Combining AI Tools, Low-Code Platforms, and Product Development in ICT Education: A Reflective Study on Educational and Practical Outcomes

Artificial Intelligence (AI) and low-code/no-code (LCNC) platforms are reshaping the processes of product development, offering new pathways for efficiency, accessibility, and creativity. By reducing technical barriers, these technologies enable novel approaches to problem-solving and innovation. This research examines the design and implementation of a university-level course structured around the CDIO (Conceive, Design, Implement, Operate) framework, leveraging AI-powered LCNC platforms. The course introduces foundational software development skills, including system design, UI/UX principles, and the creation of innovative solutions for everyday problems in a practical and accessible manner. As a project-based course, it emphasizes interpersonal and strategic skills, fostering personal and team productivity, as well as small-scale project management using an adapted agile approach. By integrating AI-driven tools into the curriculum, the course bridges human creativity and technological capabilities, enabling students to rapidly ideate, design, and deliver concrete solutions with a user-centered mindset. This study reflects on the outcomes of the first implementation of the course from both educator and student perspectives. It focuses on the course’s impact on collaboration, creativity, and problem-solving in small-scale software development projects, while also considering whether AI-assisted LCNC platforms provide a more accessible entry point into programming. The findings lay the groundwork for future research, including a planned AI-assisted programming course, which will further investigate how these tools can make programming more approachable for beginners. From the students’ perspective, the course highlighted the potential of AI-powered tools to reduce cognitive load, enable rapid prototyping, and foster multidisciplinary teamwork. However, challenges arose with the restricted functionality of free versions, particularly when students attempted to scale their projects or access advanced features. Despite these limitations, many students reported increased confidence in their ability to contribute to technology-driven projects, even with limited prior technical experience. Instructors observed that the course significantly accelerated the development process, enabling students to focus more on user-centric design and strategic decision-making. However, they emphasized the need to address tool limitations through careful project scoping and creative solutions. Ethical discussions on AI usage, data privacy, and societal impacts were particularly impactful, encouraging students to critically reflect on the broader implications of their work and the practical realities of deploying such tools in professional contexts. The course also underscored the importance of equitable access to resources and a deeper understanding of licensing models for LCNC platforms. While the free versions lowered barriers to entry, they presented challenges in replicating the functionality required for real-world project deployment. Balancing the course’s educational goals with these constraints became a central consideration, preparing students to navigate similar challenges in professional environments. In conclusion, the initial implementation of the course demonstrated the potential of AI-powered LCNC platforms to enhance human factors in product development by streamlining workflows and fostering collaboration. At the same time, it highlighted the importance of adaptive teaching practices to meet diverse student needs and prepare them for practical challenges. These findings provide a foundation for refining future iterations of the course.