Virtual Booth

Abstract:

Learners without programming experience often struggle to translate everyday ideas into functional digital solutions, even when no-code tools are available. The No-Code Solution Development Framework (NSDF) addresses this gap through a structured teaching and learning approach that guides learners beyond prototype creation to testing, user feedback and review of the development process. NSDF comprises three phases—Build, Sustain and Assure—and seven steps: Problem, Design, Build, Test, Deploy, Feedback and Validate. Implemented using AWS PartyRock, the framework guides learners to identify everyday needs, design solutions, construct AI-powered prototypes through natural-language prompts, test and share applications, incorporate user feedback and review adherence to the development process. Its novelty lies in extending solution development beyond deployment through the Sustain and Assure phases, packaged as a repeatable pedagogy for learners who build through natural-language prompting rather than code. Content validation by three senior lecturers yielded an item-level content validity index (I-CVI) of 1.00 for all seven steps, with 94.4% of framework-level ratings at “strongly agree”. A questionnaire completed by 29 students after NSDF-guided activities indicated favourable perceptions of AWS PartyRock-based learning, with mean agreement of 78.2% for perceived usefulness and 71.7% for perceived impact, while 89.7% would recommend AWS PartyRock to other students. Faculty-wide participation involving over 500 students in the AWS CendekiAwan 2026 National AI Competition, including a category win, provides further evidence of implementation reach. These preliminary findings suggest that NSDF offers a practical and transferable pathway for engaging non-technical learners in AI-enabled solution development, with potential for licensing as a teaching module and wider educational and community adoption.

Keywords: No-Code Development; Generative AI; AWS PartyRock; Teaching and Learning Framework; AI Literacy