Abstract:

The collection and analysis of big data: high volume, high velocity, and high variety (3HV) data streams are transforming the research world and the marketplace. Scientific research based on data synthesis yields discoveries as powerful as laboratory and field-based investigation. Yet teaching big data techniques is not yet prevalent in the classroom, in curricula, or informal science education. The STEM workforce needs tools to make good use of the massive volumes of heterogeneous data now available and students should be exposed to these datasets early and often to prepare them for their future. This paper examines a Professional Development (PD) model that provides middle and high school teachers with exposure, experience, and time to absorb 3HV information. In doing so, these teachers are better able to introduce and incorporate 3HV data in their own science classrooms.

Why focus on big data?
Scientific discovery, problem solving, and hypothesis testing requires observation, data analysis, and synthesis of new knowledge. This process uses existing knowledge to develop a theoretical framework, and today this effort is highly dependent on computer-based data exploration. Big data results are now woven into daily life, as our smartphones help us avoid traffic, and search engines “learn” our buying preferences. Many Teachers are adept at using laboratory experiments and field studies to educate. These approaches are deeply embedded in curricula at all levels. Indeed, some of our field and laboratory experiences are so powerful that they inspire a career or a lifetime appreciation of our planet. Though the power of big data methods surpasses the amount of information gathered from these types of experiences, data-intensive science has not yet achieved this kind of impact or prominence in middle and high school education. This study provides an examination of a PD workshop that attempts to bridge this gap.

Earth workshops
These PD workshops are implemented by the Monterey Bay Aquarium Research Institute (MBARI) and integrate 6-12 grade educator audiences in co-designing lessons with “in-the-field” scientists and their unique data sets. Often there is not sustained use of materials provided in traditional PD. This model for PD offers strategies that ensure engagement by educators long after the event, supporting national science standard goals of systemically incorporating real data usage in educational environments and facilitating sustained usage. Data in this study was gathered through observations of the week-long PD, interviews with participants during and after the PD, and anonymous participant surveys conducted during and after the PD. We document the design principals embodied in this PD and conduct a comparative analysis. Understanding this PD model may lead to enhanced coherence of science education programs through teacher professional development. Thus providing a more effective, sustainable, and efficient utilization of the vast array of publicly available big data resources that may be used in the classroom.

Keywords:

Big data in the classroom, teacher professional development, application of big data.