Growing SAM: Bringing Animation into Informal STEM Educational Settings

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Typically when a teacher wants to probe a student's understanding of a concept, she asks him to write about it. In science students write lab reports, in reading they write book reports; even in math, students often have to write how they solved the math problem. Unfortunately, many students do not enjoy writing and therefore do not necessarily give the teacher the insight she is looking for. In currently funded NSF work at Tufts University, researchers are developing a software toolset that allows students to build stop action movies (SAM) as a means for representing ideas about math and science. SAM is not meant to replace the standard reporting methods, but rather to augment them. Tufts investigators, looking at how students learn differently as a result of the difference in reporting mechanism, are finding that animation can even motivate and drive the learning (because students want to improve their movies). This ongoing work has reached the halfway point, and is starting to show preliminary successes in the classroom. Changing the reporting methodology has resulted in students being excited about coming to class. They willingly stay after class to complete their "reports", and will actively discuss the science they are learning with each other and with the teacher. This exploratory grant will allow the PI to join the Tufts team, as it were, so that the project can branch out into other learning environments while still in the development stage. The PI will extend the research to non-school-based learning environments, with particular concentration on reaching out to African-American and Latino communities. The timing of this work is critical for both institutions, and the results will be mutually beneficial. Outcomes of this exploratory project will enable Tufts to improve the user interface while their SAM software is still in development, and thereby potentially open up a new learning market. UCSD, on the other hand, will acquire new tools to teach logical thinking and elementary programming to disadvantaged populations, exploiting the substantial infrastructure and expertise they already have in place. Broader Impacts: This research will extend the SAM approach into non-traditional educational settings (e.g., the after-school learning environment) for disadvantaged students, and will further help our understanding in general of how kids learn in different environments.