Data science education can help broaden participation in computer science (CS) because it provides rich, authentic contexts for students to apply their computing knowledge. Data literacy, particularly among underrepresented students, is critical to everyone in this increasingly digital world. However, the integration of data science into K-12 schools is nascent, and the pedagogical training of CS teachers in data science remains limited. Our research-practice partnership modified an existing data science unit to include two pedagogical techniques known to support minoritized students: rich classroom discourse and personally-relevant problem-solving. This paper describes the iterative design process we used to revise and pilot this new data science unit.
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Using Student and Teacher Feedback to Modify CS Curriculum
The CS education community has over the years recognized the importance of data science by including it in the seminal K-12 CS Framework. The move is prompted by research that shows data science is a great tool to broaden participation in CS because it offers students an opportunity to apply their computing knowledge to socially relevant problems. Broadening participation, particularly among underrepresented students, is critical to the future health and stability of the field. However, data science is still a relatively new in the context of K-12 schools and few CS teachers are pedagogically
trained in data science. In order to test whether or not data science can be a tool to increase student representation in CS and help schools implement more data science curriculum, our project partnered with a local school district to modify an existing data science unit. This work explores the process of how our research practice partnership tackled the development of the new data science unit.
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- Award ID(s):
- 2122485
- PAR ID:
- 10433549
- Date Published:
- Journal Name:
- SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
- Volume:
- 2
- Issue:
- March 2023
- Page Range / eLocation ID:
- 1420 to 1420
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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