Learning from student responses: A domain-independent natural language tutor
Jenny McDonald, Alistair Knott, Richard Zeng, Ayelet Cohen · 2011
Providing timely and individualised feedback to students in large undergraduate classes is problematic. In this paper we describe our approach to creating a simple, surface-based, domain-independent natural language tutor which uses simple machine learning techniques as a step towards resolving this issue. The focus of our efforts was on developing a high-quality tutorial dialogue plan, creating well-designed questions, and building a model of student responses derived from real student data. We present some early evaluation results and briefly outline the opportunities that our approach and the new tutorial dialogue system present. 1