ERIC Number: EJ1446174
Record Type: Journal
Publication Date: 2024
Pages: 19
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-2398-5348
EISSN: EISSN-2398-5356
Learning Designs That Empower: Navigating Sandbox Data Science at the Intersection of Computing, Big Data and Social Media
Amanda Barany; Andi Danielle Scarola; Alex Acquah; Sayed Mohsin Reza; Michael A. Johnson; Justice Walker
Information and Learning Sciences, v125 n10 p794-812 2024
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.
Descriptors: Student Empowerment, Data Science, Social Media, Open Education, Inquiry, Active Learning, Artificial Intelligence, Intersectionality, Instructional Design, High School Students, Student Attitudes, Workshops, Asian American Students, African American Students, Hispanic American Students, White Students, Mathematics Education, Learner Engagement, Authentic Learning
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Publication Type: Journal Articles; Reports - Research
Education Level: High Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: 2137708