DEVELOPMENT OF AN EDUCATIONAL CHATBOT WITH A CONTEXTUAL INTENT SYSTEM ON THE DIALOGFLOW PLATFORM

Abstract

In the context of digital transformation in higher education, the development of intelligent agents capable of maintaining continuous and effective interaction with students is becoming increasingly relevant. This article presents a complete life cycle of the creation of the contextual chatbot “Pytayko z PIITU” for the Department of Software Engineering and Intelligent Control Technologies of NTU “KhPI”. The chatbot is designed to provide quick and intuitive access to information about academic procedures, communication channels, scholarships, documents, and other common questions related to students' interaction with the department and its website. The system was developed using the Dialogflow platform with Telegram integration and Google Cloud Functions as the fulfillment handler. The core of the system is a structured multi-level intent architecture, where each intent group corresponds to a thematic category such as admissions, documents, or course schedules. This allows the bot to maintain conversation context, ensure precise routing of requests, and reduce ambiguity in user interaction. The prototyping model was selected as the life cycle methodology due to the need for active user feedback and iterative improvement. Based on the analysis of the departmental website and survey data from students, an intent system was created that organizes user queries by categories, each with its own fallback intent and context-based clarification mechanisms. Special attention was paid to the dynamic distribution of queries using webhook logic and centralized reusable intent blocks. The article presents the development algorithm, intent architecture, testing process, and analysis of interaction history. The testing phase included multiple validation cycles, real-time sessions via Telegram, and the assessment of fallback effectiveness. The final implementation achieved a high accuracy rate (~91%) and low error percentage (~3%), demonstrating the feasibility of using Dialogflow for educational automation scenarios. The chatbot architecture supports future scalability and provides 24/7 support for student inquiries without additional administrative workload.