Teaching Data Storytelling as Data Literacy

Fuente: ERIC Institute of Education Sciences
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Main Authors: Kate McDowell, Matthew J. Turk
Format: Recurso educativo Open Access
Language:en
Published: 2024
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author Kate McDowell
Matthew J. Turk
author_facet Kate McDowell
Matthew J. Turk
Kate McDowell
Matthew J. Turk
collection Education Resources Information Center
contents Teaching Data Storytelling as Data Literacy Kate McDowell Matthew J. Turk Story Telling Information Literacy Social Justice Social Problems Feedback (Response) Reflection Instruction Undergraduate Students Graduate Students Data Interpretation Information Science Education Library Science Purpose: Data storytelling courses position students as agents in creating stories interpreted from data about a social problem or social justice issue. The purpose of this study is to explore two research questions: What themes characterized students' iterative development of data story topics? Looking back at six years of iterative feedback, what categories of data literacy pedagogy did instructors engage for these themes? Design/methodology/approach: This project examines six years of data storytelling final projects using thematic analysis and three years of instructor feedback. Ten themes in final projects align with patterns in feedback. Reflections on pedagogical approaches to students' topic development suggest extending data literacy pedagogy categories -- formal, personal and folk (Pangrazio and Sefton-Green, 2020). Findings: Data storytelling can develop students' abilities to move from being consumers to creators of data and interpretations. The specific topic of personal data exposure or risk has presented some challenges for data literacy instruction (Bowler et al., 2017). What "personal" means in terms of data should be defined more broadly. Extending the data literacy pedagogy categories of formal, personal and folk (Pangrazio and Sefton-Green, 2020) could more effectively center social justice in data literacy instruction. Practical implications: Implications for practice include positioning students as producers of data interpretation, such as role-playing data analysis or decision-making scenarios. Social implications: Data storytelling has the potential to address current challenges in data literacy pedagogy and in teaching critical data literacy. Originality/value: Course descriptions provide a template for future data literacy pedagogy involving data storytelling, and findings suggest implications for expanding definitions and applications of personal and folk data literacies.
format Recurso educativo Open Access
id eric_EJ1424118
institution ERIC Institute of Education Sciences
language en
publishDate 2024
record_format eric
spellingShingle Teaching Data Storytelling as Data Literacy
Kate McDowell
Matthew J. Turk
Story Telling
Information Literacy
Social Justice
Social Problems
Feedback (Response)
Reflection
Instruction
Undergraduate Students
Graduate Students
Data Interpretation
Information Science Education
Library Science
Teaching Data Storytelling as Data Literacy Kate McDowell Matthew J. Turk Story Telling Information Literacy Social Justice Social Problems Feedback (Response) Reflection Instruction Undergraduate Students Graduate Students Data Interpretation Information Science Education Library Science Purpose: Data storytelling courses position students as agents in creating stories interpreted from data about a social problem or social justice issue. The purpose of this study is to explore two research questions: What themes characterized students' iterative development of data story topics? Looking back at six years of iterative feedback, what categories of data literacy pedagogy did instructors engage for these themes? Design/methodology/approach: This project examines six years of data storytelling final projects using thematic analysis and three years of instructor feedback. Ten themes in final projects align with patterns in feedback. Reflections on pedagogical approaches to students' topic development suggest extending data literacy pedagogy categories -- formal, personal and folk (Pangrazio and Sefton-Green, 2020). Findings: Data storytelling can develop students' abilities to move from being consumers to creators of data and interpretations. The specific topic of personal data exposure or risk has presented some challenges for data literacy instruction (Bowler et al., 2017). What "personal" means in terms of data should be defined more broadly. Extending the data literacy pedagogy categories of formal, personal and folk (Pangrazio and Sefton-Green, 2020) could more effectively center social justice in data literacy instruction. Practical implications: Implications for practice include positioning students as producers of data interpretation, such as role-playing data analysis or decision-making scenarios. Social implications: Data storytelling has the potential to address current challenges in data literacy pedagogy and in teaching critical data literacy. Originality/value: Course descriptions provide a template for future data literacy pedagogy involving data storytelling, and findings suggest implications for expanding definitions and applications of personal and folk data literacies.
title Teaching Data Storytelling as Data Literacy
topic Story Telling
Information Literacy
Social Justice
Social Problems
Feedback (Response)
Reflection
Instruction
Undergraduate Students
Graduate Students
Data Interpretation
Information Science Education
Library Science
url https://eric.ed.gov/?id=EJ1424118