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Facilitating API lookup for novices learning data wrangling using thumbnail graphics
Author(s) -
Lovisa Sundin,
Nourhan Sakr,
Juho Lein,
Quintin Cutts
Publication year - 2021
Publication title -
foundations of data science
Language(s) - English
Resource type - Journals
ISSN - 2639-8001
DOI - 10.3934/fods.2021032
Subject(s) - thumbnail , computer science , graphics , lookup table , computer graphics (images) , information retrieval , artificial intelligence , programming language , image (mathematics)
With the rising demand for data science skills, the ability to wrangle data programmatically becomes a crucial barrier. In this paper, we discuss the centrality of API (application programming interface) lookup to data wrangling, and how an ontology-structured command menu could facilitate it. We design thumbnail graphics as visual alternatives to explaining data wrangling operations and use a survey to validate their quality. We furthermore predict that thumbnail graphics make the menu more navigable, improving lookup efficiency and performance. Our predictions are tested using Slice N Dice, an online data wrangling tutorial platform that collects learner activity. It includes both non-programmatic and programmatic data wrangling exercises. Participants from a multi-institutional sample ( n = 200) were randomly assigned the tutorial either with or without thumbnail graphics. Our results show that thumbnail graphics reduce the need for clarifications, thereby assisting API lookup for novices learning data wrangling. We further present some negative results regarding performance gain and follow up with a discussion on why the differences are subtle and how they can be improved. Last but not least, we complement our statistical results with a qualitative study where we receive positive feedback from our participants on the design and helpfulness of the thumbnail graphics.

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