2026· E3S Web of Conferences· 0 citations· 4 references
TL;DR
The architectural evaluation demonstrates that WA Daksha provides an accessible and scalable framework for automating realtime academic services, facilitating multi-user interaction among students, lecturers, and the public.
Abstract
This study introduces WA Daksha, an academic chatbot on WhatsApp, linked with Gemini AI, designed to facilitate intelligent academic service automation inside the Faculty of Engineering at Universitas Negeri Surabaya. The study concentrates on analysis and design at Technology Readiness Level 1-3, where system readiness is evaluated through structural requirement validation and expert-based architectural mapping. This process generates a verified system architecture, knowledge base structure, conversation flow, and use case model. The suggested system employs a hybrid conversational methodology that integrates rule-based routing, knowledge-based retrieval using Retrieval-Augmented Generation, and generative AI answers. The design comprises client, platform integration, application, data, and infrastructure layers to guarantee modularity and scalability. The chatbot offers three primary services: academic information, FAQ support, and AI-generated dynamic inquiries via WhatsApp chat. The knowledge base amalgamates institutional academic data, administrative protocols, and contextual AI processing to enhance response precision and dependability. The architectural evaluation demonstrates that WA Daksha provides an accessible and scalable framework for automating realtime academic services, facilitating multi-user interaction among students, lecturers, and the public. This research advances the creation of AI-driven academic service assistants in higher education and promotes SDG 4 by enhancing access to inclusive and high-quality education via intelligent digital academic services.
The study successfully validated that the intelligent chatbot efficiently bridges communication barriers, automates repetitive administrative inquiries, and improves service accessibility, confirming that the application is highly usable, practical, and effective as an inclusive, assistive communication tool.
Gil G. Dialogo, Hershey Alburo-Abugadie, Enrico C. Lucero· International journal of com...· 0 citations
The study concludes that AI-powered chatbot systems offer a substantive remedy to institutional communication inefficiencies and recommends full deployment alongside continuous model retraining using current institutional data.
Ulysses Chinenyeaka Ebizie· International Journal of Com...· 0 citations
A madrasah profile website integrated with a rule-based chatbot to enhance the effectiveness of academic information services and is capable of improving access to academic information.
Amelia Nurhayati, Sulidar Fitri, H. Rubiani· International Journal Educat...· 0 citations
International and transfer student check-in processes involve complex, multi-step workflows that can be streamlined with artificial intelligence (AI). This paper presents the design and implementation of an AI-driven check-in agent that automates student onboarding tasks in a university setting. The agent integrates a graphical user interface (GUI) with AI capabilities to guide students through login/authentication, document uploads, advisor assignment based on region, course pre-selection, and real-time status tracking. We provide a comprehensive literature review of similar systems in the U.S. and globally, highlighting how institutions have leveraged chatbots and AI for admissions and orientation. The system’s architecture is described with a technical focus on its Python-based implementation (Tkinter for GUI, PIL for imaging), web integration through Jupyter Notebook compatibility, and open-source API utilization (including BeeWare for cross-platform deployment). We detail each system component and discuss security measures (compliance with FERPA, GDPR) to protect educational data privacy. Challenges such as user adoption, multilingual support, and integration with cloud services are examined, along with future enhancements like machine learning-driven personalization. The paper concludes with expected benefits in institutional efficiency and student satisfaction, positioning the AI check-in agent as a valuable contribution to smart campus initiatives.
Sahar Bukhari· Journal of Climate Innovatio...· 0 citations
The internet and the growth in internet users have undoubtedly influenced the evolution of chatbot development and adoption. Various industries are increasingly adopting Artificial Intelligence (AI) and chatbot technologies to manage customer interactions and enhance customer service. As these industries increase the deployment of AI chatbot to support their customers and improve their user-experience, its therefore significant for them to understand the knowledge-centric service delivery. This study investigates the knowledge-centric quality service and responsiveness of a rule-based WhatsApp chatbot implemented by a South African mobile telecommunications service provider in resolving customer queries. The study adopted a mono-method approach within the interpretivism paradigm, were qualitative insights gathered through thematic analysis of interviews with three employees and a further platform evaluation. The chatbot immediately replies and presents the main menu with various options for the user to select. The matrix shows how the chatbot performed in each main menu task/item relative to usability, accuracy, performance, and interactive responsiveness. Findings highlight the importance of ongoing performance monitoring and iterative improvements in AI-driven knowledge interface design to align with evolving customer expectations and industry benchmarks for service quality. This study contributes to the growing discourse on AI-driven customer knowledge-centric service solutions in South African mobile telecommunications and other industries by offering a comprehensive framework for evaluating and enhancing chatbot effectiveness. This research paper position chatbots as a knowledge-mediation interface that translates organizational information into task-oriented exchanges, shaping escalation pathways, retention of operational know how and customer experience.
Sithembiso Khumalo, Tryphosa B. Mashigo, Wafeequa Ben· European Conference on Knowl...· 0 citations
Pilot test results indicate adequate average response times, thematic and temporal diversity of authors and robust data structuring, confirming its viability as an applicable prototype and advancing the integration of generative AI into library services.
Manuel Blázquez-Ochando, J. Prieto-Gutiérrez, María-Antonia Ovalle-Perandones· Library hi tech· 0 citations