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Affective Computing at the Ateneo de Manila

机译：马尼拉竞技场的情感计算

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In recent years, the Affective Computing Group of the Ateneo de Manila University has tried to arrive at computationally tractable models of affect within learning situations. ?We studied affect's role in learning, its dynamics, and the ways in which it might be automatically detected from student interactions with computer-based educational software. ?We gathered human observations as well as student interaction logs and analyzed these using statistical and data mining techniques. We found that the affective states of boredom and confusion lead to non-learning behaviors. ?We found that boredom tended to persist, regardless of learning environments. ?We are current working on developing models of student affect in order to automatically detect constructs such as boredom, confusion, and frustration. Other current work focuses on the detection of student carelessness and on remediating non-literal programming errors.
机译：近年来，马尼拉大学（Aeneo de Manila University）情感计算小组（Affective Computing Group）试图在学习情况下得出影响力的易计算的模型。我们研究了情感在学习中的作用，动态以及从学生与基于计算机的教育软件的交互中自动检测出情感的方式。我们收集了人类观察以及学生互动日志，并使用统计和数据挖掘技术对其进行了分析。我们发现无聊和困惑的情感状态导致了非学习行为。 ？我们发现，无论学习环境如何，无聊都会持续存在。我们目前正在开发学生情感模型，以自动检测无聊，困惑和沮丧等结构。当前的其他工作集中在检测学生的粗心和纠正非文字编程错误上。

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