Personalization and Contextualization of Large Language Models For Improving Early Forecasting...

[PDF] arxiv.org

Generative AI for Education (GAIED): Advances, Opportunities, and Challenges

P Denny, S Gulwani, NT Heffernan, T Käser… - arXiv preprint arXiv …, 2024 - arxiv.org
This survey article has grown out of the GAIED (pronounced" guide") workshop organized by
the authors at the NeurIPS 2023 conference. We organized the GAIED workshop as part of a …
被引用次数：29 相关文章 所有 4 个版本
[PDF] arxiv.org

Students Rather Than Experts: A New AI For Education Pipeline To Model More Human-Like And Personalised Early Adolescences

Y Ma, S Hu, X Li, Y Wang, S Liu, KH Cheong - arXiv preprint arXiv …, 2024 - arxiv.org
The capabilities of large language models (LLMs) have been applied in expert systems
across various domains, providing new opportunities for AI in Education. Educational …
被引用次数：1 相关文章 所有 2 个版本
[PDF] arxiv.org

Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning

EG Gado, T Martorella, L Zunino… - arXiv preprint arXiv …, 2024 - arxiv.org
Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student
answers to provide immediate and customized instruction. However, recent research has …
相关文章 所有 2 个版本