Pedagogical agents on the Web

Shaw, Erin; Johnson, W. Lewis; Ganeshan, Rajaram

doi:10.1145/301136.301210

Cited by 118 publications

(52 citation statements)

References 17 publications

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“…This makes it possible to create artificial agents that replicate the results of social psychology [18] by interacting with humans like humans do [42]. In a teaching perspective, this was used, e.g., to develop agents helping students to learn procedural tasks [14] or instructing medical personnel on how to use web-based services [39].…”

Section: Computingmentioning

confidence: 99%

Predicting online lecture ratings based on gesturing and vocal behavior

Cheng

Salamin

Salvagnini

et al. 2014

J Multimodal User Interfaces

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Nonverbal behavior plays an important role in any human-human interaction. Teaching -a inherently social activity -is not an exception. So far, the effect of nonverbal behavioral cues accompanying lecture delivery was investigated in the case of traditional ex-cathedra lectures, where students and teachers are co-located. However, it is becoming increasingly more frequent to watch lectures online and, in this new type of setting, it is still unclear what the effect of nonverbal communication is. This article tries to address the problem and proposes experiments performed over the lectures of a popular web repository ("Videolectures"). The results show that automatically extracted nonverbal behavioral cues (prosody, voice quality and gesturing activity) predict the ratings that "Videolectures" users assign to the presentations.

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Section: Computingmentioning

confidence: 99%

Predicting online lecture ratings based on gesturing and vocal behavior

Cheng

Salamin

Salvagnini

et al. 2014

J Multimodal User Interfaces

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show abstract

“…For this reason, we expect that a majority of E-learning application will make use of web technologies for content provision and delivery, even if used from a DVD or on the intranet. Research to utilize the web as a platform for E-learning is manifold, for an example see [12].…”

Section: Introductionmentioning

confidence: 99%

Detailed Monitoring of User’s Gaze and Interaction to Improve Future E-Learning

Drewes

Atterer

Schmidt

2007

Universal Access in Human-Computer Interaction. Ambient Interaction

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Abstract. In this paper, we investigate how to use future interaction technologies to enhance learning technologies. We examine in detail how tracking the mouse pointer and observing the user's gaze can help to monitor the use of web applications and in particular E-learning applications. To improve learning and teaching, it is of interest to understand in what order and to what extent users read texts, how much time they spend on individual parts of the teaching materials, and where they get stuck. Based on a standard web browser as an application platform, extended with a gaze tracking facility, we conducted studies to explore the feasibility of this novel approach. The concept includes an extension of current technologies to allow JavaScript code running in the browser to access the current gaze position of the user. Our work shows how pieces of web technology and eye gaze tracking can be put together to create a new platform for E-learning that provides additional benefits for learners and teachers.

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“…On the other hand, many applications presume the ability to correctly interpret the beliefs, motives and intentions underlying human behavior (such as tutoring systems, dialogue systems, mixed-initiative planning systems, or systems that learn from observation) and could benefit from a model of how emotion motivates action, distorts perception and inference, and communicates information about mental state. Emotions play a powerful role in social influence, a better understanding of which would benefit applications that attempt to shape human behavior, such as psychotherapy applications (Marsella, Johnson, & LaBore, 2000;Rothbaum et al, 1999), tutoring systems (Lester, Stone, & Stelling, 1999;Ryokai, Vaucelle, & Cassell, in press;Shaw, Johnson, & Ganeshan, 1999), and marketing applications (André, Rist, Mulken, & Klesen, 2000;Cassell, Bickmore, Campbell, Vilhjálmsson, & Yan, 2000). Lastly, models of emotion may give insight into building models of intelligent behavior in general.…”

Section: Introductionmentioning

confidence: 99%