Scientific inquiry can be more authentic and meaningful to students when using personal and peer-collected data. The challenges of organizing and evaluating a potentially large amount of data can be overcome through the use of annotations (title, tags, and audio notes). We created Zydeco, a multi-component system that students use to collect annotated multimedia data from a museum (using a smartphone app), and then create a scientific explanation with their personal and peers' data (using a tablet app). We ran a classroom study with 54 students (ages 11-13) investigating how students searched for, evaluated, and used annotated data to construct a scientific explanation. We found that tags supported data interpretation, while title searching and panning through the unfiltered data set supported finding and using data.
Digitally augmented physical spaces (e.g., smart classrooms) offer opportunities to engage students in novel and potentially transformative learning experiences. This paper presents an immersive rainforest simulation and collective inquiry activity where students collect observational data from the environment and explore their peers' data through large visualization displays and personal mobile devices. Two iterations of the design were tested, which resulted in higher quality student explanations constructed. Images were found to be an important source of evidence for the explanations, more so than text-only evidence. We also found that patterns of collective ideas influenced student performance, and that visualizations, as ambient or plenary displays, supported both teacher and students in reviewing patterns of collected data.
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