Agent based affective tutoring systems: A pilot study

Mao, Xia; Zheng, Lei

doi:10.1016/j.compedu.2010.01.005

Cited by 75 publications

(64 citation statements)

References 13 publications

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“…Mao [14] conducted a study in 2010 to investigate the critical factors affecting student's satisfaction in using ATSs. Their research findings revealed student's attitude toward affective computing, agent tutor's expressiveness, emotion recognition accuracy, number of emotions recognized by agent tutor, pedagogical actions, and easy use of the system have significant influence on student's satisfaction [14] [17].…”

Section: Introductionmentioning

confidence: 99%

“…The affection module needs to increase reasoning ability for these emotional states, so that it can produce the appropriate response from the perspectives of teaching and emotions [13]. ITS refers to detecting the learning and emotional state of students, and provide timely feedback to adjust the student's emotional state of learning [14]. The Tutoring Research Group at the University of Memphis added an emotional component to their ITS AutoTutor, which has attained significant learning gains in deeper level explanations as well as surface knowledge [15].…”

Section: Introductionmentioning

confidence: 99%

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An Affective Learning Interface with an Interactive Animated Agent

Chao

Lin

et al. 2012

2012 IEEE Fourth International Conference on Digital Game and Intelligent Toy Enhanced Learning

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Affective tutoring system (ATS) utilizes emotion recognition techniques to enhance the affective interface of an intelligent tutoring system (ITS). The aim of this study is to improve interest in learning by recognizing the emotional states of students during their learning processes and giving adequate feedback. This study consists of three research stages:(1) Design both the emotional recognition system and the tutoring strategy module. (2) Design the digital arts learning content module, and the emotional feedback mechanism via the HCI design of interactive avatars. (3) Integrate and evaluate the entire system via a two-stage evaluation. We hope to enhance learners' motivation and interest via affective interaction design, and thereby improve their learning performance. According the results of the evaluation, the system usability was rated highly satisfactory by users. Furthermore, ATS is not only attractive to users, but also increases learning motivation and self-conscious learning achievement.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Affective Learning Interface with an Interactive Animated Agent

Chao

Lin

et al. 2012

2012 IEEE Fourth International Conference on Digital Game and Intelligent Toy Enhanced Learning

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“…In order to make such interaction more natural and efficient, virtual agents have been developed. They are computer generated, animated and artificial intelligence virtual characters (usually with human-like appearance [1]), which are capable of responding with adequate verbal or non-verbal behaviors to the users [2], [3]. With the development of virtual agent technologies, researchers are seeking new methods to make the agent perceive and perform more like humans [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

Backchannel Prediction for Mandarin Human-Computer Interaction

Mao

Peng

Xue

et al. 2015

IEICE Trans. Inf. & Syst.

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SUMMARYIn recent years, researchers have tried to create unhindered human-computer interaction by giving virtual agents human-like conversational skills. Predicting backchannel feedback for agent listeners has become a novel research hot-spot. The main goal of this paper is to identify appropriate features and methods for backchannel prediction in Mandarin conversations. Firstly, multimodal Mandarin conversations are recorded for the analysis of backchannel behaviors. In order to eliminate individual difference in the original face-to-face conversations, more backchannels from different listeners are gathered together. These data confirm that backchannels occurring in the speakers' pauses form a vast majority in Mandarin conversations. Both prosodic and visual features are used in backchannel prediction. Four types of models based on the speakers' pauses are built by using support vector machine classifiers. An evaluation of the pause-based prediction model has shown relatively high accuracy in consideration of the optional nature of backchannel feedback. Finally, the results of the subjective evaluation validate that the conversations performed between humans and virtual listeners using backchannels predicted by the proposed models is more unhindered compared to other backchannel prediction methods. key words : human-computer interaction, virtual agent, backchannel, Mandarin, support vector machine

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“…Several tutoring systems, designed for typically-developing individuals, are increasingly incorporating affect responsiveness into their pedagogical strategies [70][71][72][73]. An example is Affective AutoTutor [72] which is an affect-responsive dialogue-based tutoring system for computer literacy.…”

Section: Physiology-based Modeling Of Engagement During Naturalistic mentioning

confidence: 99%

“…Several recent tutoring systems, designed for typically developing individuals, are increasingly incorporating affect responsiveness into their pedagogical strategies [70][71][72][73]. These tutoring systems were reported to lead to better learning outcomes and to higher levels of engagement than their non-affectresponsive equivalent counterparts.…”

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confidence: 99%

Psychophysiological analysis of a pedagogical agent and robotic peer for individuals with autism spectrum disorders.

Saadatzi¹

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Agent based affective tutoring systems: A pilot study

Cited by 75 publications

References 13 publications

An Affective Learning Interface with an Interactive Animated Agent

An Affective Learning Interface with an Interactive Animated Agent

Backchannel Prediction for Mandarin Human-Computer Interaction

Psychophysiological analysis of a pedagogical agent and robotic peer for individuals with autism spectrum disorders.

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