Abstract: In this project, we developed a student data chatbot using Dialogflow, a cloud-based natural language processing platform. The chatbot was designed to assist students in finding information about their grades, schedule and other relevant academic data. The project involved defining intents, entities, and responses within the Dialogflow Agent console, testing the chatbot with sample queries, and integrating it with various platforms such as Facebook Messenger and Slack.
The results of this project showed that the student data chatbot was successful in providing students with quick and easy access to the information they needed. The chatbot was able to accurately interpret and respond to student queries in natural language, and the integration with various platforms allowed for seamless communication between the student and the chatbot. The development of a student data chatbot using Dialogflow offers a promising solution for improving student engagement and access to academic information. Further improvements could be made by incorporating machine learning algorithms to enhance the chatbot's ability to understand and respond to student queries.
Keywords: Student data chatbot, Dialogflow, Natural language processing, Intents, Entities, Responses, Grades, Schedule, Academic data, Student engagement, Access to academic information.
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DOI:
10.17148/IJARCCE.2023.12611
