Advancing critical data and AI literacies through authentic and real-world assessment design using a data justice approach

Picasso, Federica, Atenas, Javiera, Havemann, Leo and Serbati, Anna (2024) Advancing critical data and AI literacies through authentic and real-world assessment design using a data justice approach. Open Praxis, 16 (3). pp. 291-310. ISSN 2304-070X

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Abstract

The development of critical data and artificial intelligence (AI) literacy has become a key focus in current discussions in Higher Education, thus it is necessary to develop and advance capacity building, reflectiveness and awareness across disciplines to critically address the possibilities and challenges presented by data and AI. In this paper, through an integrative use of the literature and the review of case studies and best practices in authentic and real world design, we propose a model that develops and enables critical data and AI literacies grounded in citizenship, civic responsibilities, and human centred values, rethinking how we develop knowledge and understanding in our disciplines, and also, in the value of our disciplines to society. The principles of data justice, which acknowledges the growing influence of data, its gathering, and use in society, promoting shared perspectives on how societal problems should be comprehended and addressed.These can provide a useful framework for authentic and real-world assessment design, bridging professional and discipline related knowledge with critical data and AI understanding in alignment with civic and citizenship literacies to examine the challenges we face by the impact of data AI on our societies and democracies. Our exploratory approach examines the relationship between authentic and real-world assessment design and critical data and AI literacy, using data justice as a catalyst for reflection and action to promote a deeper understanding of data and AI ethics through assessment practices that enable educators and students to confidently navigate the complex world of data and AI.

Item Type: Article
Uncontrolled Keywords: AI literacy, data literacy, critical data, artificial intelligence, real-world assessment, authentic assessment, data justice, data ethics, academics, higher education
Subjects: L Education > L Education (General)
L Education > LB Theory and practice of education > LB2300 Higher Education
L Education > LB Theory and practice of education > LB2361 Curriculum
Divisions: Faculty of Arts, Business & Applied Social Science > School of Social Sciences & Humanities
Depositing User: Javiera Atenas
Date Deposited: 02 Sep 2024 09:49
Last Modified: 02 Sep 2024 09:49
URI: https://oars.uos.ac.uk/id/eprint/4079

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