Virtual Booth

The teaching of programming in higher education often faces challenges such as large class sizes, limited personalized feedback, and the difficulty students experience in independently debugging and improving their code. SmartCode Tutor (SCT) is a structured, AI-enhanced framework designed to guide educators in integrating artificial intelligence tools effectively into programming courses. Its objective is to enhance student learning outcomes, streamline lecturer workload, and promote self-directed coding proficiency. The framework comprises four components: structured learning phases, strategic AI integration, automated feedback and progress monitoring, and ethical AI use with plagiarism management. To operationalize the framework, CodeLift.AI serves as the implementation model, offering an AI-powered ecosystem with code assistance, intelligent debugging, automated grading, and analytics dashboards. This workflow enables a continuous learning loop where students code, receive AI suggestions, debug errors, and resubmit until the correct output is achieved, while lecturers gain actionable insights through data analytics. The solution is cost-effective as it leverages existing AI tools and can be integrated into current learning management systems without significant infrastructure investment, reducing long-term training and assessment costs. Its commercialization potential lies in adaptation for industry training, licensing as an educator training module, and integration as a premium AI-assisted teaching plugin for various LMS platforms. By combining structured pedagogy with cutting-edge AI, SCT with CodeLift.AI offers a scalable, adaptable, and future-ready approach to programming education that benefits students, educators, institutions, and the wider digital skills ecosystem.

Keywords: SmartCode Tutor, CodeLift.AI, AI-assisted learning, programming education, teaching framework