Designing Child-Centric AI Learning Environments: Insights from LLM-Enhanced Creative Project-Based Learning
<|reference_start|>Designing Child-Centric AI Learning Environments: Insights from LLM-Enhanced Creative Project-Based Learning: Project-based learning (PBL) is an instructional method that is very helpful in nurturing students' creativity, but it requires significant time and energy from both students and teachers. Large language models (LLMs) have been proven to assist in creative tasks, yet much controversy exists regarding their role in fostering creativity. This paper explores the potential of LLMs in PBL settings, with a special focus on fostering creativity. We began with an exploratory study involving 12 middle school students and identified five design considerations for LLM applications in PBL. Building on this, we developed an LLM-empowered, 48-hour PBL program and conducted an instructional experiment with 31 middle school students. Our results indicated that LLMs can enhance every stage of PBL. Additionally, we also discovered ambivalent perspectives among students and mentors toward LLM usage. Furthermore, we explored the challenge and design implications of integrating LLMs into PBL and reflected on the program. By bridging AI advancements into educational practice, our work aims to inspire further discourse and investigation into harnessing AI's potential in child-centric educational settings.<|reference_end|>
@article{zha2024designing,
    title={Designing Child-Centric AI Learning Environments: Insights from
  LLM-Enhanced Creative Project-Based Learning},
    author={Siyu Zha, Yuehan Qiao, Qingyu Hu, Zhongsheng Li, Jiangtao Gong,
  Yingqing Xu},
    journal={arXiv preprint arXiv:2403.16159},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.16159},
    primaryClass={cs.HC}
}