It is challenging to utilize learning analytic technologies to examine gameplay log data for game-embedded assessment in the field of game-based learning. Analytical approaches based on a new perspective focusing on complicated contextual data are imperative in the current scenario. A relatively new concept called precision education, which focuses on individual learning and provides personalized and timely intervention to different learners, can be regarded as a new perspective for game-based learning. Additionally, the order of knowledge acquisition in the learning environment is a kind of learning path extracted from the contextual information of in-game behavior logs. Therefore, in this study, the authors propose a new analytical approach to identify learning path patterns and elucidate the features of these patterns for an educational game they developed. The statistical analysis shows that learners with diverse learning path patterns have different learning effects, suggesting that the learning path is an important factor in precision education. The practice of using the explanation method to examine the proposed approach can help us understand learners' knowledge acquisition and provide evidence for enhancing the accuracy of precision education and improving the quality of the educational game. The findings are expected to contribute to both game-based learning and precision education.