Games and puzzles play important pedagogical roles in STEM learning. New AI algorithms that can solve complex problems offer opportunities for scaffolded instruction in puzzle solving. This paper presents the ALLURE system, which uses an AI algorithm (DeepCubeA) to guide students in solving a common first step of the Rubik's Cube (i.e., the white cross). Using data from a pilot study we present preliminary findings about students' behaviors in the system, how these behaviors are associated with STEM skills - including spatial reasoning, critical thinking and algorithmic thinking. We discuss how data from ALLURE can be used in future educational data mining to understand how students benefit from AI assistance and collaboration when solving complex problems.

翻译：游戏与谜题在STEM教育中具有重要的教学作用。能够解决复杂问题的新型人工智能算法为谜题求解的支架式教学提供了机遇。本文介绍了ALLURE系统，该系统利用一种人工智能算法（DeepCubeA）指导学生完成魔方求解的常见第一步（即白色十字）。基于一项试点研究的数据，我们展示了学生在系统中的行为模式、这些行为与STEM技能（包括空间推理、批判性思维和算法思维）的关联性。我们探讨了如何利用ALLURE系统的数据，通过未来教育数据挖掘来理解学生在解决复杂问题时如何从人工智能辅助与协作中获益。