Towards AI-assisted Board Game-based Learning: Assessing LLMs in Game Personalisation

This paper evaluates the ability of large language models (ChatGPT, Copilot, Claude) to personalize board games for educational use by suggesting modifications aligned with specific classroom contexts and learning objectives, comparing AI-generated suggestions against human expert recommendations.

Board games are used in different educational settings to promote acquisition of disciplinary content, soft skills, foster engagement towards learning content, and sustain motivation. However, designing and conducting effective educational activities with board games requires instructional design skills, knowledge of games, as well as the ability to align the player's internal goals with the learning objectives. Board game-based learning (bGBL) design includes choosing appropriate games and pers

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