Leveraging Emancipatory Narratives in Education through Engineered Approaches with Large Language Models

Potential Abstract:

Abstract: This research article explores the potential of using large language models as an engineered approach to promoting emancipatory narratives in education. Emancipatory narratives are critical for fostering inclusive and equitable learning environments that challenge dominant power structures and enhance student agency and empowerment. However, traditional educational practices often overlook the voices and experiences of marginalized groups, leading to a perpetuation of systemic inequalities. By harnessing the power of large language models, such as GPT-3, this study investigates how these models can be utilized to amplify and center the narratives of historically marginalized students.

The research employs a mixed-methods approach, combining qualitative analysis and experimental design to understand the impact of large language models on student narratives. Through interviews and focus groups, the study explores the experiences and perspectives of students from diverse backgrounds, examining their reactions to engaging with large language models in educational settings. Additionally, the research includes an experimental component where students interact with the large language models to generate and refine their own narratives, providing opportunities for self-expression and critical reflection.

The findings of this research have significant implications for educational practice and policy. By integrating large language models into classroom settings, educators can create opportunities for students to engage with a wide range of narratives, including those that challenge dominant narratives and amplify marginalized voices. This approach has the potential to foster a more inclusive and culturally responsive learning environment, empowering students to share their own experiences and perspectives.

Furthermore, this study contributes to the emerging field of AI in education by examining the ethical considerations and potential risks associated with using large language models in educational settings. By critically analyzing the power dynamics and biases inherent in these models, educators can better navigate their integration into the classroom while minimizing potential harm.

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