DIP: Collaborative Research: Transforming Science Learning with an Interactive Web Environment for Data Sharing and Visualization

Fred Martin, Michelle Scribner-MacLean, University of Massachusetts Lowell (Award Details)
Samuel Christy, Machine Science Inc. (Award Details)

In this Cyberlearning Design and Implementation Project, the University of Massachusetts Lowell (UML) and a non-profit collaborator, Machine Science Inc. of Cambridge, Massachusetts, are studying classroom implementations of a web platform that helps middle school and high school teachers engage their students in collaborative scientific inquiry. This technology — the Internet System for Networked Sensor Experimentation (iSENSE) — provides a shared repository of user-contributed classroom activities, such as tabletop science experiments, environmental analyses, engineering projects, and surveys, together with the data generated by these activities. The system features tools that enable teachers and students to create their own experiments, upload and tag data, and configure and share dynamic visual representations of the data.

School districts in Massachusetts and New Hampshire are participating in the four-year study. Teachers from each district attend annual summer professional development workshops at UML and receive ongoing support from the project team in integrating iSENSE into their science teaching. Educators participate in follow-up meetings during the academic year to report their experiences and exchange best practices. The most promising approaches are documented as lesson plans and shared with the larger iSENSE community. Throughout the project, researchers from UML’s Graduate School of Education are collecting formative data to inform system refinement and curriculum development and to answer questions about integration and use of cyber-enabled learning technologies in classrooms, and conducting a summative assessment to determine the project’s impact on student learning and science teaching practice.

Project deliverables include a set of iSENSE lesson plans, developed in close consultation with participating educators, together with several significant enhancements to the iSENSE data collection and visualization technology and a set of guidelines and justifications for those guidelines pertaining to developing data scientists and to integrating cyber-enabled learning technologies into classrooms. In particular, the project partners are developing data collection and visualization apps for Android and iOS mobile devices. On the iSENSE website, community-building features are being integrated into the system, giving users the ability to “follow” each other’s system activity, in the manner of Twitter or Facebook. To foster a sense of community, students and teachers are encouraged to append comments to experiments, data sets, and saved visualizations. This enables them to ask questions relating to ongoing experiments,share resources, suggest further investigations, and critique one another’s work.

Because iSENSE incorporates many emerging cyberlearning technologies, including interactive data visualizations, on-line community-building features, and the use of mobile computing platforms, the project has broad potential implications for the cyberlearning field. The project team is investigating how interacting with cyberlearning technologies and collaborating on-line changes the way students think about scientific data and the nature of science. The team is also examining how cyberlearning resources, such as user-contributed web content, web-based software tools, and mobile computing platforms, can enhance science teaching practice. At the same time, the investigators seek to identify what resources are needed, in terms of technology, professional development, and curriculum, to effectively support incorporation of sophisticated learning technologies in support of science practice and learning in the classroom.

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