Double-Edged Sword or Sharp Tool? Designing and Evaluating Triadic LLM-Teacher Collaboration for K-12 Writing at Scale
arXiv:2605.30200v1 Announce Type: new Abstract: The double-edged sword of integrating Large Language Models (LLMs) requires an effective triadic collaboration mechanism among LLMs, teachers and students, especially for K-12 education. By developing a triadic collaboration system to support K-12 writing learning, a multidimensional evaluation framework grounded in Systemic Functional Linguistics and the suggestion trajectory tracing pipeline, this paper contributes a large-scale empirical dataset involving $57,954$ essays from $10,195$ students across $120$ schools over two years. Our findings
The accelerating integration of Large Language Models (LLMs) into education necessitates robust evaluation frameworks to understand their impact and effective implementation, especially in K-12 settings.
This research provides a large-scale empirical study and a framework for integrating LLMs into K-12 writing education, offering critical insights into their real-world utility and challenges.
The understanding of how LLMs can be effectively integrated into K-12 collaborative learning environments is enhanced, moving beyond theoretical discussions to empirical evidence.
- · Educational technology providers leveraging LLMs
- · K-12 students receiving personalized writing support
- · Educators and researchers in AI in education
- · Traditionalists resistant to AI integration in education
- · Educational tools lacking AI integration
Increased adoption and refinement of AI-powered writing assistance tools in K-12 schools.
Curriculum adjustments and teacher training programs will evolve to incorporate triadic LLM-teacher-student collaboration models.
Long-term shifts in pedagogical approaches, potentially leading to more individualized learning pathways and new metrics for student performance.
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Read at arXiv cs.AI