Potential Abstract:
Indigenous knowledge systems have long been marginalized in educational settings, often dismissed in favor of more dominant Western perspectives. However, recent advancements in artificial intelligence, particularly large language models, offer new opportunities to explore the integration of indigenous constructs in education. Drawing on cognitive science theories, this research examines the potential benefits of incorporating indigenous knowledge into visualization practices within educational settings. Through an interdisciplinary approach, this study seeks to bridge the gap between traditional educational practices and emerging technologies, aiming to create more culturally responsive and inclusive learning environments. By leveraging the power of large language models, we aim to develop innovative visualization tools that can better represent and communicate indigenous knowledge systems to learners. Ultimately, this research aims to contribute to a more equitable and diverse educational landscape by recognizing the value of indigenous constructs and integrating them into mainstream educational practices.
Potential References:
- A new visualization approach to re-contextualize indigenous knowledge in rural Africa
- Spatio-temporal visualisation and data exploration of traditional ecological knowledge/Indigenous knowledge
- Explainability for large language models: A survey
- CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models
- Halueval: A large-scale hallucination evaluation benchmark for large language models
