Given decision-makers often prioritize causal research that identifies the impact of treatments on the people they serve, a key question in education research is, "Does it work?". Today, however, researchers are paying increasing attention to successive questions that are equally important from a practical standpoint--not only does it…

Though previously unacknowledged, a SMART (Sequential Multiple Assignment Randomized Trial) design uses both regression discontinuity (RD) and randomized controlled trial (RCT) designs. This combination structure creates a conceptual symbiosis between the two designs that enables both RCT- and previously unrecognized, RD-based inferential claims.…

Background: For decades, education researchers have relied on the work of Campbell, Cook, and Shadish to help guide their thinking about valid impact estimates in the social sciences (Campbell & Stanley, 1963; Shadish et al., 2002). The foundation of this work is the "validity typology" and its associated "threats to…

Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…

Classroom engagement is a critical factor for evaluating students' learning outcomes and teachers' instructional strategies. Traditional methods for detecting classroom engagement, such as coding and questionnaires, are often limited by delays, subjectivity, and external interference. While some neural network models have been proposed to detect…

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…

Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers' case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method,…

Single-case experimental designs (SCEDs) have a long history in clinical and educational disciplines. One underdeveloped area in advancing SCED design and analysis is understanding the process of how internal validity threats and operational concerns are avoided or mitigated. Two strategies to ameliorate such issues in SCED involve replication and…

Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a…

Traditional cloze tests (such as the CBM-maze) may be poor measures of comprehension processes beyond the single sentence level. This paper presents an alternative, a deep cloze test with gaps that are strategically chosen to assess comprehension beyond the sentence level. To fill each gap, the reader has to draw global cohesion inferences during…

In this paper, we explore the role that examples play as mathematicians formulate conjectures, and we describe and exemplify one particular example-related activity that we observed in interviews with thirteen mathematicians. During our interviews, mathematicians productively used examples as they formulated conjectures, particularly by creating…

Narrative inquiry is a type of qualitative research that explores human experiences through lived or told stories to understand a phenomenon. Narrative researchers collect data through spoken or written stories and life experiences of an individual (subject). The data is examined in chronological order to understand the meaning of the phenomenon…

An ongoing debate in the literature on human reasoning concerns whether or not the logical status (valid vs. invalid) of an argument can be intuitively detected. The finding that conclusions of logically valid inferences are liked more compared to conclusions of logically invalid ones--called the logic-liking effect--is one of the most prominent…

Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…

Researchers across many fields have called for greater attention to heterogeneity of treatment effects--shifting focus from the average effect to variation in effects between different treatments, studies, or subgroups. True heterogeneity is important, but many reports of heterogeneity have proved to be false, non-replicable, or exaggerated. In…