Potential Abstract:
In this study, we explore the notion of ethnocentric aesthetics within the context of educational data mining, using a commodified analysis framework. The increasing reliance on data-driven decision-making in education has led to concerns about how ethnocentric biases may be perpetuated and reinforced through the aesthetic choices made in the design and implementation of data mining tools and algorithms. Drawing on critical theories of race, culture, and technology, we examine how these biases manifest in the way educational data is collected, analyzed, and used to inform instructional practices. Through a series of case studies and qualitative analyses, we uncover the ways in which ethnocentric aesthetics shape the outcomes of educational data mining processes and contribute to the reproduction of inequality and injustice in educational systems. Our findings highlight the need for greater attention to the ethical dimensions of data mining in education, and call for a more critical and reflexive approach to the design and implementation of data-driven interventions in diverse educational settings.
Potential References:
- The Mask of Art: Breaking the Aesthetic Contract—Film and Literature
- Celebrating pluralism: Art, education, and cultural diversity
- Materialism, status consumption and consumer ethnocentrism amongst black generation Y students in South Africa
- A theoretical model of factors influencing online consumer purchasing behavior through electronic word of mouth data mining and analysis
- Mitigating inter-and intra-group ethnocentrism: Comparing the effects of culture knowledge, exposure, and uncertainty intolerance
