Data Routine for working with existing scientific data¶

Element · All elements
Evidence · 2 claims (2 for) · 2 studies (1 causal, 1 review), q2 · 0 of 2 report an effect size · 2 claims rest on one study

Description¶

The Data Routine is a teaching routine described by Penuel et al. (2023) to support students working with existing scientific data to explore real-world phenomena. Per the report, "The Data Routine includes four elements: Framing Questions, Orienting to the Data, Exploring the Data, and Sensemaking About the Data." Designers intend it to support both curriculum developers and teachers in designing and enacting lessons that engage students productively with data, focusing on steps not commonly encountered in science classes.

Design Implications¶

Context¶

Requirements¶

• Should be used in the context of a storyline-based unit, as the designers describe clarifying routine elements within a storyline

Constraints¶

• Initially conceived as a tool for curriculum designers; the report notes it also has potential to shape teachers' lesson adaptations

Target Learners¶

• high school science students

Target Learning Goals¶

• analyzing and interpreting scientific data
• sensemaking about data

Claims¶

• OpenSciEd grade 7 units align with some data-practice frameworks but are less aligned with digital tools, large data sets, and full data cycles [+W]
• Teachers addressed graph comprehension consistently at high levels across observed lessons, while covariational reasoning enactment varied widely by lesson [+W]

Related Elements¶

Examples¶

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Key Sources¶

• McElhaney, K. W., & Kamdar, D. (2024). Updated summary and synthesis of OpenSciEd research [White paper]. Digital Promise. https://doi.org/10.51388/20.500.12265/231