We believe that we can’t make informed decisions, or fully understand problems, without understanding the data behind them first. With the Data Science-Driven Science Education (DSDSE) project, we want to help learners and educators to understand how to use data both within the classroom and in their everyday lives.
Every data-driven investigation starts with a statistical investigative question.
Collecting reliable data means using good experimental design and accounting for variability.
Statistical analysis, modeling, and data visualization are essential for drawing accurate conclusions.
Conclusions that are communicated through meaningful visualizations support data-driven solutions.
The DSDSE project is an initiative to raise national data literacy and preparedness among high school students for critical data science careers. We are integrating data science concepts with existing high school STEM curricula to promote adoption, as well as building educator capacity to confidently lead students in data science explorations. Our mission is to make learning data science easier and more accessible.
"...our collective goal in advancing data science research and education is the betterment of our global human society."
Clusters explore topics from many angles. These groupings of pathways are designed by LabXchange and other collaborators to help users to see a topic through different lenses. In contrast to traditional courses or syllabi, clusters provide a multidimensional approach to learning. Within each cluster, learners will develop skills related to one or more of the aforementioned steps of solving problems with data science.
The climate change cluster illustrates data science concepts through the perspective of studying our ever-changing climate. Topics in this cluster align with NGSS high school Earth Science standards and AP Environmental Science coursework.
The biotechnology cluster teaches level-appropriate data science concepts through the lens of modern biotechnology problems, including disease testing and clinical trials. Topics in this cluster align with many NGSS high school Life Sciences standards and AP Biology coursework.
"Through this project, we aim to infuse data science into the high school science curriculum, introducing data science concepts to deepen students' understanding of biotechnology and climate science, and, conversely, using biotechnology and climate science examples to make data science more intuitive and accessible."
We have assembled a dynamic group of leaders, experts, and educators to spearhead this project.
Professor Blitzstein received his PhD in Mathematics from Stanford University, and has taught Statistics 110: Introduction to Probability at Harvard since 2006. His research interests include inference for network data, foundational issues in statistics and data science, and education.Read more
Professor Meng received his PhD in Statistics from Harvard University, and he is the founding editor in chief of the Harvard Data Science Review. His research interests include statistical theory and principles for data science, philosophical and foundational issues in statistics, and uncertainty assessments.Read more
The project team are the driving force behind the DSDSE project. They are responsible for designing, building, and overseeing the production of all educator and learner resources.
The advisory board is a select group of professors, educators, and industry experts who review learning resources to ensure their scientific accuracy and that the relevant data science skills are covered.
LabXchange is proud to collaborate with the Teaching Institute for Excellence in STEM (TIES) on the DSDSE project. TIES is dedicated to making STEM accessible to all learners by connecting, collaborating, and catalyzing dynamic STEM ecosystems. TIES connects LabXchange with teachers nationwide to ensure that these data science resources meet the needs of today's educators.