LumiCHAT: An Expert-Based Mental Health Support Chatbot for Students

This study developed and evaluated an expert-based mental health support chatbot designed to provide accessible, confidential, and responsive assistance to students of Tagoloan Community College experiencing emotional distress, academic pressure, and psychological concerns. The system employed Artificial Intelligence and Natural Language Processing through RASA, supported by Laravel and React.js, to deliver empathetic conversations, assess risk levels, recommend coping strategies, and activate referral mechanisms to guidance counselors when necessary. Using the Agile Software Development Life Cycle, the platform integrated key features such as anonymous interaction, bilingual communication, automated appointment scheduling, and secure data handling compliant with the Data Privacy Act of 2012. System testing and usability evaluation using the System Usability Scale confirmed that the application is functional, user-friendly, and effective in reducing barriers caused by stigma, limited access to counseling services, and hesitation to seek help. The results demonstrate that the system enhances institutional mental health support by promoting early intervention, strengthening student-counselor communication, and fostering emotional well-being through a safe, inclusive, and technology-driven platform, contributing to a more responsive mental health support system within the academic environment.