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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.

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.

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.

Humankind faces unprecedented environmental, social, and economic challenges. There is a critical need for STEM education to foster both science learning and the application of learning to problem solving. At the University of Utah, Professor Nancy Butler Songer and her collaborators have developed a suite of interdisciplinary instructional and field-based data collection resources offering elementary and secondary students the chance to create solutions for local, urban environmental issues.