Towards Automatic Boundary Detection for Human-AI Collaborative Hybrid Essay in Education

This paper proposes a boundary detection method to identify transition points between human-written and AI-generated content in hybrid essays, constructing a dataset by having ChatGPT fill in incomplete student essays and evaluating detection approaches. The work addresses academic integrity concerns by detecting AI-assisted writing in educational assignments rather than assuming essays are entirely human or AI-generated.

The recent large language models (LLMs), e.g., ChatGPT, have been able to generate human-like and fluent responses when provided with specific instructions. While admitting the convenience brought by technological advancement, educators also have concerns that students might leverage LLMs to complete their writing assignments and pass them off as their original work. Although many AI content detection studies have been conducted as a result of such concerns, most of these prior studies modeled A

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