Enhancing Student Motivation and Competencies via the WWH Teaching Method: A Case Study on the NoSQL Database Course

NoSQL databases are vital for modern big data applications, yet traditional teaching methods struggle with lagging content, insufficient practice, and low student engagement. To address these issues, this paper proposes the WWH-integrated teaching method “Why learn, What learn, How learn” for a NoSQL database course. WWH combines three core approaches: the general–special method, which structures knowledge from foundational concepts to specialized technologies; the comparative method, which contextualizes NoSQL value via real-scenario analysis; and the theory–practice combination method, which links concepts to hands-on tasks, supplemented by the problem-guidance and key-highlighting strategies. A quasi-experiment with two cohorts (80 students each; 2023 cohort as control, 2024 as experimental) validated WWH. Quantitative results showed significant improvements: theoretical exam scores rose by 9.2 points (t(158) = 9.21, p < 0.001) and experimental scores by 10.3 points (t(158) = 7.92, p < 0.001), and classroom discussion rates increased from 45.2% to 82.7% (χ2(1) = 28.90, p < 0.001). Qualitative analysis of student essays and project reports further confirmed deeper conceptual understanding, stronger tradeoff awareness, and enhanced knowledge integration in the experimental cohort. This study provides an evidence-based, student-centered framework for modernizing NoSQL instruction, better preparing students for industry data management needs.