Classroom Learning Partner (CLP) tools allow students and teachers to create, annotate, and manipulate visual representations to solve math problems. The tools may be used for a number of mathematical purposes, but were mainly conceived to assist in creating visual representations for multiplication and division. The underlying model of multiplication and division assumed by the current set of tools involves a repetition of groups of the same size.
Smith, J. P., & Barrett, J. E. (2017). The learning and teaching of measurement: Coordinating quantity and number. In J. Cai (Ed.), Compendium for research in mathematics education (pp. 355–385). Reston, VA: National Council of Teachers of Mathematics.
Quantitative reasoning and measurement competencies support the development of mathematical and scientific thinking in children in the early and middle grades and are fundamental to science, technology, engineering, and mathematics (STEM) education. The sixteenth Journal for Research in Mathematics Education (JRME) monograph is a report on a four-year-long multisite longitudinal study that studied children’s thinking and learning about geometric measurement (i.e., length, area, and volume).
We evaluated the effects of three instructional interventions designed to support young children’s understanding of area measurement as a structuring process.
Explore methods and challenges associated with supporting and evaluating scientific modeling in K–12 classrooms in this structured poster session.
In this interactive panel symposium, presenters will draw from a set of active DR K-12 projects to explore a diverse array of resources, models, and tools (RMTs) designed to operationalize varying perspectives on scientific modeling in elementary, middle, and secondary classrooms across disciplinary domains.
Join a facilitated discussion about the application of data science to education, drawing on a recent NSF-sponsored report. Participants share insights from DR K–12 projects.
The Computing Research Association’s report from an NSF-sponsored workshop describes seven next steps for data-intensive research in education:
This session provides a forum for discussing the challenges of evaluating program effectiveness by using existing measures that vary in their alignment with program learning goals.
This session provides a forum for discussion around issues of alignment between programs, their learning goals, and the measures for assessing program effectiveness. The session seeks to offer ideas and strategies on how to tackle these kinds of issues.
The session addresses a common challenge in research—the tension between the need for using existing measures to ensure that research results can be compared across studies and the need for using measures that are well-aligned with a program’s learning goals to assess treatment effects.
How do we encourage referent-based mathematical argumentation without encouraging students to request that examples accompany otherwise viable arguments? Assessment concerns are explored and discussed.
The LAMP project has developed a sequence of lessons in a hypothetical learning trajectory that targets students’ ability to write viable arguments in algebraic contexts. Most of the lessons encourage students to produce a referent (e.g., variable expression or equation, generic example, diagram) as the foundation of their argument. Students come to the lessons with a predisposition for example production in support of their claims and to augment arguments.
This interactive session is designed to promote critical thinking about current research practices and integrate a variety of perspectives on research syntheses and how they can help advance education research.
Examples of research practices that limit the validity of research syntheses are not difficult to find. For example, Education Development Center, Inc. (EDC), and Abt Associates reported in their Compendium of STEM Instruments that psychometric reporting practices in the STEM community tend to be insufficient, and this limited what they could learn from their synthesis.