International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 06 | Jun 2025
p-ISSN: 2395-0072
www.irjet.net
AI-POWERED CHATBOTS FOR REAL-TIME ACADEMIC SUPPORT AND COUNSELING Arun Kumar Maurya1, Deepshikha2 1Master of Technology, Computer Science and Engineering, Lucknow Institute of Technology, Lucknow, India 2Assistant Professor, Department of Computer Science and Engineering, Lucknow Institute of Technology,
Lucknow, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The rapid evolution of Artificial Intelligence
face increasing student populations and limited staff availability, chatbots offer a scalable, cost-effective, and always-available solution. They can deliver immediate assistance, resolve frequently asked questions, and reduce faculty workload, while also providing a confidential platform for students to express academic anxieties or emotional concerns. The convergence of AI, education, and mental health technologies reflects a broader move toward inclusive, personalized, and tech-driven learning ecosystems.
(AI) has opened new avenues for enhancing student support in higher education. This research presents the design, development, and evaluation of an AI-powered chatbot system aimed at delivering real-time academic guidance and emotional counseling to students in technical disciplines. The system integrates Natural Language Processing (NLP), Machine Learning (ML), and sentiment analysis to understand user queries, recognize emotional states, and generate empathetic, context-aware responses. Developed using the Rasa framework and trained on both academic FAQs and emotionally labeled datasets, the chatbot offers dual functionality: addressing subject-related questions and providing basic psychological support. A mixed-method evaluation was conducted involving 40 student participants, with metrics including intent recognition accuracy (91%), task completion rate (89%), sentiment detection accuracy (89.5%), and a System Usability Scale (SUS) score of 81.3. Results indicate high effectiveness in resolving queries and strong user satisfaction, affirming the system's viability as a first-level support tool. Limitations such as language restrictions and sarcasm detection are discussed, along with future directions including multilingual support, voice interaction, and deeper emotional modeling. This study demonstrates how intelligent chatbots can enrich student engagement and well-being in digital learning ecosystems.
Figure-1: Application of AI Chatbots in Education.
1.2 Problem Statement
Key Words: AI Chatbots, Academic Support, Sentiment Analysis, Real-Time Counseling, Natural Language Processing, Higher Education, User-Centered Design.
Despite the availability of academic advisors and counseling services, students frequently encounter barriers in accessing timely and personalized support. Traditional systems are constrained by human limitations such as fixed office hours, limited counselor-to-student ratios, and inconsistent availability. These challenges are further compounded by psychological barriers—students often hesitate to seek help due to fear of judgment, cultural stigma, or discomfort in face-to-face interactions. As a result, many academic and emotional concerns go unaddressed, contributing to stress, decreased academic performance, and even dropouts. Furthermore, existing digital solutions like discussion forums and FAQs lack interactivity and contextual understanding, making them inadequate for students seeking dynamic support. There is a pressing need for an intelligent, empathetic, and responsive system that can bridge the support gap by providing on-demand academic guidance and emotional reassurance in real-time.
1. INTRODUCTION 1.1 Background and Importance Over the past decade, the integration of Artificial Intelligence (AI) in education has grown rapidly, transforming the traditional academic landscape. Among various AI applications, chatbots have emerged as a promising tool to address the evolving needs of learners. These AI-powered conversational agents, equipped with natural language processing (NLP) and machine learning (ML), are capable of simulating human interaction to provide automated, intelligent, and context-aware responses. The educational sector, particularly in higher education, is leveraging these tools to support students in both academic and psychological domains. As institutions
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