Research Summary

‘Let your data tell a story:’ climate change experts and students navigating disciplinary argumentation in the classroom

Using Social Media to Learn Argumentation with Scientists

International Journal of Science Education

The adoption of the Next Generation Science Standards (NGSS) has shifted educators’ focus away from knowledge acquisition to helping students understand the construction and application of scientific ideas in context. This notion of practice-based learning requires creating classroom based opportunities for engaging in authentic science and understanding how scientific knowledge is generated and communicated by professional scientists on an everyday basis, through practices such as argumentation.

To that end, this study explored a partnership between climate scientists and students, facilitated through a social media platform. The researchers were interested in how students developed scientific argumentation skills through practice-based learning with experts. The study centered on a 6-week climate change module within a yearlong life sciences curriculum. In the module, students performed fieldwork, analyzed professional data sets, and used computer modeling to understand climate change impacts, while also developing infographics to communicate their findings. Throughout the module, students used a social media platform that connected them to scientists who periodically provided feedback on student work. Participants included three ninth-grade classes from two schools, with 49 total students. Researchers used a mix of inductive and deductive approaches to analyze students’ draft and final infographics as well as scientists’ feedback.

Overall, through cycles of feedback with expert scientists, students improved their infographics, according to an assessment rubric that the researchers developed. Common revisions included adding text to support the students’ claims and/or providing new evidence, adding graphs or figures, reorganizing information, and removing elements. Students improved their infographics by adding evidence or increasing their depth of explanation, often by adding mechanistic explanations. Although initial infographics were typically simplistic, they grew in complexity over time.

Results demonstrated that, in their feedback to students, scientists modeled their own practices and processes of building arguments and communicating, encouraging students to seek additional evidence. Often, in seeking more evidence, students engaged in additional scientific practices, such as asking probing questions and using mathematical thinking. According to the researchers, scientists’ feedback pushed students to engage more holistically in scientific practices, as doing one practice often involved incorporating many other practices. Also, researchers described the infographics and the data sets that students used as “boundary objects” through which students could learn in partnership with scientists. The work provided a connection point where students could construct personally relevant ideas and engage in practice-based learning along with real scientists. This finding suggests that practice-based science learning should include publicly available, professional data sets, as they provide a window for students into the everyday practices of scientists.

The Bottom Line

Experiences in which students work with expert scientists can support more holistic engagement in scientific practices. Working through cycles of feedback with scientists pushes students to incorporate several different scientific practices as they construct evidence-based arguments. Using publicly available, professional data sets helps students engage in authentic scientific practices in a way that is personally relevant and allows 19 for a meaningful connection point between students and scientists. Teachers can use prior examples of student/ scientist partnerships as models to support practice-based learning of argumentation in their classrooms. Successful practices from prior models include encouraging students to investigate data around related research questions; engaging students in the analysis and data mining of large-scale professional data sets; and asking open-ended, probing questions that elicit reflection and more evidence seeking by students.