# "I Would Never Trust Anything Western": Kumu (Educator) Perspectives on Use of LLMs for Culturally Revitalizing CS Education in Hawaiian Schools

arXiv: https://arxiv.org/abs/2501.17942 · HTML: https://mlsanity.com/paper/2501.17942/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jan 2025.

## Built on by (most cited first, 3 of 3)

- [Bridging Cultural Distance Between Models Default and Local Classroom Demands: How Global Teachers Adopt GenAI to Support Everyday Teaching Practices](https://mlsanity.com/paper/2509.10780/) (2025)
- [TVS Sidekick: Challenges and Practical Insights from Deploying Large Language Models in the Enterprise](https://mlsanity.com/paper/2509.26482/) (2025)
- [Identifying Harm in Personalized, Generative AI Systems Requires User-Centered Auditing at the Interaction Level](https://mlsanity.com/paper/2608.14692/) (2026)

## Abstract (arXiv)

As large language models (LLMs) become increasingly integrated into educational technology, their potential to assist in developing curricula has gained interest among educators. Despite this growing attention, their applicability in culturally responsive Indigenous educational settings like Hawai`i's public schools and Kaiapuni (immersion language) programs, remains understudied. Additionally, `Olelo Hawai`i, the Hawaiian language, as a low-resource language, poses unique challenges and concerns about cultural sensitivity and the reliability of generated content. Through surveys and interviews with kumu (educators), this study explores the perceived benefits and limitations of using LLMs for culturally revitalizing computer science (CS) education in Hawaiian public schools with Kaiapuni programs. Our findings highlight AI's time-saving advantages while exposing challenges such as cultural misalignment and reliability concerns. We conclude with design recommendations for future AI tools to better align with Hawaiian cultural values and pedagogical practices, towards the broader goal of trustworthy, effective, and culturally grounded AI technologies.