NajahniBot: An Intelligent Chatbot aware of Educational Context for Adaptive Learning

The application of natural language to improve learners' interaction with intelligent tutoring systems is demonstrated to be beneficial. In particular, advances in adaptive learning enable a new way of interaction that accelerates insight from existing educational context, thereby contributing to the process of learning. This work aims at researching the application of chatbots in intelligent tutoring system. We propose a modular chatbot architecture for question answering of learning progression, featuring social dialogue (small talk), improved by individual learning preferences. This system has been implemented as a personal agent NajhniBot to assist students in learning a course of algorithmic. Its implementation includes the training of machine learning models and natural language understanding algorithms in a humanlike interface. The effectiveness of the system has been validated through an experiment.