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All or Nothing: Levels of Sociability of a Pedagogical Software Agent and Its Impact on Student Perceptions and Learning.
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2005
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EngineeringEducationSoftware Engineering EducationCommunicationSoftware AgentInteractive LearningSocial Learning EnvironmentVirtual ClassroomPedagogyLearning SciencesHuman Agent InteractionUser ExperienceStudent-centered LearningLearning AnalyticsStudent PerceptionsHigher EducationPerformance StudiesAgent TechnologySocial ComputingPedagogical Software AgentHuman-computer InteractionProfessional DevelopmentComputer-based EducationVirtual AgentPedagogical Software AgentsDigital Learning
This article reports the results of an experimental study on multimedia learning environments, which investigated the impact of increasing the social behaviors of a pedagogical agent on students' perceptions of social presence, their perceptions of the learning experience, and learning. Paradoxically, in this experiment students detected higher degrees of social presence in both the text only and the fully animated social agent conditions than students in the voice only and the static image of the agent with voice conditions. Furthermore, students had more positive perceptions of the learning experience in the text only condition. The results support the careful design of social behaviors for animated pedagogical agents if they are to be of educational value, otherwise, the use of agent technology can actually detract from the learning experience. ********** Recent research in technological learning environments has begun to focus on the educational benefits of including pedagogical software agents. The work of Reeves and Nass (1996) has demonstrated that in human-to-computer interactions, humans will anthropomorphize the software even to the extent of applying social rules of human-to-human communication to the computer agents. The application of these rules to interactions with a software agent in an electronic learning environment may have educational benefits as well. Pedagogical software agents are animated interface agents in instructional environments that draw upon human-to-human social communication scripts by embodying observable human characteristics (such as the use of gestures and facial expressions). Research in the past few years on the use of pedagogical software agents has expanded to cover a variety of pedagogical roles taken on by the agent. The Teachable Agent Group at Vanderbilt (TAG-V) has developed social agents who play the role of the tutee rather than the tutor. In this environment where students learn by teaching, students are able to adjust the agent's attitude, and teach him or her relevant skills and concepts. The Tutoring Research Group at the University of Memphis, under Art Grasser, has developed a system called AutoTutor, which uses conversational agents that act as dialogue partners to assist learners in the active construction of knowledge. The Pedagogical Agent Learning Systems (PALS) laboratory at the University of Florida, under Amy Baylor, has developed a multiple agent environment called Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) in which the agents act as mentors to students. Research on the MIMIC environment has focused on manipulating the characteristics of the agents such as programming the agents to offer feedback from an instructivist and constructivist theoretical perspective (Baylor, 2002). Baylor has also investigated the impact of using multiple agents that serve as experts and/or motivators to students (Baylor & Ebbers, 2003). The agents in all of the aforementioned environments are responsive to user input. However, even in a more didactic electronic teaching environment, agents can maintain motivational and affective features. According to Atkinson (2002): In particular, may be possible to structure an example-based learning environment so that a lifelike character can exploit verbal (e.g., instructional explanations) as well as nonverbal forms of communication (e.g., gaze, gesture) within the examples themselves in an effort to promote a learner's motivation toward the task and his or her cognitive engagement in it. (p. 416) In traditional classroom settings it is difficult to deny that teaching by its very nature involves some sort of intervention in the learning process of students in an attempt to facilitate their acquisition of desired educational outcomes (Shuell, 1996). One form that this intervention takes is providing cues as to which in the material being studied is most important and the manner in which students might process the information (p. …