Design and Implementation of NLP-based Conversational CHATBOT Framework in Higher Education

The increasing use of technology is changing the way students learn and absorb information. Hence, educational institutions also need to accelerate their student communication process to draw the attention of this fast-paced generation. The project here aims to harvest better teacher-student relationships and to prepare students for personalised learning by developing a convincing chatbot to assist pupils in their queries related to common operations in numerical base 2 or binary operations with general information operations. Background research on various web applications and chatbot systems was discussed and analysed before the development of the project. Functional and non-functional requirements were assessed on the priority basis and the respective methodology was devised for the project. Python Flask and MongoDB are used for the backend whereas HTML5, CSS3 and jQuery are used for the frontend of the framework. Deployment is done through Heroku Cloud Platform. Moreover, MongoDB Atlas, NLTK, AWS Lambda Functions, AWS Lex, Boto3, Pymongo and Gunicorn are used as Third-Party Tools and Libraries. Various test cases were verified to check for the functional and non-functional requirements completion. A Likert-scale questionnaire survey was done from 60 engineering students who have studied Introduction to Digital Electronics module after the chatbot deployment and the survey responses were recorded and evaluation of the results were generated. The survey concludes that majority of the participants find the chatbot to be extremely useful and the developed framework generates correct responses, and explanations to the questions. Further to the aforementioned points, future study for the project has been proposed in the paper. AI approach can be used to train the chatbot framework and to provide more accurate answers for students in future. Moreover, the framework can be altered to support advanced parsing techniques in future along with an added voice functionality and multi-language support in the chatbot framework.