Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of…

Research in the social and behavioral sciences relies on a wide range of experimental and quasi-experimental designs to estimate the causal effects of specific programs, policies, and events. In this paper we highlight measurement issues relevant to evaluating the validity of causal estimation and generalization. These issues impact all four…

Theoretical models of reading comprehension have consistently highlighted the importance of inference generation in the meaning-making process. Additionally, previous research has indicated that instruction in making inferences is effective at improving inference ability and general reading comprehension. In this meta-analysis, we aimed to further…

We examined knowledge-based inference in 6-, 8- and 10-year-olds. Participants listened to texts where the number of clues for an inference was manipulated and then judged whether single-word probes (target inference, competing inference, literal word from the text and an unrelated concept) were related to the story. Accuracy and response times…

This experiment employed viewing time methods to investigate the effects of individual differences in visuospatial working memory (VWM) on the processing of older adults' bridging inferences in the understanding of visual narratives. The results showed that older adults could make bridging inferences in visual narrative processing, and that VWM…

Behavioral inhibition (BI) is an early-appearing temperamental trait characterized by intense negative affect and withdrawal behaviors to novel and challenging situations. Inhibited children are more likely to display social withdrawal and experience an increased risk for internalizing problems. Trait inference, the way children interpret…

Inferencing is an important and complex process required for successful reading comprehension. Previous research has suggested instruction in inferencing is effective at improving reading comprehension. However, varying definitions of inferencing is likely impacting how inferencing instruction is implemented in practice and inferencing ability is…

Knowledge tracing (KT) for evaluating students' knowledge is an essential task in personalized education. More and more researchers have devoted themselves to solving KT tasks, e.g., deep knowledge tracing (DKT), which can capture more sophisticated representations of student knowledge. Nonetheless, these techniques ignore the reconstruction of…

Sensitivity analysis, a statistical method crucial for validating inferences across disciplines, quantifies the conditions that could alter conclusions (Razavi et al., 2021). One line of work is rooted in linear models and foregrounds the sensitivity of inferences to the strength of omitted variables (Cinelli & Hazlett, 2019; Frank, 2000). A…

When a situation could lead to multiple mutually exclusive consequences, recent research shows that people automatically generate multiple predictive inferences in memory. Several theoretical mechanisms have been proposed to account for the generation of predictive inferences. One hypothesis is that inferences are minimally encoded, represented…

Making inferences is essential to comprehending text. Teachers can ask inferential questions, model their thinking, and teach specific strategies to support upper elementary students in making inferences while reading.

U.S. national data indicate that approximately 90% of rural students with a reading disability read at or below basic levels of reading proficiency. A growing body of research demonstrates that the ability to make inferences is essential for reading comprehension but particularly difficult for students with reading disabilities. Compounding…

Using software to teach statistical inference in introductory courses opens the door for methods and practices that are more conceptually appealing to students. With an increasing number of fields requiring competency in statistics including data science, natural and social sciences, public health and more, it is crucial that we as instructors…

Generating accurate inferences is crucial for the successful comprehension of text and is a skill that needs to be supported starting in the early grades. Teachers can support inference-making during read-aloud lessons by asking inferential questions and providing scaffolding and feedback on students' inference-making. In this article, we describe…

This paper scrutinizes the increasing trend of using international large-scale assessment (ILSA) data for causal inferences in educational research, arguing that such inferences are often tenuous. We explore the complexities of causality within ILSAs, highlighting the methodological constraints that challenge the validity of causal claims derived…