Mathematics

We explore the implementation of a co-designed data-dance unit in which middle school students created their own embodied metaphors to represent and communicate about graphs through dance. In analyzing dance artifacts and post-study interviews with the learners and teachers, we demonstrate how the creation of embodied metaphors in dance led to new ways of exploring the data as learners reflected on different perspectives on topics across numerical values, contexts, and implications.

Effective data literacy instruction requires that learners move beyond understanding statistics to being able to humanize data through a contextual understanding of argumentation and reasoning in the real-world. In this paper, we explore the implementation of a co-designed data comic unit about adolescent friendships.

Effective data literacy instruction requires that learners move beyond understanding statistics to being able to humanize data through a contextual understanding of argumentation and reasoning in the real-world. In this paper, we explore the implementation of a co-designed data comic unit about adolescent friendships.

Effective data literacy instruction requires that learners move beyond understanding statistics to being able to humanize data through a contextual understanding of argumentation and reasoning in the real-world. In this paper, we explore the implementation of a co-designed data comic unit about adolescent friendships.

The process of using Learning Analytics (LA) to improve teaching works from the assumption that data should be readily shared between stakeholders in an educational organization. However, the design of LA tools often does not account for considerations such as data privacy, transparency and trust among stakeholders. Research in human-centered design of LA does attend to these questions, specifically with a focus on including direct input from K-12 educators. In this paper, we present a series of design studies to articulate and refine conjectures about how privacy and transparency might influence better trust-building and data sharing within four school districts in the United States.

Despite the ease of accessing a wide range of measures, little attention is given to validity arguments when considering whether to use the measure for a new purpose or in a different context. Making a validity argument has historically focused on the intended interpretation and use. There has been a press to consider both the intended and actual interpretations and how users make sense of the data when constructing validity arguments, but the practice is not widespread.This paper contributes to existing research on validity by highlighting the value of attending to the actual interpretation and use of a measure aimed at supporting instructional improvement in mathematics.

With the spread of learning analytics (LA) dashboards in K-12 schools, educators are increasingly expected to make sense of data to inform instruction. However, numerous features of school settings, such as specialized vantage points of educators, may lead to different ways of looking at data. This observation motivates the need to carefully observe and account for the ways data sensemaking occurs, and how it may differ across K-12 professional roles. Our mixed-methods study reports on interviews and think-aloud sessions with middle-school mathematics teachers and instructional coaches from four districts in the United States.

From a network perspective, self-regulated learning (SRL) can be conceptualized as networks of mutually interacting self-regulatory learning behaviors. Nevertheless, the research on how SRL behaviors dynamically interact over time in a network architecture is still in its infancy, especially in the context of STEM (sciences, technology, engineering, and math) learning. In the present paper, we used a multilevel vector autoregression (VAR) model to examine the temporal dynamics of SRL behaviors as 101 students designed green buildings in Energy3D, a simulation-based computer-aided design (CAD) environment.

The work presented here describes in detail the development of an integrated STEM observation instrument - the STEM Observation Protocol (STEM-OP) - that can be used for both research and practice. Over a period of approximately 18-months, a team of STEM educators and educational researchers developed a 10-item integrated STEM observation instrument for use in K-12 science and engineering classrooms. The process of developing the STEM-OP began with establishing a conceptual framework, drawing on the integrated STEM research literature, national standards documents, and frameworks for both K-12 engineering education and integrated STEM education.

The work presented here describes in detail the development of an integrated STEM observation instrument - the STEM Observation Protocol (STEM-OP) - that can be used for both research and practice. Over a period of approximately 18-months, a team of STEM educators and educational researchers developed a 10-item integrated STEM observation instrument for use in K-12 science and engineering classrooms. The process of developing the STEM-OP began with establishing a conceptual framework, drawing on the integrated STEM research literature, national standards documents, and frameworks for both K-12 engineering education and integrated STEM education.