On Traversing the Data Landscape: Introducing APIs to Data‐science Students
Teaching statistics(2021)
Abstract
The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data science being fun to teach and fun to learn. We advocate curiosity-driven, exploratory learning for pursuing these goals. Our illustrations use tasks embedded in contexts that teenagers can relate to, provide visual rewards for computational actions, use rich data-contexts, and integrate statistical and computational thinking. They provide engaging introductions to modern data sourced from databases via Application Programming Interfaces (APIs) that are accessible to a broad range of students and facilitate student personalization for investigation. We provide in-depth discussion of teaching strategies that heavily involve questioning and student tinkering supported by graphical-user interfaces that enable students to interact with the data sources rapidly in multiple ways.
MoreTranslated text
Key words
teaching,APIs,computational thinking,data harvesting,data wrangling,exploratory data analysis,statistical thinking,teaching statistics
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined