TY  - JOUR
JF  - Research in Learning Technology
KW  - critical data literacy; data justice; education; creative pedagogies
A1  - Atenas, Javiera
A1  - Havemann, Leo
A1  - Nerantzi, Chrissi
ID  - discovery10203677
N2  - This paper offers guidance on employing open and creative methods for co-designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. Through innovative approaches, we aim to enhance participation in learning, research and policymaking, fostering a comprehensive understanding of the impact of data and AI whilst promoting inclusivity in critical data and AI literacy. By reflecting on the Higher Education (HE) context, we advocate for active participation and co-creation within data ecosystems, amplifying the voices of educators and learners. Our methodology employs a triangulation model: initially, we conduct interpretative analyses of literature to gauge best practices for curriculum development in HE; then, we examine frameworks in data justice and ethics to identify principles and skills applicable to undergraduate, postgraduate and academic development programs; finally, we explore proposals for critical, creative, ethical, open and innovative ideas for educators to integrate data and AI into their practice.
SN  - 2156-7069
PB  - Association for Learning Technology
UR  - https://doi.org/10.25304/rlt.v32.3296
N1  - © The Author(s), 2025. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/
TI  - Critical and creative pedagogies for artificial intelligence and data literacy: an epistemic data justice approach for academic practice
AV  - public
Y1  - 2025/01/16/
VL  - 32
ER  -