Potential Abstract:
Abstract: This research study focuses on reframing ethnocentric perspectives in education through the application of eigenvectors, utilizing a collaborative platform like GitHub to challenge and transform reified practices. Ethnocentrism, the tendency to evaluate other cultures based on one’s own cultural norms, can hinder educators’ ability to provide inclusive and culturally responsive instruction. By incorporating eigenvectors, a mathematical concept used in data analysis and machine learning, this study seeks to investigate how educators can identify and address implicit biases in their teaching practices. Additionally, the use of GitHub as a collaborative platform aims to facilitate transparency, accountability, and peer feedback in the process of reframing ethnocentric perspectives.
Through a mixed-methods approach, this study will collect quantitative data on educators’ ethnocentric beliefs and qualitative data on their experiences with reframing these beliefs through eigenvectors and GitHub. Findings from this research will contribute to the field of education by offering practical strategies for addressing ethnocentrism in instructional practices and promoting diversity, equity, and inclusion in educational settings.
Potential References:
- Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated
- Reward Frustration Can Selectively Amplify Negative Own-Race Biases
- The social construction of African-Caribbean identities: A Black British male perspective
- Spaces of cross-cultural encounter
- Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.
