Modelling affect expression and recognition in an interactive learning environment
Modelling affect expression and recognition in an interactive learning environment
复制标题
建模影响交互式学习环境中的表达和识别
DOI：
10.1504/ijlt.2009.028807
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
James C. Lester
中科院分区：
文献类型：
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作者：
Scott W. McQuiggan;James C. Lester
情感推理在智能辅导系统中具有重要的潜力。将情感推理融入到教学决策能力中，可以使学习环境创造出个性化的体验，这些体验可以根据学生个人不断变化的参与程度、兴趣、动机和自我效能感进行动态调整。因为生理反应是由情感变化直接触发的，生物反馈数据，如心率和皮肤电反应，可以用来推断情感变化，并结合情境。本文探讨了一种为学习环境诱导情感模型的方法。归纳方法检验了模拟学生的自我效能感和同伴代理的同理心的任务。综上所述，这些关于叙事学习环境中情感的研究表明，通过观察情境背景和学生的生理反应，可以建立情感构念模型。
Affective reasoning holds significant potential for intelligent tutoring systems. Incorporating affective reasoning into pedagogical decision-making capabilities could enable learning environments to create customised experiences that are dynamically tailored to individual students' ever-changing levels of engagement, interest, motivation and self-efficacy. Because physiological responses are directly triggered by changes in affect, biofeedback data such as heart rate and galvanic skin response can be used to infer affective changes in conjunction with the situational context. This article explores an approach to inducing affect models for a learning environment. The inductive approach is examined for the task of modelling students' self-efficacy and empathy for companion agents. Together, these studies on affect in a narrative learning environment suggest that it is possible to build models of affective constructs from observations of the situational context and students' physiological response.