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Framework to describe constructs of academic emotions using ontological descriptions of statistical models

机译:使用统计模型的本体描述描述学术情绪构造的框架

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Abstract Many studies have been conducted during the last two decades examining learner reactions within e-learning environments. In an effort to assist learners in their scholastic activities, these studies have attempted to understand a learner’s mental states by analyzing participants’ facial images, eye movements, and other physiological indices and data. To add to this growing body of research, we have been developing the intelligent mentoring system (IMS), which performs automatic mentoring by using an intelligent tutoring system (ITS) to scaffold learning activities and an ontology to provide a specification of learner’s models. To identify learner’s mental states, the ontology operates on the basis of the theoretical and data-driven knowledge of emotions. In this study, we use statistical models to examine constructs of emotions evaluated in previous psychological studies and then produce a construct of academic boredom. In concrete terms, we develop ontological descriptions of academic boredom that are represented with statistical models. To evaluate the validity and utility of the descriptions, we conduct an experiment to obtain subjective responses regarding learners’ academic emotions in their university course and describe them as instances on the basis of the ontological descriptions.
机译:摘要在过去的二十年中,已经进行了许多研究,以检查学习者在电子学习环境中的反应。为了帮助学习者进行学业活动,这些研究试图通过分析参与者的面部图像,眼睛运动以及其他生理指标和数据来了解学习者的心理状态。为了增加这一不断发展的研究范围,我们一直在开发智能辅导系统(IMS),该系统通过使用智能辅导系统(ITS)来支持学习活动和本体以提供学习者模型规范来执行自动辅导。为了识别学习者的心理状态,本体基于情绪的理论和数据驱动知识进行操作。在这项研究中,我们使用统计模型来检查在先前的心理学研究中评估的情绪构造,然后得出学术无聊的构造。具体而言,我们开发了以统计模型表示的学术厌倦的本体论描述。为了评估描述的有效性和实用性,我们进行了一项实验,以获取关于学习者在大学课程中的学术情感的主观反应,并根据本体论描述将其描述为实例。

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