Preliminary Results from Integrating Chatbots and Low-Code AI in Computer Science Coursework
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Orka Kalds
College:
The Dorothy and George Hennings College of Science, Mathematics, and Technology
Major:
Computer Science
Faculty Research Advisor(s):
Yulia Kumar
Abstract:
This study presents initial outcomes from incorporating chatbots and low-code artificial intelligence (AI) tools into computer science (CS) education. Its aim is to enhance student engagement, facilitate specific learning opportunities, and streamline administrative tasks. The primary focus has been on instructors' experiences with chatbots and students' interactions with low-code AI. Data collection involved observational analysis, followed by statistical evaluation. Initial findings indicate that instructors experienced increased efficiency in handling tasks, chatbots significantly enhanced student engagement in coding classes and research activities.
Tools like ChatGPT, Gemini, Claude AI and Microsoft Copilot facilitated comprehension of complex concepts, fostering creativity and innovation in problem solving. Low-code AI platforms effectively bridged the gap between theoretical knowledge and practical skills in CS and AI, offering an accessible entry point for students with varied backgrounds In conclusion, the study examines implications for teaching methodologies, curriculum development, and the future trajectory of AI-enhanced learning environments in STEM education.