Gamification for Learning Java Programming: Design and Implementation of Java Realm

This study presents the design and development of JavaRealm, a web-based gamified learning application for teaching Java programming to undergraduate IT students at a South African university. Adopting a design science research methodology, the work addresses high attrition and disengagement in introductory programming by translating learner requirements into a functional software artefact. The paper concludes at the design validation phase, and its authors explicitly note that summative evaluation of learning outcomes and competency gains has not yet been conducted.

Design validation drew on quantitative questionnaires completed by 20 participants and qualitative focus groups with six participants, all purposively sampled and enrolled in or having completed Java courses, with 75% in third-year or postgraduate study. Respondents strongly favoured immediate feedback, with 95% agreement (M = 4.80, SD = 0.52), and showed broad support for engagement, perceived value of rewards, and intent to use. Preferences regarding competition and collaboration were notably heterogeneous, a pattern the authors term the "Competition Paradox," which motivated opt-in leaderboards and complementary social features. Qualitative analysis additionally surfaced demands for professional-grade tooling resembling Visual Studio Code, progressive code scaffolding to manage cognitive load, and a non-game aesthetic.

The authors are careful to frame these results as exploratory and preliminary, given the small sample and subgroup sizes, which limit statistical power and generalisability. The study's implications centre on a design blueprint suggesting that gamification in complex cognitive domains should prioritise scaffolding, authenticity, structured progression, and learner autonomy over simple points and badges. Its claims about psychological mechanisms drawn from Self-Determination Theory and Cognitive Load Theory remain theoretical interpretations pending empirical confirmation in larger, multi-institutional studies.