Exploring AI Conversational Chatbot UX Design: Insights from High School Suha Khalil Assayed , Daniel Woods, Manar Alkahtib , and Khaled Shaalan Abstract Advancements in state-of-the-art models and algorithms for chatbots have significantly driven the growth and evolution of human–computer interaction (HCI) in recent years. As a result, numerous authors are inspired to study the most effective interactive chatbot design that can maximize students’ experiences. Despite the fact that high school is one of the most critical stage in a student’s life, there is a lack of studies that focused on developing effective interactive high school advising chatbots. To address this current gap, this study aims to elicit the main effective features for high school advising chatbot. The authors in this study conducted a semi-structured qual- itative interview with six high school students in UAE and the MAXQDA Analytics software—ver. 22.6.0 is implemented by processing the thematic analysis to study the findings. The results revealed that high school students recommended the same general interaction design characteristics that was derived from the previous system- atic review with emphasizing more into accurate, reliable, and trustworthy short answers with having minimal conversational issues. In addition to that, emotions and empathic factors are less important for high school students. Keywords Chatbot · Human-chatbot interaction · Education · HCI · High school · Qualitative study · User experience 1 Introduction Human-computer interaction (HCI) is a multidisciplinary field that primarily combines psychology and behavioral science with computer and information systems (Chignell et al. 2023; MacKenzie 2024). It explores how people may efficiently communicate with computers to enhance user experiences and meet their needs. HCI This paper was prepared for INF 611 & RES 600, taught by DR. Daniel Woods S. K. Assayed (B) · D. Woods · M. Alkahtib · K. Shaalan The British University in Dubai, Dubai, UAE e-mail: sassayed@gmail.com © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025 K. Al Marri et al. (eds.), BUiD Doctoral Research Conference 2024, Lecture Notes in Civil Engineering 587, https://doi.org/10.1007/978-3-031-84371-6_18 219