Atenas, J;
Havemann, L;
Timmermann, C;
(2023)
Reframing data ethics in research methods education: a pathway to critical data literacy.
International Journal of Educational Technology in Higher Education
, 20
(1)
, Article 11. 10.1186/s41239-023-00380-y.
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Abstract
This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research methods syllabi from across the disciplines, as well as 80 syllabi from data science programmes to understand how or if data ethics was taught. We also reviewed 12 data ethics frameworks drawn from different sectors. Finally, we reviewed an extensive and diverse body of literature about data practices, research ethics, data ethics and critical data literacy, in order to develop a transversal model that can be adopted across higher education. To promote and support ethical approaches to the collection and use of data, ethics training must go beyond securing informed consent to enable a critical understanding of the techno-centric environment and the intersecting hierarchies of power embedded in technology and data. By fostering ethics as a method, educators can enable research that protects vulnerable groups and empower communities.
Type: | Article |
---|---|
Title: | Reframing data ethics in research methods education: a pathway to critical data literacy |
Location: | Switzerland |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1186/s41239-023-00380-y |
Publisher version: | https://doi.org/10.1186/s41239-023-00380-y |
Language: | English |
Additional information: | © 2023 BioMed Central Ltd. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Critical data literacy, Curriculum design, Data ethics, Data literacy, Ethics, Higher education, Research methods |
UCL classification: | UCL |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10166000 |
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