  This study investigates the use of Artificial Intelligence (AI)-powered,
multi-role chatbots as a means to enhance learning experiences and foster
engagement in computer science education. Leveraging a design-based research
approach, we develop, implement, and evaluate a novel learning environment
enriched with four distinct chatbot roles: Instructor Bot, Peer Bot, Career
Advising Bot, and Emotional Supporter Bot. These roles, designed around the
tenets of Self-Determination Theory, cater to the three innate psychological
needs of learners - competence, autonomy, and relatedness. Additionally, the
system embraces an inquiry-based learning paradigm, encouraging students to ask
questions, seek solutions, and explore their curiosities.
  We test this system in a higher education context over a period of one month
with 200 participating students, comparing outcomes with conditions involving a
human tutor and a single chatbot. Our research utilizes a mixed-methods
approach, encompassing quantitative measures such as chat log sequence
analysis, and qualitative methods including surveys and focus group interviews.
By integrating cutting-edge Natural Language Processing techniques such as
topic modelling and sentiment analysis, we offer an in-depth understanding of
the system's impact on learner engagement, motivation, and inquiry-based
learning.
  This study, through its rigorous design and innovative approach, provides
significant insights into the potential of AI-empowered, multi-role chatbots in
reshaping the landscape of computer science education and fostering an
engaging, supportive, and motivating learning environment.
