This innovative practice full paper delves into the transformative role of Learning Assistants (LAs) in Computer Science education, focusing on enhancing student engagement and improving learning outcomes. The LA model, which aligns with Vygotsky's Social Constructivist Learning Theory, fosters an environment of student-centered learning and social interaction. In a pilot study conducted in Spring 2024 at a public university, the LA program is implemented in two computer science courses. A quasi-experimental design has been used to evaluate the impact of LA-facilitated team activities on student learning outcomes. The study compares a control group receiving traditional instruction with an experimental group participating in LA-facilitated team activities. The experimental group engaged in weekly team-based activities, guided by LAs and faculty, to reinforce class concepts and promote collaboration among team members. Student engagement and learning have been evaluated using feedback from students and LAs collected through Discussion Boards (DBs). Preliminary findings suggest that LA-facilitated in-class activities promote active learning and enhance problem-solving skills. LAs provide valuable support and guidance to students, particularly those struggling to understand complex concepts. The study tested a working model of AIELA, an innovative AI-powered chatbot that assists human LAs in supporting students through knowledge-reinforcing questions and multimodal data analysis, powered by OpenAI API's gpt-4-turbo model. This research is a step towards embracing the challenges of modern CS education, inspiring further innovation in this critical field. The findings will benefit educators seeking innovative strategies to enrich student engagement and learning in engineering and computing disciplines.
