Inability to regulate affective states can impact one's capacity to engage in higher-order thinking like scientific reasoning with game-based learning environments. Many efforts have been made to build affect-aware systems to mitigate the potentially detrimental effects of negative affect. Yet, gaps in research exist since accurately capturing and modeling affect as a state that changes dynamically over time is methodologically and analytically challenging. In this paper, we calculated multilevel mixed effects growth models to assess whether seventy-eight participants’ (n = 78) time engaging in scientific reasoning (via logfiles and eye gaze) were related to time facially expressing confused, frustrated, and neutral states (via facial recognition software) during game-based learning with Crystal Island. The fitted model estimated significant positive relations between the time learners facially expressed confusion, frustration, and neutral states and time engaging in scientific-reasoning actions. The time individual learners facially expressed frustrated, confused, and neutral states explained a significant amount of variation in time engaging in scientific reasoning. Our finding emphasize that individual differences and agency may play a important role on relations between affective states, their dynamics, and higher-order cognition during game-based learning. Designing affect-aware game-based learning environments that track the dynamics within individual learners’ affective states may best support cognition.

中文翻译：

---

基于游戏的学习过程中的情感动态和认知


无法调节情感状态可能会影响一个人进行高阶思维的能力，例如在基于游戏的学习环境中进行科学推理。人们已经做出了许多努力来构建情感感知系统，以减轻负面情感的潜在有害影响。然而，研究中存在差距，因为准确捕获和建模影响作为一种随时间动态变化的状态在方法论和分析上都具有挑战性。在本文中，我们计算了多级混合效应增长模型，以评估 78 名参与者 (n = 78) 参与科学推理（通过日志文件和眼睛注视）的时间是否与面部表达困惑、沮丧和中立状态的时间相关（在水晶岛的游戏学习过程中通过面部识别软件）。拟合模型估计了学习者面部表达困惑、沮丧和中立状态的时间与参与科学推理活动的时间之间的显着正相关关系。个体学习者面部表达沮丧、困惑和中立状态的时间解释了参与科学推理的时间的显着变化。我们的发现强调，在基于游戏的学习过程中，个体差异和代理可能对情感状态、情感状态动态和高阶认知之间的关系发挥重要作用。设计基于情感感知的游戏学习环境来跟踪个体学习者情感状态的动态可能最好地支持认知。