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Perrotta, Carlo – Learning, Media and Technology, 2023
This article proposes a pragmatic approach to data justice in education that draws upon Nancy Fraser's theory. The main argument is premised on the theoretical and practical superiority of a deontological framework for addressing algorithmic bias and harms, compared to ethical guidelines. The purpose of a deontological framework is to enable the…
Descriptors: Data, Justice, Algorithms, Bias
Sotoudeh, Ramina; DiMaggio, Paul – Sociological Methods & Research, 2023
Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…
Descriptors: Algorithms, Simulation, Prediction, Correlation
Thompson, Terrie Lynn; Prinsloo, Paul – Learning, Media and Technology, 2023
Learning analytics offer centralization of a particular understanding of learning, teaching, and student support alongside data-informed insight and foresight. As such, student-related data in higher education can be imagined and enacted as a 'data frontier' in which the data gaze is expanding, intensifying, and performing new meanings and…
Descriptors: Learning Analytics, Data, Activism, Higher Education
Arantes, Janine Aldous; Vicars, Mark – Learning, Media and Technology, 2023
In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and…
Descriptors: Foreign Countries, Homosexuality, LGBTQ People, Data