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In this post, we are excited to share an Analyzing and Interpreting Data Routine. This is part of a rough draft effort to create instructional practice slides that support teachers when using curriculum resources from UC San Diego. The aim is that these highly accessible resources help teachers facilitate unfamiliar tasks or routines with students. They also serve as helpful reminders on literature and effective practices to support diverse learners, such as multilingual learners.
The Power of Analyzing and Interpreting Data in Science Education
Data analysis and interpretation helps students engage in authentic scientific practices and think/act like real scientists. Data analysis is not a solitary act, but is a collaborative process where students discuss and make sense of data together. It helps students move beyond just collecting data to answering science research questions and developing evidence-based explanations. The focus for this routine should be about analyzing data for a purpose, not just running calculations or creating a graph to practice isolated skills.
As students analyze and interpret data, they develop critical thinking skills by looking for patterns, relationships and trends in data. This helps them connect evidence to claims in scientific explanations of phenomena. It also provides opportunities for promoting scientific discourse and argumentation among students as they interpret their findings.
The Analysis and Interpretation of Data Routine
Analyzing and Interpreting Routine: This google doc allows you to scaffold student thinking through the scaffolded steps of analysis and interpretation.
Analyzing and Interpreting Data Routine Slides: These slides provide a step-by-step guide for educators to lead their students through the data analysis process. From identifying data features to interpreting relationships, each slide offers clear instructions and prompts.
Initial Analysis of Data Organizer: This template helps students structure their initial observations and interpretations of data. It encourages them to notice features, describe the purpose of the data, and begin identifying patterns.
Example Organizer with Responses: To support teachers in implementing this routine, we've included an example organizer filled with sample responses. This demonstrates how students might engage with real-world data about temperature variations across different locations in San Diego.
Key Features of the Routine
Our new resource is based off the Next Generation Science Standards: A Framework for K-12 Science Education and the wonderful professional learning resources of OpenSciEd. Consulting with the California Reading and Literature Project (CRLP), we developed the resources to implement the routine with emerging multilingual learners. Below are the key features:
Scaffolded Approach: The routine breaks down the analysis and interpretation into manageable steps, from observations of data features to careful inferences on patterns.
Emphasis on Pattern Recognition: Students are guided to identify patterns in various types of data representations, including tables, graphs, and maps, aligning with the National Framework's goal of helping students "recognize patterns in data that suggest relationships with investigating further" (NRC, 2012, p.52).
Focus on Interpretation: Beyond just identifying patterns, students are prompted to consider what the data means in the context of their investigation on their anchoring or investigative phenomenon.
Flexibility: The routine can be adapted for various types of data and across different scientific disciplines, supporting divers learning needs.
Strategies to use with the Analyzing and Interpreting Data Routine
Many of the following strategies come from Instructional Leadership for Science Practices (ILSP) - www.sciencepracticesleadership.com
To practice making interpretations with data, give students a data table, graph, or map and sentence strips with various statements about the patterns in the data. Have students decide whether each statement is accurate or inaccurate based on the data.
Have groups of students compare and contrast their data tables. If differences exist in the data, ask students to hypothesize about why these differences exist. Have students make a plan to reduce sources of error in future iterations of the investigation (e.g., dropping a ball from the same height, or have the same students operate a stopwatch through the investigation.)
Ask students to vote (thumbs up / thumbs down) whether they agree with a specific interpretation of the patterns in data.
Conduct a gallery walk for students to view and critique each other's data. Encourage students to use sticky notes to ask questions and provide feedback.
Hang posters in the classroom with different types of organized data (tables, bar graphs, line graphs, etc.) that students can reference as they decide what to construct to support analyzing the data.
Additional Data Based Resources
Data Puzzles: Great data resources from CIRES that are for grades 6-12. Most data puzzles require up to two 60-minute class periods.
Data Nuggets: Activities that bring real scientific data into the classroom.
Share how you are using this routine in your classroom. Send your stories to sdsp@ucsd.edu or tag us on social media.