Learning designs that empower: navigating sandbox data science at the intersection of computing, big data and social media
Information and Learning Sciences
ISSN: 2398-5348
Article publication date: 22 August 2024
Issue publication date: 28 October 2024
Abstract
Purpose
There is a need for precollege learning designs that empower youth to be epistemic agents in contexts that intersect burgeoning areas of computing, big data and social media. The purpose of this study is to explore how “sandbox” or open-inquiry data science with social media supports learning.
Design/methodology/approach
This paper offers vignettes from an illustrative youth study case that highlights the pedagogical prospects and obstacles tied to designing for open-ended inquiry with computational data science to access or “scrape” Twitter/X. The youth case showcases how social media can be taken up productively and in ways that facilitate epistemological agency, an approach where individuals actively shape understanding and knowledge-creation processes, highlighting the potentially transformative impact this approach might have in empowering learners to engage productively.
Findings
The authors identify three key affordances for learning that emerged from the illustrative case: (1) flexible opportunities for content-specific domain mastery, (2) situated inquiry that embodies next-generation science practices and (3) embedded computational skill development. The authors discuss these findings in relation to contemporary education needs to broaden participation in data science and computing.
Originality/value
To address challenges in current data science education associated with supporting sustained and productive engagement in computing-based data science, the authors leverage a “sandbox” approach – an original pedagogical framework to support open inquiry with precollege groups. The authors demonstrate how “big data” drawn from social media with high school-aged youth supports learning designs and outcomes by emphasizing learner interests and authentic practice.
Keywords
Acknowledgements
This work was supported in part by a grant from the National Science Foundation (#2137708 for review). Any opinions, findings, conclusions and/or recommendations expressed herein are those of the authors and do not necessarily reflect the views of the National Science Foundation or the University of Texas at El Paso for review. The authors extend their gratitude to Alan Barrera for his efforts in this research.
Citation
Barany, A., Scarola, A.D., Acquah, A., Reza, S.M., Johnson, M.A. and Walker, J. (2024), "Learning designs that empower: navigating sandbox data science at the intersection of computing, big data and social media", Information and Learning Sciences, Vol. 125 No. 10, pp. 794-812. https://doi.org/10.1108/ILS-12-2023-0211
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited