@inproceedings{1b962e9273a9473695e943b2409b0c1e,
title = "Cipherbot: An AI-Powered Educational Assistant for Conversational Q\&A about Course Material",
abstract = "Education is one of the areas where artificial intelligence (AI) is having a dramatic impact. In this paper, we present Cipherbot, an AI-powered educational assistant designed to deliver scalable, personalized learning experiences through conversational interfaces as an exemplar for the design of such systems. This paper presents the technical architecture, development methodology, and dual-interface functionality of Cipherbot for educators and students. We evaluate Cipherbot in an eight-week deployment with sixteen undergraduate participants. Cipherbot demonstrated strong performance in enhancing educational interactions, achieving a 95.8\% task completion rate. Usability assessments yielded high satisfaction scores, 78\% on the System Usability Scale and 76\% on the Chatbot Usability Questionnaire. Despite these positive outcomes, a gradual decline in student engagement over time highlights the need for dynamic and immersive learning strategies. Findings emphasize the critical role of sustaining engagement and enhancing learning outcomes within emerging educational technologies that rely on AI.",
keywords = "Chatbot, Dialogue learning, LLMs, Q\&A",
author = "Jinan Azem and Jung, \{Soon Gyo\} and Johanne Medina and Aldous, \{Kholoud K.\} and Joni Salminen and Jansen, \{Bernard J.\}",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025 ; Conference date: 25-11-2025 Through 28-11-2025",
year = "2025",
doi = "10.1109/FLLM67465.2025.11390928",
language = "English",
series = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "660--667",
editor = "Kai Erenli and Christian Guetl and Yaser Jararweh and Jim Jansen",
booktitle = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",
address = "United States",
}