Embracing AI in Education: Understanding the Surge in Large Language Model Use by Secondary Students
원문 초록
The impressive essay writing and problem-solving capabilities of large language models (LLMs) like OpenAI's ChatGPT have opened up new avenues in education. Our goal is to gain insights into the widespread use of LLMs among secondary students to inform their future development. Despite school restrictions, our survey of over 300 middle and high school students revealed that a remarkable 70% of students have utilized LLMs, higher than the usage percentage among young adults, and this percentage remains consistent across 7th to 12th grade. Students also reported using LLMs for multiple subjects, including language arts, history, and math assignments, but expressed mixed thoughts on their effectiveness due to occasional hallucinations in historical contexts and incorrect answers for lack of rigorous reasoning. The survey feedback called for LLMs better adapted for students, and also raised questions to developers and educators on how to help students from underserved communities leverage LLMs' capabilities for equal access to advanced education resources. We propose a few ideas to address such issues, including subject-specific models, personalized learning, and AI classrooms.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model
Specification-based Security Evaluation of Real-World Agents Tool-Calling under Long-Horizon Context Tasks
Assay2Mol: large language model-based drug design using BioAssay context
Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery
Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.