E-Learning中学习者情感补偿方法的研究

For the prevalent phenomenon of valuing knowledge while ignoring emotional elements in e-learning, this project draws the rule and trend of negative emotion varation, to compensate the negative emotion, and it aims to improve the learning efficiency of e-learners. The major research work includes: first, analysing the emotion illiteracy in e-learning, we try to explore emotional transition model and present the e-learner’s emotional compensation mechanism in the network environment as the theoretical basis of e-learning, by combining the theories of human-human interaction in response to features of the negative emotion in e-learning. We try to set up the e-learners' emotional fusion model by studying the relationship between the learners’ internal elements, such as personality, interest, emotion and so on. On this basis,we analyze the e-learners' emotional compensation strategy based on the technique of trust and collaborative recommend , and put forward the emotional compensation model and algorithm. Fllowing, we give compensation evaluation feedback algorithm for e-learners by data mining. Combining the theories and methods mentioned above, we would test as well as verify them on the platform of network education. .The significance of the research includes the following points. First,we can find the mode of emotional changes and show the evolution rules and key factors of emotions. Second, emotion as an important non-intellectual factors influences cognitive activity, and the learner’s cognitive activity is adapted relative to emotion compensation. Last, the application of emotional interaction and compensation can improve the learning efficiency. .Expected achievements include: publishing six pieces of high level papers, training three students and a development system for emotional interaction and compensation..

本项目针对e-Learing中普遍存在的“重知轻情”现象，研究学习者情感演变规律、情感补偿方法，目标是提高学习者的学习效率。主要研究内容包括：一、针对e-Learning中不同学习场景下情感缺失的原因，基于学习者情感演化特点，研究网络环境中学习者情感变迁模式，提出e-Learning中学习者情感补偿机理；二、基于情感的分类与度量，研究个性、情感、兴趣之间相互关系，建立个性-情感-兴趣融合模型；三、提出网络环境下学习者情感补偿模型、算法及补偿评价反馈算法，并研制情感补偿系统，以此对项目成果进行测试和应用。项目的研究意义在于：一、发现学习者情感变迁模式，揭示情感演化规律形成机理与关键影响因素；二、情感作为非智力因素对认知活动映射，学习者情感补偿方法的研究有助于自适应调节其认知活动；三、应用情感交互补偿可提高学习者的学习效率。预期成果包括：发表高水平论文6篇；培养硕士3名；研制情感补偿系统。

情感作为教学活动中的一种非常重要的非智力因素，与认知紧密相连，它既可以直接对个体的认知行为产生重要影响，也可以通过影响学习动机而间接地影响个体的认知行为。如：积极情感可以提高个体的积极性和思维认知能力，消极情感会影响人们的动机、决策过程及记忆的水平。e-Learning系统中因时空分离使得师生、生生之间难以感受对方情感和心智状态，缺乏必要的情感交流，普遍存在“重知轻情”问题，导致学习者情感缺失、学习热情减退，严重影响学习效率。因此，在网络学习过程中有必要监控学习者的情感变化趋势，适时调节和干预学习者的负面情感，并进行补偿。本项目针对e-Learing中普遍存在的“重知轻情”现象，研究学习者情感演变规律、情感补偿方法，目标是提高学习者的学习效率。主要研究内容包括：一、针对e-Learning中不同学习场景下情感缺失的原因，基于学习者情感演化特点，研究网络环境中学习者情感变迁模式，提出e-Learning中学习者情感补偿机理；二、基于情感的分类与度量，研究个性、情感、兴趣之间相互关系，建立个性-情感-兴趣融合模型；三、提出网络环境下学习者情感补偿模型、算法及补偿评价反馈算法，并研制情感补偿系统，以此对项目成果进行测试和应用。项目的研究意义在于：一、发现学习者情感变迁模式，揭示情感演化规律形成机理与关键影响因素；二、情感作为非智力因素对认知活动映射，学习者情感补偿方法的研究有助于自适应调节其认知活动；三、应用情感交互补偿可提高学习者的学习效率。