2,843 research outputs found

    Generating socially appropriate tutorial dialog

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    Analysis of student-tutor coaching dialogs suggest that good human tutors attend to and attempt to influence the motivational state of learners. Moreover, they are sensitive to the social face of the learner, and seek to mitigate the potential face threat of their comments. This paper describes a dialog generator for pedagogical agents that takes motivation and face threat factors into account. This enables the agent to interact with learners in a socially appropriate fashion, and foster intrinsic motivation on the part of the learner, which in turn may lead to more positive learner affective states

    Towards an Intelligent Tutor for Mathematical Proofs

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    Computer-supported learning is an increasingly important form of study since it allows for independent learning and individualized instruction. In this paper, we discuss a novel approach to developing an intelligent tutoring system for teaching textbook-style mathematical proofs. We characterize the particularities of the domain and discuss common ITS design models. Our approach is motivated by phenomena found in a corpus of tutorial dialogs that were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor for textbook-style mathematical proofs can be built on top of an adapted assertion-level proof assistant by reusing representations and proof search strategies originally developed for automated and interactive theorem proving. The resulting prototype was successfully evaluated on a corpus of tutorial dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453

    Politeness and Alignment in Dialogues with a Virtual Guide

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    Language alignment is something that happens automatically in dialogues between human speakers. The ability to align is expected to increase the believability of virtual dialogue agents. In this paper we extend the notion of alignment to affective language use, describing a model for dynamically adapting the linguistic style of a virtual agent to the level of politeness and formality detected in the user’s utterances. The model has been implemented in the Virtual Guide, an embodied conversational agent giving directions in a virtual environment. Evaluation shows that our formality model needs improvement, but that the politeness tactics used by the Guide are mostly interpreted as intended, and that the alignment to the user’s language is noticeable

    Using Medical Students to Enhance Curricular Integration of Cross-Cultural Content

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    We hypothesized that an interested medical student group would be helpful in reviewing tutorial cases and giving relevant feedback on the curricular integration of cross-cultural content using case triggers in a preclinical gastrointestinal pathophysiology course. Self-selected student leaders (n = 9) reviewed pre-existing problem-based learning tutorial cases (n = 3) with cross-cultural triggers, and provided narrative feedback to course faculty. The cases were modified and used for the entire class in the following 2 years. Participating course students' comments and teaching faculty feedback were also noted. Outcomes were a change in case content, student global evaluations of the course, and self-reported faculty comfort with teaching the cases. All three tutorial cases were reviewed by a separate group of 2–3 students. Major and minor revisions were made to each case based on the student feedback. These cases were used in 2007 and 2008 and were the major change to the course during that time. Overall course evaluation scores improved significantly from 2006 to 2008 (p = 0.000). Tutors (n = 22 in 2007; n = 23 in 2008) expressed relief during tutor meetings that students had reviewed the cases. A general framework for eliciting student feedback on problem-based cases was developed. Student feedback, consisting of self-selected students' case reviews and solicited course and tutor comments, added value to a curricular reform to improve the integration of cross-cultural content into a problem-based learning curriculum. Our study underscores the fundamental link between teachers and students as partners in curricular development

    Building Artificially Intelligent Learning Games

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    The idea of digital game-based learning (DGBL) is gaining acceptance among researchers, game designers, educators, parents, and students alike. Building new educational games that meet educational goals without sacrificing what makes games engaging remains largely unrealized, however. If we are to build the next generation of learning games, we must recognize that while digital games might be new, the theory and technologies we need to create DGBL has been evolving in multiple disciplines for the last 30 years. This chapter will describe an approach, based on theories and technologies in education, instructional design, artificial intelligence, and cognitive psychology, that will help us build intelligent learning games (ILGs)
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