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On traversing the data landscape: Introducing APIs to data‐science students
Author(s) -
Fergusson Anna,
Wild Chris J.
Publication year - 2021
Publication title -
teaching statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.425
H-Index - 13
eISSN - 1467-9639
pISSN - 0141-982X
DOI - 10.1111/test.12266
Subject(s) - computer science , personalization , variety (cybernetics) , curiosity , key (lock) , data science , human–computer interaction , multimedia , world wide web , psychology , artificial intelligence , social psychology , computer security
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.