This study investigated changes in motivation, self‐efficacy beliefs, and a range of emotions, including enjoyment, hope, pride, curiosity, anxiety, boredom, apathy, confusion, and shame, from a complex dynamic systems theory (CDST) perspective over a 2‐year period in the Hungarian English as a Foreign Language (EFL) context. Using the same questionnaire, we collected data four times throughout 4 semesters from 101 participants studying English in two Hungarian high schools. For data analysis, we used latent growth curve modeling (LGCM) to detect the group‐level changes in learners’ motivation, self‐efficacy, and emotions. We also employed dynamic cluster analysis to identify trends in learners’ trajectories regarding these variables. In our panel data, linear models described the data well concerning the ought‐to second language (L2) self, language learning experience, boredom, apathy, and confusion, and for enjoyment, curiosity, anxiety, and shame, nonlinear models had the best fit. We could also identify trajectories depicting attractor states and learner paths that featured influences of perturbations.

中文翻译：

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语言学习者情感的变化：复杂的动态系统理论视角


本研究从复杂动态系统理论 （CDST） 的角度调查了匈牙利英语作为外语 （EFL） 背景下 2 年期间动机、自我效能信念和一系列情绪的变化，包括享受、希望、自豪、好奇、焦虑、无聊、冷漠、困惑和羞耻。使用相同的问卷，我们在 4 个学期中收集了 4 次来自两所匈牙利高中学习英语的 101 名参与者的数据。对于数据分析，我们使用潜在生长曲线模型 （LGCM） 来检测学习者动机、自我效能感和情绪的组级变化。我们还采用动态聚类分析来确定学习者对这些变量的轨迹趋势。在我们的面板数据中，线性模型很好地描述了关于应该第二语言 （L2） 自我、语言学习体验、无聊、冷漠和困惑的数据，而对于享受、好奇、焦虑和羞耻，非线性模型最适合。我们还可以识别描绘吸引子状态的轨迹和以扰动影响为特征的学习者路径。