Machine learning (ML) has become commonplace in educational research and science education research, especially to support assessment efforts. Such applications of machine learning have shown their promise in replicating and scaling human-driven codes of students' work. Despite this promise, we and other scholars argue that machine learning has…

Imprecise constructs abound in science education research in part due to reliance on stipulative definitions that neglect fine distinctions between closely related constructs and overlook important meanings and hidden values embedded in language. Lack of conceptual clarity threatens construct validity, hampers theory development, and prevents…

Discipline-based education research (DBER) conducted by faculty within geoscience departments can address identified needs in undergraduate geoscience education. This study explores the evolution of undergraduate geoscience education research (GER) from 1985 to 2016, primarily in terms of the types of published research and secondarily in terms of…

This article addresses some of the challenges faced when attempting to evaluate the long-term impact of informal science learning interventions. To contribute to the methodological development of informal science learning research, we critically examine (Falk and Needham (2011) "Journal of Research in Science Teaching," 48: 1-12.) study…