| dc.contributor.author | Shilibekova, Aigerim | en_US |
| dc.date.accessioned | 2025-10-10T12:36:42Z | |
| dc.date.available | 2025-10-10T12:36:42Z | |
| dc.date.issued | 2025-07 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/163138 | |
| dc.description.abstract | The paper introduces the concept of localized intelligence, a pedagogical principle that frames instructional design with AI as a situated and context-responsive practice, guided by human expertise. This approach challenges assumptions of AI scalability and oZers a replicable model for designing inclusive, culturally aligned professional learning experiences, with implications for multilingual faculty development across global contexts. | en_US |
| dc.title | Localized Intelligence: Designing an AI-Enhanced OER Course for Faculty Development in a Low-Resource Language Context | en_US |
| dc.type | Article | en_US |
| dc.relation.journal | 2025 MIT AI and Education Summit | |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |