to an item in a contrast set, such as a big glass in the context of a smaller glass. Recent studies have suggested that this rapid, contrastive interpretation of scalar adjectives is malleable and…

Although there is no generally accepted list of criteria for the acceptance of proofs in mathematical practice, judging the acceptability of purported proofs is an essential aspect of handling proofs in daily mathematical work. For this reason, school students, university students, and mathematicians need to hold certain acceptance criteria for…

In institution research, surveys of students or faculty can be a helpful tool to gather data. Surveying a sample of students or faculty and computing weights to be able to make inferences to your student or faculty population are important. In this chapter, we introduce the connected topics of sampling and weighting. We begin with a discussion on…

In this article, I introduce Robert Brandom's inferentialism as an alternative to common representational interpretations of constructivism in science education. By turning our attention away from the representational role of conceptual contents and toward the norms governing their use in inferences, we may interpret knowledge as a capacity to…

There is much debate about the place of probability in an introductory statistics course. While students may or may not use probability distributions in their post-collegiate lives, they will likely be faced with day-to-day decisions that require a probabilistic assessment of risk and reward. This paper describes an innovative way to teach…

Purpose: This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method: First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors.…

The analysis of covariance (ANCOVA) is a useful statistical procedure that incorporates covariate features into the adjustment of treatment effects. The consequences of omitted prognostic covariates on the statistical inferences of ANCOVA are well documented in the literature. However, the corresponding influence on sample-size calculations for…

Corpus-based studies have offered the domain definition inference for test developers. Yet, corpus-based studies on temporal fluency measures (e.g., speech rate) have been limited, especially in the context of academic lecture settings. This made it difficult for test developers to sample representative fluency features to create authentic…