Preliminary Results from Integrating Chatbots and Low-Code AI in Computer Science Coursework
Yulia Kumar, Anjana Manikandan, J. Jenny Li, Patricia A. Morreale · 2024
The study investigates the application of chatbots and low-code AI tools in advancing Computer Science (CS) education, concentrating on the CS AI Explorations course and the AI for ALL extracurricular programs. It addresses two main research questions: firstly, the impact of chatbots on student growth and engagement in undergraduate research, and secondly, the potential of low-code AI platforms to bridge the gap between theoretical and practical AI skills. Conducted during the 2022–2024 academic years, this research combines case studies and empirical data to evaluate the effectiveness of integrating these technologies into conventional teaching methodologies. The preliminary findings suggest a significant transformative potential for chatbots and low-code AI, offering valuable insights for future educational strategies and developing more dynamic, interactive learning environments. Notably, there was a significant increase in students' involvement in research. Future investigations will elucidate the long-term effects of integrating chatbots and low-code AI.