In this Cyberlearning: Transforming Education Exploration project, researchers focus on the challenge of helping students in grades 4 through 6 develop data science skills -- understanding the significance of data and where it comes from, and developing capabilities involved in manipulating data and using it to draw conclusions and make informed decisions. The researchers are developing and refining software, called Local Ground, designed to allow learners to collect data relevant to local scientific or socio-scientific challenges and to help learners manipulate those data and use them to achieve the challenge, in the process developing charts, graphs, and narratives to be shared with others. The system is designed to provide scaffolding that helps students iteratively develop and refine representations and understandings of what their data represent. It is designed to display and translate between a variety of distinct representations. The intention is that Local Ground will act as an "auxiliary stimulus" -- a cultural form wedged between students' naïve ways of thinking and spontaneous inclinations to represent that thinking. The research team is using use of Local Ground as a context for investigating fundamental questions associated with developing data science skills, including how children convert naïve representations into more usable and communicable forms, how and if those forms are appropriate by others, how those processes support understanding of core mathematic, statistical, and computational constructs, and the impact of locally collected and relevant data on learning these competencies.
Understanding, manipulating, and using data are essential skills for 21st century citizens. The researchers in this project are exploring a new approach to helping pre-teens begin to develop data skills and designing a software platform called Local Ground that supports 4th through 6th graders as they work on community projects they care about that require significant data collection, manipulation, analysis, and application. The pedagogical approach has students using data in sophisticated ways to address issues of importance to their communities; the tool helps them successfully gather, analyze, and use the data. In this context, the researchers are engaging in research that will add to what is known about how to help young learners understand core mathematical, statistical, and computational constructs important to data use and analysis.
