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arxiv: 2510.18385 · v2 · pith:FNLRSTOInew · submitted 2025-10-21 · 💻 cs.HC

Khelte Khelte Shikhi: A Proposed HCI Framework for Gamified Interactive Learning with Minecraft in Bangladeshi Education Systems

classification 💻 cs.HC
keywords percentschoolslearningframeworkminecraftruraldeploymenteducation
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Game-based learning shows real promise for engaging students in well-resourced classrooms, but what about the millions who study in schools with far fewer opportunities? We propose a practical framework for bringing Minecraft Education Edition into Bangladesh's 130,000 schools, where 55 percent lack reliable internet, rural areas receive only 12 to 16 hours of electricity per day, computer access in rural schools is just 8 percent, and student-teacher ratios can reach 52:1. Our approach addresses these constraints directly through three deployment tiers: cloud-based multiplayer for urban schools with stable infrastructure (15 percent), local-area network (LAN) solutions with optional solar power for semi-urban schools (30 percent), and fully offline, turn-based modes using refurbished hardware for rural contexts (55 percent). We provide eight curriculum-aligned Minecraft worlds with complete Bangla localization, covering topics from Lalbagh Fort reconstruction to monsoon flood simulation. The interface supports first-time users through progressive complexity, culturally familiar metaphors rooted in local farming and architecture, and accessibility features such as keyboard-only controls and 200 percent text scaling. We outline evaluation benchmarks including 15 percent learning gains, 70 percent transfer-task mastery, System Usability Scale scores above 70, and a per-student cost below two dollars per hour. Although not yet empirically validated, this work synthesizes game-based learning theory, HCI principles, and contextual analysis to offer implementable specifications for pilot testing in resource-constrained settings. It is presented as a design-oriented conceptual framework rather than a field deployment, providing an implementation-ready blueprint for future empirical validation.

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