SQL Adventure: Where Bloom’s Taxonomy Meets Gamification to Foster SQL Skills in Emerging Developers

Abstract

Game-based learning (GBL) has demonstrated significant potential in teaching complex computational subjects such as programming, web development, and database management. This research presents SQL Adventure, a gamified learning environment that integrates learning analytics (LA) with Bloom’s Taxonomy to scaffold SQL skill development. Learning analytics, defined as the systematic measurement, collection, analysis, and reporting of learner interaction data, enables performance monitoring, prediction of learning outcomes, and delivery of personalized, data-driven feedback. SQL Adventure employs narrative-driven tasks, drag-and-drop query construction, adaptive hints, and gamification elements (points, badges, and levels) to enhance engagement while capturing fine-grained behavioral data. The analytics engine classifies learners based on accuracy, error patterns, and time-on-task, generating adaptive learning pathways and external resource recommendations (e.g., NPTEL modules). By aligning SQL exercises with Bloom’s cognitive levels and embedding real-time analytics, the system promotes deeper conceptual understanding, sustained motivation, and improved problem-solving ability. This study evaluates the platform using the MEEGA+ model and learner performance data, contributing a validated design framework for integrating taxonomy-aligned pedagogy, gamification mechanics, and data-centric feedback into SQL education.