https://bit.ly/DataDunkers
The program consists of learning activities designed to explore how to find meaning in data, primarily using open data from the NBA and WNBA. Students engage in data analysis by defining a question, collecting, cleaning, and analyzing data, and effectively communicating results. Beyond this, the initiative serves as a launchpad for global competencies, such as critical thinking and problem solving, and discovering career pathways within the realm of data science.
Key Components | Activities, Tools, and Techniques |
---|---|
Learn Data Science through basketball | Leverage basketball statistics from both the NBA and the WNBA, with an emphasis on those of Pascal Siakam Build student understanding of data science through Python and Jupyter Notebooks |
Differentiated Learning | All students are provided with the opportunity to be successful with coding and Jupyter Notebooks regardless of level of readiness Learn essential concepts and apply them to real-world scenarios |
Design Thinking Process | Engage in the design thinking process (empathize, ideate, prototype, and test) Promote global competencies (communication, collaboration, creativity, critical thinking, and problem solving) |
Inquiry (Personal Projects) |
Explore data sets through basketball or other domains of interest Encourage student voice and choice to build both digital and data science skills Amplify creativity and personalization |
Career Opportunities | Seek new opportunities in the field Discover and explore career pathways and opportunities in data science |
For questions or further information, please contact DataDunkers@Dell.com.