# Human Experts' Evaluation of Generative AI for Contextualizing STEAM Education in the Global South

arXiv: https://arxiv.org/abs/2511.19482 · HTML: https://mlsanity.com/paper/2511.19482/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 40 references that are in the map.
- First posted on arXiv 23 Nov 2025.

## Builds on (most cited first, 8 of 8)

- [Generative AI](https://mlsanity.com/paper/2309.07930/) (2023)
- [Human-Centred Learning Analytics and AI in Education: a Systematic Literature Review](https://mlsanity.com/paper/2312.12751/) (2023)
- [Using ChatGPT for Science Learning: A Study on Pre-service Teachers' Lesson Planning](https://mlsanity.com/paper/2402.01674/) (2024)
- [Transforming Teachers' Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practices](https://mlsanity.com/paper/2410.03018/) (2024)
- [Collaborative Learning with Artificial Intelligence Speakers (CLAIS): Pre-Service Elementary Science Teachers' Responses to the Prototype](https://mlsanity.com/paper/2401.05400/) (2023)
- [Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability,Reproducibility, and Practicality](https://mlsanity.com/paper/2406.08845/) (2024)
- [Generative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis](https://mlsanity.com/paper/2411.00631/) (2024)
- [Designing Culturally Aligned AI Systems For Social Good in Non-Western Contexts](https://mlsanity.com/paper/2509.16158/) (2025)

## Built on by (most cited first, 2 of 2)

- [Prompt Engineering for Responsible Generative AI Use in African Education: A Report from a Three-Day Training Series](https://mlsanity.com/paper/2601.06121/) (2026)
- [Education-centered critical policy analysis of AI: Ghana's AI strategy as a case](https://mlsanity.com/paper/2608.16910/) (2026)

## Abstract (arXiv)

STEAM education in many parts of the Global South remains abstract and weakly connected to learners sociocultural realities. This study examines how human experts evaluate the capacity of Generative AI (GenAI) to contextualize STEAM instruction in these settings. Using a convergent mixed-methods design grounded in human-centered and culturally responsive pedagogy, four STEAM education experts reviewed standardized Ghana NaCCA lesson plans and GenAI-generated lessons created with a customized Culturally Responsive Lesson Planner (CRLP). Quantitative data were collected with a validated 25-item Culturally Responsive Pedagogy Rubric assessing bias awareness, cultural representation, contextual relevance, linguistic responsiveness, and teacher agency. Qualitative reflections provided additional insight into the pedagogical and cultural dynamics of each lesson. Findings show that GenAI, especially through the CRLP, improved connections between abstract standards and learners lived experiences. Teacher Agency was the strongest domain, while Cultural Representation was the weakest. CRLP-generated lessons were rated as more culturally grounded and pedagogically engaging. However, GenAI struggled to represent Ghana's cultural diversity, often producing surface-level references, especially in Mathematics and Computing. Experts stressed the need for teacher mediation, community input, and culturally informed refinement of AI outputs. Future work should involve classroom trials, broader expert participation, and fine-tuning with Indigenous corpora.