理解大学生学习动机与情绪的关系对于教育实践有重要意义。目前该领域的研究主要使用实验室范式和回顾式问卷等传统方法，所得结论缺少在日常情境下的效度验证和不同情境间的区分对比。因此，本研究希望在真实日常生活中展开对学习动机和情绪关系的探索，使用动态评估的方法，从情绪的主观体验和生理唤醒两种成分的路径出发，区分学习和非学习情境的特异性；纳入10分类情绪的视角，具体刻画特定细分情绪的特异性；同时为学习动机提升的应用实践提供了一套智能化自助式干预方案。 本研究招募了80名大学生参与者，使用日重现法和可穿戴生理测量设备追踪采集参与者在连续10个工作日中情绪评分和心率特征，对比学习情境和非学习情境下情绪的认知和生理两种成分与学习动机的关系，并以情绪为靶点开发一个基于智能设备的日常情境学习动机提升干预方案。研究1a基于主观报告情绪数据，研究了日常情境下自我报告的10类别情绪和学习动机之间的关系，发现情绪和学习动机的关系在学习情境下更强，初步支持了情境特异性和情绪特异性的存在。研究1b加入心率数据，探索生理特征作为情绪组成成分之一是否与学习动机的表达有关。通过构建不同情境下学习动机的生理心理回归模型发现心率和情绪的交互项对学习动机具有独特的贡献。研究2基于研究1的结论，从情绪入手开发了一个为期10个工作日的日常学习动机干预方案，验证了该方案对参与者有积极的情绪调节作用，且干预效果受到个体的尽责性、神经质和学习动机特质水平影响。 本研究使用日常情境研究方法采集了个体在真实生活中情绪状态的心理生理数据，结论扩展了现有研究对情绪和学习动机关系的理解，提出了情境特异性和情绪特异性的解释角度，结合生理唤醒的测量提供了更为客观、动态的视角。在理论机制方面，本研究基于日常情境生理心理测量为情绪和学习动机关系提供了实证支持；在实践应用方面，为基于智能设备进行自助式学习动机提升干预提供了一套方案设计和效果验证工具。
Understanding the relationship between college students' learning motivation and emotion is of great significance to educational practice. At present, the research in this field mainly uses traditional methods such as laboratory paradigm and retrospective questionnaire, and the conclusions obtained lack the validity verification in daily life and the comparison between different contexts. Therefore, this study attempts to explore the relationship between learning motivation and emotion in real daily life by ambulatory assessment, distinguish the specificity of learning and non-learning contexts based on two emotional components of self-reported emotion and objective physiological arousal, describing the specificity of specific emotions, and supplementing a set of online self-service learning motivation improvement intervention program. In order to further study the relationship between learning motivation and emotion in daily life, this study recruited 80 participants, and used day reconstruction method and wearable physiological measurement device to track and collect participants' self-reported emotional states and heart rate in 10 working days. This study compared the relationship between cognitive and physiological components of emotion and learning motivation in learning and non-learning context, and developed a daily learning motivation intervention program based on mobile devices with emotion as the target. Study 1a investigated the relationship between self-reported 10-category emotions and learning motivation in daily life and found that the relationship between emotion and learning motivation was stronger in learning contexts, preliminarily supporting context specificity and emotion specificity. Study 1b constructed a physiological and psychological regression model of learning motivation in different contexts, and found that the interaction of heart rate and self-reported emotion had a unique contribution to learning motivation. Based on the conclusions of Study 1, Study 2 designed a 10-day learning motivation intervention program and verified that the program has a positive effect on emotion regulation. The intervention effect is related to the individual's level of conscientiousness, neuroticism and learning motivation traits. This study uses daily research methods to collect psychological and physiological data of individuals' emotional states in real life, expands the conclusions on the relationship between emotion and learning motivation, and proposes a new interpretation angle of context specificity and emotion specificity. More objective and dynamic findings from the perspective of physiological arousal are complemented by wearable physiological measurement. In conclusion, the results of this study provide empirical support for the mechanism of the psychophysiological representation of learning motivation, and also provide a program design and effect verification tool for the application of self-service learning motivation enhancement based on mobile devices.
